Siddharth Hariharan, et al v. Adobe Systems, Inc., et al

Filing 10

Filed (ECF) Respondents Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall and Daniel Stover answer to 23f petition. Date of service: 11/18/2013. [8867390] (BPG)

Download PDF
No. 13-80223 In the United States Court Of Appeals For the Ninth Circuit __________________________ IN RE HIGH-TECH EMPLOYEE ANTITRUST LITIGATION _________________________ Petition for permission to appeal from the United States District Court Northern District of California The Honorable Lucy H. Koh, Presiding Case No. 5:11-2509-LHK SUPPLEMENTAL EXCERPTS OF RECORD Vols. I-VI LIEFF CABRASER HEIMANN & BERNSTEIN, LLP Kelly M. Dermody Brendan P. Glackin Dean M. Harvey 275 Battery Street, 29th Floor San Francisco, CA 94111-3339 Telephone: 415.956.1000 Facsimile: 415.956.1008 JOSEPH SAVERI LAW FIRM Joseph R. Saveri Joshua P. Davis Lisa J. Leebove James G. Dallal 505 Montgomery Street, Suite 625 San Francisco, California 94111 Telephone: 415.500.6800 Facsimile: 415.500.6803 Co-Lead Class Counsel 1141390.1 In re High-Tech Employees Antitrust Litigation Case No. 11-2509 SUPPLEMENTAL EXCERPTS OF THE RECORD Table of Contents Docket Entry Document Title Vol. Page 1 1 2 163 Expert Report of Edward E. Leamer, PH.D. Reply Expert Report of Edward E. Leamer, PH.D. Supplemental Expert Report of Edward E. Leamer, PH.D Rebuttal Supplmental Expert Report of Edward E. Leamer, PH.D 3 317 3 398 3 464 3 526 Expert Witness Report of Kevin F. Hallock Exhibit 71 of Declaration of Anne Shaver in Support of Motion for Class Certification (Dept. of Justice Competitive Impact Statement) 4 566 4 686 Opposition to Plaintiffs' Motion for Class Certification, Case No. 12-80188 4 Order Denying Costco's 23(f) Petition 4 UNDER SEAL SUPPLEMENTAL EXCERPTS OF RECORD 715 718 PUBLIC SUPPLEMENTAL EXCERPTS OF RECORD 494 321 518-1 518-5 424-4 470-1 424-1 188-10 209 5 Transcript of Proceedings before the Honorable Lucy H. Koh - August 8, 2013 Transcript of Proceedings before the Honorable Lucy H. Koh - January 17, 2013 Expert Report of Edward E. Leamer, PH.D. Reply Expert Report of Edward E. Leamer, PH.D. Supplemental Expert Report of Edward E. Leamer, PH.D Rebuttal Supplemental Expert Report of Edward E. Leamer, PH.D 5 719 5 839 5 905 5 967 Expert Witness Report of Kevin F. Hallock 6 1009 Docket Report 6 1129 Certificate of Service 6 1 1 UNITED STATES DISTRICT COURT 2 NORTHERN DISTRICT OF CALIFORNIA 3 SAN JOSE DIVISION 4 5 6 7 8 9 IN RE: HIGH-TECH EMPLOYEE ANTITRUST LITIGATION, _________________________ THIS DOCUMENT RELATES TO: ALL ACTIONS _________________________ ) ) ) ) ) ) ) ) C-11-02509 LHK SAN JOSE, CALIFORNIA AUGUST 8, 2013 PAGES 1-161 10 11 TRANSCRIPT OF PROCEEDINGS BEFORE THE HONORABLE LUCY H. KOH UNITED STATES DISTRICT JUDGE 12 A P P E A R A N C E S: 13 FOR THE PLAINTIFFS: 14 15 16 17 18 19 20 21 22 23 JOSEPH SAVERI LAW FIRM BY: JOSEPH SAVERI LISA J. LEEBOVE JAMES G. DALLAL 255 CALIFORNIA STREET, SUITE 450 SAN FRANCISCO, CALIFORNIA 94111 LIEFF, CABRASER, HEIMANN & BERNSTEIN BY: KELLY M. DERMODY BRENDAN P. GLACKIN DEAN M. HARVEY ANNE B. SHAVER LISA J. CISNEROS 275 BATTERY STREET, 30TH FLOOR SAN FRANCISCO, CALIFORNIA 94111 APPEARANCES CONTINUED ON NEXT PAGE OFFICIAL COURT REPORTER: LEE-ANNE SHORTRIDGE, CSR, CRR CERTIFICATE NUMBER 9595 24 25 PROCEEDINGS RECORDED BY MECHANICAL STENOGRAPHY TRANSCRIPT PRODUCED WITH COMPUTER UNITED STATES COURT REPORTERS 1 2 1 APPEARANCES (CONTINUED) 2 FOR DEFENDANT GOOGLE: 3 4 KEKER & VAN NEST BY: ROBERT A. VAN NEST DANIEL E. PURCELL JUSTINA K SESSIONS 633 BATTERY STREET SAN FRANCISCO, CALIFORNIA 94111 5 MAYER BROWN BY: LEE H. RUBIN TWO PALO ALTO SQUARE, SUITE 300 PALO ALTO, CALIFORNIA 94306 6 7 8 FOR DEFENDANT APPLE: 9 10 11 12 13 O'MELVENY & MYERS BY: GEORGE A. RILEY MICHAEL F. TUBACH CHRISTINA J. BROWN TWO EMBARCADERO CENTER 28TH FLOOR SAN FRANCISCO, CALIFORNIA 94111 FOR DEFENDANTS ADOBE AND INTUIT: JONES DAY BY: DAVID C. KIERNAN LIN W. KAHN CRAIG E. STEWART 555 CALIFORNIA STREET, 26TH FLOOR SAN FRANCISCO, CALIFORNIA 94104 FOR DEFENDANT INTEL: BINGHAM MCCUTCHEN BY: DONN P. PICKETT FRANK HINMAN SUJAL SHAH THREE EMBARCADERO CENTER SAN FRANCISCO, CALIFORNIA 14 15 16 17 18 94111 19 20 21 FOR DEFENDANT PIXAR: COVINGTON & BURLING BY: EMILY J. HENN 333 TWIN DOLPHIN DRIVE, SUITE 700 REDWOOD SHORES, CALIFORNIA 94065 22 23 24 25 UNITED STATES COURT REPORTERS 2 3 1 SAN JOSE, CALIFORNIA 2 3 4 5 6 7 AUGUST 8, 2013 P R O C E E D I N G S (COURT CONVENED AND THE FOLLOWING PROCEEDINGS WERE HELD:) THE CLERK: CALLING CASE NUMBER C-11-02509 LHK, IN RE: HIGH-TECH EMPLOYEE ANTITRUST LITIGATION. MR. GLACKIN: BRENDAN GLACKIN, LEIFF, CABRASER, HEIMANN & BERNSTEIN ON BEHALF OF THE PLAINTIFFS. 8 MS. DERMODY: GOOD AFTERNOON, YOUR HONOR. 9 KELLY DERMODY, LEIF, CABRASER. AND THE OTHER LEIF, CABRASER 10 PEOPLE WITH US ARE MY PARTNER, DEAN HARVEY, AND ASSOCIATES 11 ANNE SHAVER AND LISA CISNEROS. 12 13 AND ALSO IN THE COURTROOM TODAY ARE NAMED PLAINTIFFS, BRANDON MARSHAL AND MIKE DEVINE. 14 THE COURT: 15 MR. SAVERI: 16 JOSEPH SAVERI. 17 OKAY. GOOD AFTERNOON, YOUR HONOR. WITH ME FROM MY OFFICE ARE LISA LEELOVE AND JAMES DALLAL. 18 THE COURT: OKAY. 19 MR. VAN NEST: GOOD AFTERNOON, YOUR HONOR. 20 BOB VAN NEST FROM KEKER & VAN NEST FOR GOOGLE. 21 I'M HERE WITH DAN PURCELL AND TINA SESSIONS. 22 ALSO, LEE RUBIN FROM MAYER BROWN. 23 AND I'VE BEEN ASKED TO SPEAK ON BEHALF OF ALL DEFENDANTS 24 25 THIS AFTERNOON. MR. RILEY: GOOD AFTERNOON, YOUR HONOR. UNITED STATES COURT REPORTERS GEORGE RILEY 3 4 1 OF O'MELVENY & MYERS FOR APPLE. 2 CHRISTINA BROWN AND MICHAEL TUBACH. 3 THE COURT: 4 MR. PICKETT: 5 OKAY. I'M JOINED BY MY COLLEAGUES GOOD AFTERNOON. GOOD AFTERNOON. DONN PICKETT. HERE ALONG WITH FRANK HINMAN AND SUJAL SHAH FOR INTEL. 6 THE COURT: 7 MR. KIERNAN: OKAY. GOOD AFTERNOON. GOOD AFTERNOON, YOUR HONOR. 8 DAVID KIERNAN OF JONES DAY ON BEHALF OF ADOBE. 9 TODAY IS LIN KAHN. 10 BECAUSE OF TRIAL ON ANOTHER MATTER. THE COURT: 12 MR. KIERNAN: 13 THE COURT: 15 OKAY. 18 OKAY. MR. KIERNAN AND? I'M SORRY. AND LIN KAHN. OKAY. THANK YOU. AND THERE'S NO ONE HERE FOR LUCASFILM, PIXAR, AND INTUIT; CORRECT? 16 17 HERE WITH ME BOB MITTELSTAEDT COULDN'T BE HERE TODAY 11 14 I'M MS. HENN: BURLING. YOUR HONOR, EMILY HENN, COVINGTON & I'M HERE FOR THE CMC FOR PIXAR. THE COURT: OKAY. WOULD YOU MIND IF WE DID THAT AT 19 THE END, OR WOULD YOU LIKE TO DO THAT AT THE BEGINNING? 20 THAT OKAY IF IT'S AT THE END? 21 MS. HENN: 22 MR. STEWART: 23 24 25 IS YES. YOUR HONOR, CRAIG STEWART. I'M HERE ON BEHALF OF INTUIT. THE COURT: OKAY. ALL RIGHT. WELL, GOOD AFTERNOON TO EVERYONE. UNITED STATES COURT REPORTERS 4 5 1 2 3 4 SO ACTUALLY THE FIRST QUESTION WOULD GO TO INTUIT, LUCASFILM, AND PIXAR, AS WELL AS THE PLAINTIFFS. WHEN DO YOU ANTICIPATE FILING YOUR MOTION FOR PRELIMINARY APPROVAL? 5 MS. DERMODY: WELL, YOUR HONOR, WE ARE HEAVILY IN THE 6 PROCESS OF TRYING TO DOCUMENT THAT AGREEMENT, AND WITH THE 7 ADDITION OF THE INTUIT SETTLEMENT, WE HAVE ANOTHER FAMILY TO 8 DEAL WITH IN FIGURING OUT THE BEST PROCESS. 9 10 WE'RE HOPING TO DO THAT VERY, VERY SOON. HARD TO ACCOMPLISH THAT, YOUR HONOR. 11 12 13 WE'RE WORKING THE COURT: CAN WE SET A DEADLINE BY WHICH THAT WILL BE DONE? MR. SAVERI: I THINK THERE ARE PROBABLY TWO THINGS WE 14 WOULD NEED TO DO: 15 APPROVAL PAPERS; AND THEN WE WOULD LIKE TO COME IN AS SOON AS 16 POSSIBLE AND HAVE THE HEARING ON PRELIMINARY APPROVAL. 17 SET A DEADLINE FOR FILING THE PRELIMINARY THE COURT: WELL, I HAVE SOME POSSIBLE HEARING DATES 18 FOR YOU, SO I NEED TO KNOW WHEN YOU'RE GOING TO FILE AND WE CAN 19 GO FROM THERE. 20 MS. DERMODY: 21 THE COURT: 22 MS. DERMODY: 23 THE COURT: 24 25 WHAT DO YOU HAVE, YOUR HONOR? SO -THAT MIGHT GIVE US A TARGET. WELL, OCTOBER 3RD, NOVEMBER 21, DECEMBER 19, JANUARY 9, FEBRUARY 13, FEBRUARY 20. MR. SAVERI: YOUR HONOR, CAN THE -- IS THERE ANY WAY UNITED STATES COURT REPORTERS 5 6 1 TO GET IN EARLIER THAN THAT FOR THE PRELIMINARY APPROVAL 2 HEARING? 3 4 5 THE COURT: EARLIER THAN OCTOBER 3? WHEN ARE YOU GOING TO FILE? MS. HENN: YOUR HONOR, I THINK THAT WOULD BE 6 AGGRESSIVE IN LIGHT OF WHERE WE ARE AT THIS POINT IN TIME, SO I 7 THINK WE WOULD SUPPORT A DATE NO EARLIER THAN OCTOBER. 8 THE COURT: WELL, HOW QUICKLY ARE YOU GOING TO FILE? 9 MR. SAVERI: WELL, THE -- I DON'T -- I'M HOPING, 10 MAYBE I'M OVERLY OPTIMISTIC, THAT WE'LL HAVE THE DOCUMENTATION 11 DONE IN A COUPLE WEEKS AND WE WOULD PREPARE -- BE PREPARED TO 12 FILE SHORTLY THEREAFTER. 13 14 15 THE PRELIMINARY APPROVAL HEARING IS GOING TO BE UNOPPOSED. THE COURT: SO THERE HAVE BEEN NO EXCHANGES OF DRAFTS YET OF FINAL DOCUMENTS? 16 MR. SAVERI: 17 MR. STEWART: 18 NO, WE HAVE EXCHANGED DOCUMENTS. NOT WITH INTUIT, YOUR HONOR. WE HAVEN'T RECEIVED THE SETTLEMENT DOCUMENTS YET. 19 THE COURT: 20 MS. HENN: I SEE. WHAT ABOUT PIXAR AND LUCASFILM? WE'VE RECEIVED ONE DOCUMENT, BUT THERE ARE 21 MANY DOCUMENTS THAT WE HAVEN'T SEEN, AND IT TOOK A WHILE TO GET 22 THE FIRST DOCUMENTS. 23 24 25 SO WE DO THINK THIS IS GOING TO TAKE SOME TIME AND SHOULDN'T BE RUSHED. THE COURT: OKAY. SO GIVE ME A DEADLINE THAT SEEMS UNITED STATES COURT REPORTERS 6 7 1 REALISTIC FOR FILING THE MOTION, AND THEN YOU CAN PICK ANY OF 2 THESE DATES FOR THE HEARING. 3 MS. DERMODY: IF WE'RE WORKING FROM OCTOBER 3RD, YOUR 4 HONOR, I THINK THE REAL QUESTION THEN IS HOW MUCH TIME DO YOU 5 THINK YOUR HONOR WOULD LIKE TO HAVE WITH THE PAPERS BEFORE THE 6 HEARING? 7 SO THERE WON'T BE ANY ADDITIONAL FILINGS, PRESUMABLY, AFTER THE 8 MOTION FOR PRELIMINARY APPROVAL, AND IT'S REALLY ABOUT THE 9 COURT'S CONVENIENCE. 10 11 BECAUSE AS MR. SAVERI SAID, IT WILL BE UNCONTESTED, THE COURT: WELL, I NEED A MINIMUM OF TWO WEEKS, MINIMUM. 12 MS. DERMODY: 13 THE COURT: 14 MS. DERMODY: 15 YES? SO SEPTEMBER 19? THAT WOULD BE THE LAST POSSIBLE DATE. I THINK THAT SOUNDS ACHIEVABLE. SOUND RIGHT FOR YOU ALL? 16 MS. HENN: 17 YES, YOUR HONOR. THE COURT: I THINK SEPTEMBER 12TH WOULD BE EVEN 18 BETTER, BUT I'LL TAKE THE 19TH. 19 MS. DERMODY: 20 MR. SAVERI: THANK YOU, YOUR HONOR. I THINK WE'D LIKE TO GET IT DONE AS SOON 21 AS WE CAN AND GET THE MOTIONS ON FILE AND GIVE THE COURT AS 22 MUCH TIME AS WE CAN WITH THE PAPERS. 23 24 25 THE COURT: UM-HUM. WHY DON'T WE SAY SEPTEMBER 16TH? IS THAT OKAY? MS. HENN, DOES THAT GIVE YOU ENOUGH TIME, OR -- IF YOU WANT UNITED STATES COURT REPORTERS 7 8 1 UNTIL THE 19TH, THAT'S FINE. 2 MS. HENN: 3 THE COURT: 4 THREE, RIGHT? SEPTEMBER 19TH WOULD BE BETTER. OKAY. MS. HENN: 6 MS. DERMODY: 7 THE COURT: SEPTEMBER 19TH. 9 10 YES. MS. DERMODY: WILL THAT BE 1:30 OR 2:00 O'CLOCK, YOUR HONOR? 12 MS. DERMODY: 13 THE COURT: 1:30. THANK YOU. OKAY. NOW, ARE THERE ANY OTHER NEGOTIATIONS WITH OTHER REMAINING DEFENDANTS? 15 17 SO FILE THE MOTION BY IT WILL BE HEARD ON OCTOBER THE 3RD. THE COURT: 16 YES. OKAY. 11 14 SO FILE YOUR -- ALL ALL THREE? 5 8 ALL RIGHT. MR. SAVERI: OR NOT? WELL, YOUR HONOR, WE WENT TO A MEDIATION ON WHICH WE REPORTED AND THAT MEDIATION IS NOW CONCLUDED. SO -- 18 THE COURT: 19 DON'T WANT ANY DETAIL, BUT -- 20 MR. SAVERI: 21 22 23 THERE'S NO FURTHER EFFORTS? I MEAN, I I GUESS I WANT TO BE CAREFUL ABOUT THAT. THERE'S REALLY NOTHING ELSE THAT I CAN REPORT RIGHT NOW. THE COURT: OKAY. COULD I SET JUST A SETTLEMENT STATUS REPORT DATE FOR A WEEK FROM NOW? 24 MS. DERMODY: 25 THE COURT: OR -- SURE, YOUR HONOR. WHAT MAKES SENSE? I DON'T KNOW IF THE UNITED STATES COURT REPORTERS 8 9 1 2 3 HEARING IS GOING TO MAKE A DIFFERENCE. MR. VAN NEST: YOUR HONOR, THIS IS BOB VAN NEST. I DON'T THINK ANYTHING WILL CHANGE IN A WEEK. I THINK, AS 4 MR. SAVERI PUT IT QUITE CORRECTLY, THE MEDIATION OCCURRED, IT'S 5 OVER, AND NOTHING IS HAPPENING. 6 THE COURT: 7 MR. VAN NEST: 8 9 10 11 OKAY. WITH RESPECT TO THE FOUR REMAINING DEFENDANTS, NOTHING IS GOING TO CHANGE IN THE NEXT WEEK. THE COURT: OKAY. WHAT ABOUT THE NEXT TWO WEEKS, THREE WEEKS? MR. VAN NEST: I THINK IF YOU SET IT OUT A MONTH, 12 THEN FINE, WE'LL SUBMIT A REPORT AND PERHAPS SOMETHING WILL 13 HAPPEN IN THAT PERIOD OF TIME. 14 THAT'S FINE. OR SET IT FOR THE 19TH AND WE'LL FILE SOMETHING ALONG WITH 15 THE OPENING PAPERS. 16 THE COURT: OKAY. LET ME ASK -- I MEAN, OBVIOUSLY 17 YOU MAY NOT KNOW AND YOU HAVE TO CONSULT WITH CLIENTS, BUT DO 18 YOU NEED A RULING ON THE MOTION? 19 SUMMARY JUDGMENT RULING? 20 DO YOU THINK THE PARTIES NEED FOR THE REMAINING FOUR 21 DEFENDANTS? 22 23 MR. SAVERI: OR DO YOU THINK YOU NEED A WHAT -- WHAT ADDITIONAL INFORMATION YOUR HONOR, JUST SPEAKING FOR MYSELF, I THINK WE CAN -- 24 THE COURT: 25 MR. SAVERI: UM-HUM. -- I DON'T THINK WE NEED TO SET IT AT UNITED STATES COURT REPORTERS 9 10 1 ANY PARTICULAR MILESTONE. 2 THE COURT: 3 UM-HUM. MR. SAVERI: I THINK, FROM THE PLAINTIFFS' 4 PERSPECTIVE, WE'RE READY TO TALK. 5 APPROPRIATE TO DO ANOTHER ROUND OF MEDIATION, I THINK WE'D BE 6 WILLING TO DO THAT. 7 THE COURT: 8 MR. SAVERI: 9 10 WE'RE -- IF IT WAS UM-HUM. TO ME I THINK IT'S IMPORTANT TO KEEP TALKING ALL THE TIME, SO I'D LIKE TO KEEP THE COMMUNICATION GOING. 11 SO I DON'T -- TO ANSWER YOUR QUESTION DIRECTLY, I DON'T 12 THINK WE SHOULD PUT IT OFF UNTIL SUMMARY JUDGMENT OR RULING ON 13 THE CLASS. 14 15 I MEAN, OBVIOUSLY EVERYBODY IS INTERESTED TO KNOW WHAT'S GOING TO HAPPEN AS A RESULT OF TODAY OR -- 16 THE COURT: UM-HUM. 17 MR. SAVERI: 18 THE COURT: 19 MR. VAN NEST: 20 THE COURT: -- DOWN THE ROAD. UM-HUM. LET ME HEAR FROM MR. -- MR. VAN NEST. THANK YOU, YOUR HONOR. OF COURSE I WAS GOING TO SAY THAT. 21 WHAT DO YOU THINK? 22 MR. VAN NEST: 23 OBVIOUSLY CLASS CERT IS A VERY IMPORTANT MILESTONE. 24 THE COURT: UH-HUH. 25 MR. VAN NEST: OBVIOUSLY IF WE GO PAST THAT, SUMMARY UNITED STATES COURT REPORTERS 10 11 1 JUDGMENT IS AN IMPORTANT MILESTONE. 2 BUT I AGREE WITH MR. SAVERI. THERE'S NOTHING MAGIC ABOUT 3 ANY PARTICULAR TIME. I JUST THINK IT'S UNLIKELY THAT ANYTHING 4 WILL HAPPEN BEFORE YOU RULE ON CLASS CERT. 5 THE COURT: I SEE. 6 MR. VAN NEST: I'M NOT SAYING ANYTHING WOULD HAPPEN 7 AFTER THAT, EITHER, BUT I DON'T THINK ANYTHING WILL HAPPEN 8 UNTIL THEN. 9 THE COURT: 10 UNTIL THERE'S AN ACTUAL RULING? MR. VAN NEST: A RULING OR AN INDICATION FROM YOUR 11 HONOR AS TO WHAT THE RULING WILL BE, YES. 12 ANYTHING IS LIKELY TO HAPPEN IN THAT PERIOD. 13 I DON'T THINK ON THE OTHER HAND, IF MR. SAVERI WANTS TO TALK, THAT'S 14 FINE. WE CAN CERTAINLY SUBMIT A REPORT ON THE 19TH. 15 WON'T TAX ANYBODY. 16 THE COURT: 17 MR. VAN NEST: 18 THE COURT: THAT UM-HUM. AND THEN YOU'LL KNOW. ALL RIGHT. WELL, TELL ME, WITH REGARD 19 TO -- ONCE A RULING IS ISSUED, WHAT'S GOING TO HAPPEN? 20 SAY I CERTIFY A CLASS. 21 AT THAT POINT? 22 MS. DERMODY: 23 LET'S DO YOU WANT TO HAVE ANOTHER ADR SESSION YOUR HONOR, ACTUALLY. 24 25 THE COURT: I THINK THAT WOULD BE VERY HELPFUL, LET ME SEE IF THE DEFENDANTS ARE WILLING. IS THAT SOMETHING THAT YOU'D BE WILLING TO DO AT THAT UNITED STATES COURT REPORTERS 11 12 1 2 3 POINT? MR. VAN NEST: CONSIDER ADR. 4 THE COURT: 5 MR. VAN NEST: 6 UM-HUM. THE COURT: 8 MR. VAN NEST: 10 11 12 13 14 15 AS I SAID, I THINK IT'S UNLIKELY ANYTHING WOULD HAPPEN BEFORE YOUR RULING ON CLASS CERT. 7 9 YOUR HONOR, WE'RE ALWAYS WILLING TO OKAY. WE OBVIOUSLY FEEL STRONGLY ABOUT THAT ISSUE, AS WE'RE GOING TO BE DISCUSSING IN A MOMENT. SO I DO THINK, THOUGH, THAT ADR BEFORE THAT TIME WOULD NOT BE PRODUCTIVE. I DO AGREE WITH YOU THERE. THE COURT: CERTIFY A CLASS. OKAY. ALL RIGHT. LET'S SAY I DON'T AT THAT POINT? MR. VAN NEST: I THINK THE SAME THING. THAT'S AN IMPORTANT MILESTONE FOR ALL OF US AND -- 16 THE COURT: ALL RIGHT. 17 MR. VAN NEST: 18 THE COURT: 19 MR. VAN NEST: 20 THE COURT: -- TALKING AFTER THAT WOULD BE -- WOULD MAKE SENSE? -- WORTHWHILE, YES. OKAY. WELL, I WOULD LIKE TO, BECAUSE IT 21 SOUNDS LIKE EITHER WAY THERE'S -- EITHER WAY IT SEEMS LIKE A 22 FURTHER ADR SESSION MIGHT BE HELPFUL AFTER A RULING. 23 24 25 SO CAN I GO AHEAD AND REFER YOU NOW AND SET A LONG ENOUGH LEAD TIME THAT YOU'RE ABLE TO MEET THAT DEADLINE? ASSUMING -- LET'S SAY ASSUMING YOU GET A RULING, I DON'T UNITED STATES COURT REPORTERS 12 13 1 KNOW, IN THE NEXT MONTH. 2 MR. VAN NEST: 3 THE COURT: 4 5 HOW MUCH TIME WOULD YOU NEED FOR ADR? TO GET READY FOR ADR? AND TO COMPLETE IT, BECAUSE I'LL SET A DEADLINE -MS. DERMODY: THE PROBLEM IS THE MEDIATORS' 6 SCHEDULES, YOUR HONOR. 7 THROUGH THIS, ALL OF US, COLLECTIVELY TRYING TO GET DATES. 8 THE COURT: 9 THE VERY GOOD MEDIATORS -- WE WENT MS. DERMODY: 10 11 SURE. AND IT WAS UNBELIEVABLE TO GET DATES OVER A FOUR MONTH PERIOD. SO WE MAY ALL HAVE GOOD WILL ABOUT WHEN WE COULD DO IT AND 12 HAVE AVAILABILITY. 13 BE THE SCHEDULE, WHEN THE RULING WILL COME OUT, AND WHEN YOU 14 WOULD LIKE US TO COMPLETE ADR, WE CAN CALL TODAY TO FIND OUT 15 SCHEDULES AND SEE IF WE CAN GET OURSELVES ON A CALENDAR JUST TO 16 HAVE THAT BOOKED. 17 SO THE SOONER WE KNOW WHAT YOU THINK WILL MR. VAN NEST: YOUR HONOR, IF YOU GAVE US 90 DAYS 18 FROM THE RULING, I THINK WE WOULD BE ABLE TO GET IN AND OUT OF 19 THE MEDIATION. 20 THE COURT: 21 MR. SAVERI: UM-HUM. MY CONCERN, THOUGH, YOUR HONOR, IS THAT 22 EVEN IF YOU WERE TO SAY TODAY, "I WANT YOU TO GO TO MEDIATION," 23 GIVEN THE WAY THE MEDIATORS' CALENDARS GO AND SCHEDULING, IT 24 WOULD BE, I MEAN, 60 OR 90 DAYS BEFORE WE COULD PROBABLY GET IN 25 FRONT OF A MEDIATOR IF THE PAST IS AN INDICATOR. UNITED STATES COURT REPORTERS 13 14 1 SO I'M A LITTLE WORRIED THAT -- IF YOUR HONOR WANTS US TO 2 GET IN AND DO IT, I THINK WE NEED TO -- IT WOULD BE USEFUL TO 3 HAVE SOME PARAMETERS. 4 I THINK A LOT OF IT DEPENDS ON WHEN YOU RULE AND THAT'S -- 5 THE COURT: UM-HUM. WELL, I AM TARGETING GETTING AN 6 ORDER OUT BY THE END OF THIS MONTH OR EARLY SEPTEMBER AT THE 7 LATEST, BUT PREFERABLY THE END OF AUGUST. 8 9 10 11 SO UNDERSTANDING THAT'S THE CASE, I WOULD SUGGEST YOU GO AHEAD AND JUST ASSUME ANY DAY AFTER LABOR DAY IS FAIR GAME FOR A MEDIATION AND JUST GO AHEAD AND SCHEDULE ONE. CAN I THEN SET YOU ON A NOVEMBER 15TH DEADLINE? 12 MR. VAN NEST: 13 MS. DERMODY: 14 MR. VAN NEST: 15 THE COURT: SURE. THAT MAKES SENSE, YOUR HONOR. THAT'S FINE, YOUR HONOR. ALL RIGHT. SO THEN THE REMAINING 16 DEFENDANTS WILL HAVE ANOTHER PRIVATE MEDIATION SESSION TO BE 17 COMPLETED BY NOVEMBER 15TH OF 2013. 18 MR. SAVERI: 19 THE COURT: OKAY. YOUR HONOR -SO YOU'RE SAYING, MR. VAN NEST, THAT YOU 20 DON'T THINK THAT THERE WILL BE ANY FURTHER SETTLEMENTS ABSENT 21 ANOTHER MEDIATION SESSION? 22 MR. VAN NEST: 23 THE COURT: 24 25 THAT'S RIGHT. SO GETTING AN INTERIM SETTLEMENT STATUS REPORT -MR. VAN NEST: NOT MEANINGFUL. UNITED STATES COURT REPORTERS 14 15 1 THE COURT: IF YOU WERE GOING TO RESOLVE THE CASE, I 2 WOULDN'T HAVE TO ISSUE THE ORDER. 3 GOING TO HAPPEN? 4 5 MS. DERMODY: BUT YOU KNOW THAT'S NOT YOU KNOW, YOUR HONOR, WE'LL LET YOU KNOW IF SOMETHING ELSE -- 6 MR. VAN NEST: 7 THE COURT: 8 MR. VAN NEST: 9 MR. SAVERI: ALL RIGHT. IF YOU SET THE DEADLINE, WE'LL COMPLETE IT BY THEN. 10 IT'S NOT MEANINGFUL. I WOULD HOPE, YOUR HONOR, THAT WE -- YOU 11 KNOW, WE WENT THROUGH MEDIATION SESSIONS, WE ESSENTIALLY 12 ACCOMPLISHED THE SETTLEMENTS WE DID WITH BILATERAL NEGOTIATIONS 13 BETWEEN THE PLAINTIFFS AND THE DEFENDANTS. 14 15 SO I WOULD HOPE THAT WE'D BE ABLE TO CONTINUE THAT AND NOT JUST WAIT FOR THE MEDIATION SESSION TO TRY TO NARROW THIS. 16 17 THE COURT: PLEASE. MONEY -- 18 MR. VAN NEST: 19 THE COURT: 20 21 I MEAN, SAVE YOURSELVES THE ABSOLUTELY. -- AND JUST DO IT YOURSELVES. OKAY, YEAH, PLEASE. MR. SAVERI: AND, YOUR HONOR, I GUESS THE OTHER THING 22 I WOULD SAY IS THAT FROM MY PERSPECTIVE, I THINK IT IS -- IT IS 23 USEFUL TO HAVE DECISION MAKERS TO BE PRESENT AND INVOLVED AT 24 THE MEDIATION, AND I THINK IF WE'RE GOING TO DO THIS SERIOUSLY 25 THE NEXT TIME, FROM MY PERSPECTIVE, IT WOULD BE USEFUL TO HAVE UNITED STATES COURT REPORTERS 15 16 1 A COMMITMENT FROM ALL SIDES THAT PEOPLE WITH AUTHORITY AND 2 DECISION MAKING POWER ARE GOING TO BE ACTIVE PARTICIPANTS ON 3 THE DAY OF THE MEDIATION. 4 5 6 THE COURT: HOW WERE THEY AVAILABLE LAST TIME? JUST BY PHONE, OR -MR. SAVERI: FROM WHAT I UNDERSTAND, AND THE OTHER 7 SIDE CAN SPEAK TO THIS, THERE WERE IN-HOUSE COUNSEL REPRESENTED 8 AT THE MEDIATION, BUT THAT WAS -- THAT WAS IT. 9 10 THE COURT: BUT THEY MUST HAVE HAD SETTLEMENT AUTHORITY UP TO A CERTAIN NUMBER. 11 MR. SAVERI: 12 ANYTHING ABOUT THAT. 13 I DON'T KNOW ANYTHING -- I DON'T KNOW MR. VAN NEST: WE HAD PEOPLE THERE, YOUR HONOR, WITH 14 SETTLEMENT AUTHORITY, AND WE WILL AGAIN, AND I UNDERSTAND 15 THAT'S THE BASELINE, OF COURSE. 16 BUT AS MR. SAVERI SAYS -- AND I UNDERSTAND WHAT HE SAYS IS 17 TRUE -- SOME OF THE NEGOTIATIONS OCCURRED JUST BETWEEN THE 18 LAWYERS AND THAT'S WHAT ULTIMATELY GOT IT DONE -- 19 THE COURT: UM-HUM. 20 MR. VAN NEST: 21 THE COURT: 22 MR. VAN NEST: 23 THE COURT: -- FOR THE ONES THAT SETTLED. UM-HUM. SO UNDERSTOOD. OKAY. ALL RIGHT. NOW, LET ME ASK, FOR 24 ANTITRUST IMPACT, DO WE NEED TO CONSIDER NOW THE ALLEGATIONS 25 THAT YOU MADE AGAINST LUCASFILM, PIXAR, AND ADOBE -- AND UNITED STATES COURT REPORTERS 16 17 1 INTUIT? DO WE STILL NEED TO -- I KNOW BOTH SIDES BELIEVE THAT 2 THERE'S NO IMPACT FROM THE THREE DEFENDANTS SETTLING, BUT TELL 3 ME WHAT IS THERE, IF ANY, IMPACT ON WHETHER WE STILL LOOK AT 4 THE DEPOSITION TESTIMONY AND THE EVIDENCE OF THOSE THREE 5 COMPANIES AS PART OF THE ANALYSIS IN THIS MOTION. 6 MR. VAN NEST: 7 THE COURT: 8 MR. VAN NEST: 9 I THINK, YOUR HONOR -- WHAT DO WE DO WITH THAT? I THINK THEY ESSENTIALLY DROP OUT. BUT THEY'RE A SMALL PART OF THE GROUP. I MEAN, THE THREE 10 TOGETHER EMPLOY LESS THAN 8 PERCENT OF THE EMPLOYEES IN THE 11 PROPOSED CLASS. 12 SO I THINK THE REAL FOCUS NOW IS ON THE REMAINING 13 DEFENDANTS AND THE -- AND WHATEVER AGREEMENTS THEY'RE ABLE TO 14 PROVE AS BETWEEN AND AMONG THEM. 15 BUT EITHER WAY, I THINK BOTH OF US SAID IN THE STATUS 16 CONFERENCE STATEMENTS, THE SETTLEMENTS DON'T CHANGE ANYTHING, 17 IN PART BECAUSE THE THREE SETTLING DEFENDANTS WERE A VERY SMALL 18 PART OF THIS TO BEGIN WITH. 19 CLASS MEMBERS ARE EMPLOYED BY ALL THREE COMBINED. 20 AS I SAID, LESS THAN 8 PERCENT OF SO THE LARGEST PART OF THE CASE IS STILL BEFORE YOUR HONOR 21 AND THE CONDUCT THAT I THINK YOU'LL BE FOCUSSING ON IS THE 22 CONDUCT OF THE FOUR REMAINING DEFENDANTS, NOT THOSE THAT HAVE 23 SETTLED OUT. 24 25 THE COURT: BUT WHY WOULDN'T THE COMMENTS OF MR. CATMULL AND MR. LUCAS STILL BE RELEVANT TO -- UNITED STATES COURT REPORTERS 17 18 1 MR. VAN NEST: 2 THE COURT: 3 THEY MIGHT HAVE SOME -- -- THE ANTITRUST CONSPIRACY, HOW THE AGREEMENTS WERE ENFORCED, HOW THEY WERE IMPLEMENTED? 4 MR. VAN NEST: 5 RELEVANCE, YOUR HONOR. 6 THEY MIGHT HAVE SOME LIMITED BUT ESSENTIALLY YOU'RE LOOKING NOW -- BECAUSE THE NATURE OF 7 THE AGREEMENTS THAT THEY'VE ALLEGED ARE BILATERAL BETWEEN AND 8 AMONG INDIVIDUAL PAIRS OF DEFENDANTS, I THINK THAT EVIDENCE IS 9 GOING TO BE LARGELY RELEVANT BECAUSE THE FOCUS WILL BE ON WHAT, 10 IF ANY, IMPACT WAS THERE FROM THE BILATERAL AGREEMENTS THAT ARE 11 BEING LITIGATED NOW AS BETWEEN THE OTHER FOUR REMAINING 12 DEFENDANTS. 13 14 SO, AGAIN, I DON'T WANT TO SAY ABSOLUTELY NO RELEVANCE, BUT VERY LIMITED. 15 THE COURT: 16 MR. SAVERI: 17 THE COURT: OKAY. YOUR HONOR -LET ME HEAR FROM THE PLAINTIFFS. YOU 18 AGREE THAT YOU'RE NOT ADVOCATING AN OVERARCHING CONSPIRACY 19 ANYMORE, IT'S JUST BILATERAL AGREEMENTS AND -- 20 MR. SAVERI: NO, YOUR HONOR. I DON'T THINK THAT THE 21 FACT THAT WE'VE -- THAT WE'VE -- NOTHING HAS REALLY CHANGED IN 22 TERMS OF OUR THEORY OF THE CASE. 23 IS GOING TO HANDLE THE SUBSTANCE OF THE ARGUMENT, BUT LET ME 24 JUST SAY THIS. 25 WE ALLEGE -- AND MR. GLACKIN I THINK THAT THE -- AS YOU SAID, THE EVIDENCE OF THE UNITED STATES COURT REPORTERS 18 19 1 SETTLING DEFENDANTS WITH RESPECT TO THE AGREEMENTS, THE NATURE 2 AND THE SCOPE OF THE AGREEMENTS, IS STILL GOING TO BE RELEVANT 3 IN THIS CASE. 4 AND TO THE EXTENT THAT THERE IS OTHER EVIDENCE THAT HAS TO 5 DO WITH THE BUSINESS PRACTICES OF THOSE COMPANIES THAT WE RELY 6 ON TO SHOW A CLASS-WIDE IMPACT, THE FACT THAT THOSE DEFENDANTS 7 HAVE SETTLED DOESN'T CHANGE THAT FACT. 8 9 10 REMEMBER THAT THIS REMAINS A, AN ANTITRUST CLAIM AND ALL THE PARTICIPANTS IN THE CONSPIRACY ARE, AS A MATTER OF LAW, JOINTLY AND SEVERALLY LIABLE. 11 AND SO TO THE EXTENT THAT WE PROVE AN UNDERSTANDING, A 12 COMMON COURSE OF CONDUCT THAT INVOLVES ALL OF THESE COMPANIES, 13 I MEAN, THAT EVIDENCE IS RELEVANT. 14 THE COURT: WHAT IS THE BREAKDOWN OF THE, WHAT IS IT, 15 60,000 THAT YOU'RE ALLEGING ARE IN YOUR TECHNICAL EMPLOYEE 16 CLASS? 17 INCLUDING THE ONES WHO ARE NOW OUT OF THE CASE? 18 WHAT'S THE BREAKDOWN AMONGST THE VARIOUS DEFENDANTS, MR. GLACKIN: WOULD YOU LIKE TO KNOW THE BREAKDOWN ON 19 NUMBER OF CLASS MEMBERS OR -- WELL, I CAN TELL YOU WHERE THAT 20 INFORMATION IS IN THE RECORD ACTUALLY IF THAT WOULD BE HELPFUL. 21 THE COURT: OKAY. 22 MR. GLACKIN: THAT'S FINE. IF YOU GO TO THE OCTOBER 12, 2012 23 REPORT OF DR. LEAMER AND YOU GO TO PAGE 23, WHICH IS BETWEEN 24 PARAGRAPHS 54 AND 55, THERE ARE TWO TABLES THERE THAT -- ONE OF 25 THEM IS FOR THE ALL SALARIED CLASS AND ONE OF THEM IS FOR THE UNITED STATES COURT REPORTERS 19 20 1 TECHNICAL CLASS, WHICH IS THE SAME CLASS THAT WE'RE NOW SEEKING 2 TO CERTIFY. 3 4 THE COURT: WHICH REPORT? I HAVE THE MAY 10TH, 2013 -- 5 MR. GLACKIN: 6 THE COURT: 7 OH, I DON'T HAVE THAT. 8 MR. GLACKIN: 9 10 -- AND JULY 12TH. BUT IF YOU WERE TO -- I'D BE I SHOWED THIS TO MR. VAN NEST. THE COURT: 12 MR. GLACKIN: CAN YOU JUST GIVE ME THE BALLPARKS? SURE. WELL, BY NUMBER OF EMPLOYEES, I CAN TELL YOU THAT ADOBE IS 3,601; APPLE IS 6,835. 14 THE COURT: 15 MR. GLACKIN: 16 THE COURT: 17 MR. GLACKIN: 18 THE COURT: 19 MR. GLACKIN: 20 THE COURT: 21 MR. GLACKIN: 22 THE COURT: 23 MR. GLACKIN: 24 THE COURT: 25 RIGHT. HAPPY TO HAND YOU MY PAGE IF IT'S HELPFUL. 11 13 THIS IS LAST YEAR. 6,000 WHAT? 835. OKAY. THANK YOU. GOOGLE IS 7,854. OKAY. INTEL IS 36,643. OKAY. INTUIT IS 3,236. OKAY. LUCAS IS 522; PIXAR IS 859. ALL RIGHT. WHAT ABOUT THE -- HOW MANY JOBS -- WELL, I GUESS THAT'S IN THE CHART THAT YOU PROVIDED, UNITED STATES COURT REPORTERS 20 21 1 THE VARIOUS JOB TITLES FOR EACH OF THOSE. 2 MR. VAN NEST: 3 MR. GLACKIN: 4 MR. VAN NEST: 5 THE COURT: 6 -- IS THE TOTAL. MR. HARIHARAN -- DID I PRONOUNCE THAT CORRECTLY? MR. GLACKIN: 8 THE COURT: 10 24 -- NOW, LET ME ASK, WITH REGARD TO 7 9 2400, YOUR HONOR -- CORRECT. OKAY. HE DID NOT WORK FOR A DEFENDANT WHO IS LEFT IN THIS CASE, SO WHY SHOULD HE STILL CONTINUE TO SERVE AS A CLASS REPRESENTATIVE? 11 MR. GLACKIN: WELL, AS MR. SAVERI SAID, YOUR HONOR, 12 WE'RE ALLEGING A SINGLE VIOLATION OF THE SHERMAN ACT, A SINGLE 13 CONSPIRACY, COMBINATION, AGREEMENT, UNDERSTANDING IN RESTRAINT 14 OF TRADE. 15 AND EVEN -- THE EMPLOYEES WHO WERE AT THE -- THE PEOPLE WHO 16 WORKED FOR THE SETTLED COMPANIES DURING THE CLASS PERIOD STILL 17 HAVE ACTIVE CLAIMS AGAINST THE OTHER MEMBERS OF THE CONSPIRACY 18 BECAUSE, AS MR. SAVERI SAID, UNDER COPIOUS PRECEDENT, INCLUDING 19 TEXAS VERSUS RADCLIFF, WHICH IS THE SIGNATURE UNITED STATES 20 SUPREME COURT CASE ON JOINT AND SEVERAL LIABILITY, AND UNDER 21 THE SHERMAN ACT, ALL OF THE MEMBERS OF THE COMBINATION 22 CONSPIRACY UNDERSTANDING ARE LIABLE FOR ONE ANOTHER'S CONDUCT, 23 OR WRONGDOING, I SHOULD SAY. 24 25 SO MR. HARIHARAN STILL HAS AN ACTIVE CLAIM AGAINST THE OTHER FOUR DEFENDANTS, JUST AS ALL THE OTHER NAMED CLASS UNITED STATES COURT REPORTERS 21 22 1 REPRESENTATIVES HAVE ACTIVE CLAIMS AGAINST THOSE FOUR REMAINING 2 DEFENDANTS. 3 THE COURT: SO YOU'RE NOT EVEN LIMITING THAT TO ANY 4 OF THE DEFENDANTS WHO HAD A SPECIFIC BILATERAL AGREEMENT WITH 5 HIS EMPLOYER, LUCASFILM? 6 7 8 9 10 11 MR. GLACKIN: CORRECT, BECAUSE WE'RE ALLEGING A SINGLE, A SINGLE CONSPIRACY AND RESTRAINT OF TRADE. AND THE CLASS IS -- THE SETTLEMENT CLASS IS IDENTICAL TO THE PROPOSED TECHNICAL CLASS. IT INCLUDES MEMBERS OF ALL OF THESE COMPANIES. SO, FOR EXAMPLE, YOU KNOW, INTEL EMPLOYEES ARE MEMBERS OF 12 THE SETTLEMENT -- OF THE CLASS THAT WILL BE PROPOSED FOR THE 13 SETTLEMENT, AND THERE ARE GOING TO BE CLASS MEMBERS WHO RELEASE 14 THEIR CLAIMS AGAINST INTUIT, PIXAR, AND LUCASFILM. 15 SO WHEN WE FILE THE PAPERS, THERE WON'T BE ANY DIFFERENCE 16 BETWEEN THE CLASSES, AND THAT I THINK WE PUT FORWARD IN THE 17 UPDATE YOU REQUESTED. 18 THE COURT: SO LET ME HEAR FROM MR. VAN NEST. WHAT'S 19 YOUR POSITION ON WHETHER MR. HARIHARAN CAN CONTINUE TO SERVE AS 20 A CLASS REP? 21 22 MR. VAN NEST: I THINK YOUR HONOR IS RIGHT. HE DOESN'T REALLY HAVE A ROLE AT THIS POINT. 23 IT'S NOTABLE THAT REALLY NONE OF THE CLASS REPS ARE FROM 24 JOB TITLES THAT MAKE UP THE VAST MAJORITY OF JOB TITLES THAT 25 ARE NOW BEING PROPOSED. UNITED STATES COURT REPORTERS 22 23 1 THESE 2400 JOB TITLES, TWO-THIRDS OF THE CLASS WORK AT 2 INTEL. OF THOSE, ROUGHLY HALF WORK IN SEMICONDUCTOR 3 MANUFACTURING, WHICH IS UNIQUE TO THEM. 4 THERE ARE JOB TITLES ALL OVER THE LOT THAT HAVE NOTHING TO 5 DO WITH THE JOB TITLES OF THE CLASS REPS, WHO ARE ESSENTIALLY, 6 MOST OF THEM, SOFTWARE ENGINEERS. 7 TYPICAL REPRESENTATIVES TO BEGIN WITH. 8 9 10 SO THEY DON'T REALLY HAVE HE'S IN A UNIQUE SITUATION SINCE HE DOESN'T WORK FOR ANYBODY THAT'S GOING TO BE IN THE CASE. AND, OF COURSE, LUCASFILM AND PIXAR ARE KIND OF IN A 11 SEPARATE INDUSTRY, TOO. 12 FILM INDUSTRY, WHICH NOBODY ELSE PARTICIPATES IN, SO THEY ARE 13 UNIQUE. 14 15 16 HE IS UNIQUE. THEY'RE IN THIS NORTHERN CALIFORNIA THEY'RE NO LONGER IN THE CASE. THEY HAVE FOUR OTHER CLASS REPS. FRANKLY, I DON'T THINK ANY OF THEM ARE PARTICULARLY TYPICAL 17 OF SOMETHING WHERE YOU'RE TRYING TO CERTIFY 2400 JOB TITLES, 18 BUT CERTAINLY HE'S PROBABLY AT THE BOTTOM OF THE LIST AND 19 THERE'S NO LONGER ANY REASON FOR HIM TO SERVE. 20 21 THE COURT: DID ANY OF THE NAMED PLAINTIFFS WORK FOR APPLE OR GOOGLE? 22 MR. GLACKIN: 23 THE COURT: 24 MR. GLACKIN: 25 THE COURT: I BELIEVE THE ANSWER IS NO, YOUR HONOR. OKAY. IF I -- SORRY. SO WHAT'S THE THEORY OF, OF THE NAMED UNITED STATES COURT REPORTERS 23 24 1 2 PLAINTIFFS REPRESENTING EMPLOYEES AT THOSE TWO COMPANIES? MR. GLACKIN: WELL, THERE'S NO -- I MEAN, SAYING THAT 3 IT WAS NECESSARY TO HAVE AN EMPLOYEE FROM EACH COMPANY IN 4 THE -- AS A CLASS REPRESENTATIVE WOULD BE AKIN TO SAYING THAT 5 YOU COULD NOT CERTIFY A CLASS IN A PRICE FIXING CONSPIRACY CASE 6 UNLESS YOU HAD SOMEBODY WHO HAD BOUGHT FROM EVERY DEFENDANT. 7 AND IF YOU TOOK MR. VAN NEST'S ARGUMENT AND TRANSLATED IT 8 INTO THAT CONTEXT, WITH WHICH WE'RE ALL VERY FAMILIAR, THE 9 ARGUMENT WOULD BE THAT IF YOU BOUGHT FROM A SETTLED DEFENDANT, 10 YOU ARE NO LONGER AN APPROPRIATE CLASS REPRESENTATIVE IN A 11 GARDEN VARIETY PRICE FIXING CONSPIRACY CASE. 12 AND I CAN TELL YOU THAT HAVING -- I MEAN, I'M NOT -- I'LL 13 SIMPLY SAY I AM NOT AWARE OF THAT EVER HAPPENING. 14 AWARE OF ANYONE EVER MAKING THAT CONTENTION. 15 ANY COURT EVER COMING TO THAT CONCLUSION. 16 I'M NOT I'M NOT AWARE OF BECAUSE EVEN IF YOU -- I MEAN, WE HAD THIS COME UP SIMPLY 17 12 MONTHS AGO. I MEAN, THERE WERE -- WHEN WE TRIED THE LCDS 18 CASE, WE HAD A NUMBER OF CLASS REPRESENTATIVES. 19 AGAINST TOSHIBA. 20 MAJORITY OF OUR CLASS REPRESENTATIVES DID NOT BUY FROM TOSHIBA 21 BECAUSE TOSHIBA WAS A VERY SMALL MANUFACTURER IN THAT MARKET. 22 SO IT'S TOTALLY NORMAL TO HAVE -- TO NOT HAVE COMPLETE EVERY OTHER DEFENDANT SETTLED. THE TRIAL WAS BUT THE VAST 23 COVERAGE OF EVERY MEMBER OF THE CONSPIRACY IN TERMS OF 24 TRANSACTIONS, AND IT'S TOTALLY NORMAL FOR THOSE WHO BOUGHT FROM 25 SETTLED DEFENDANTS TO STAY IN THE CASE BECAUSE MR. HARIHARAN, UNITED STATES COURT REPORTERS 24 25 1 HE'S STILL JUST IN THE SAME POSITION AS EVERY OTHER CLASS 2 MEMBER. 3 WHO HAVE NOT SETTLED. HE STILL HAS A CLAIM AGAINST THE OTHER FOUR MEMBERS 4 MR. VAN NEST: YOUR HONOR, THERE'S REALLY A MORE 5 FUNDAMENTAL PROBLEM THAN THIS, AND THAT IS THERE IS NO CASE 6 THAT HAS CERTIFIED A CLASS THIS BROAD AND THIS DIVERSE IN A 7 WAGE SUPPRESSION CONTEXT. 8 9 WE HAVE, AMONG THE EVIDENCE HERE -- AND I HAVE AN APPENDIX I CAN HAND UP -- 2400 JOB TITLES, 60,000 EMPLOYEES. 10 A WIDE RANGE OF AREAS. 11 SILICON VALLEY. 12 THEY COVER DISPARATE. 13 MORE THAN HALF OF THEM WORK OUTSIDE OF IT IS AN ENORMOUS CLASS AND ENORMOUSLY IF YOU LOOK AT THE JOB TITLES THAT THEY ARE CLAIMING ARE 14 LINKED TOGETHER, IT'S EVERYTHING FROM A MASK DESIGNER TO A 15 SEMICONDUCTOR MANUFACTURER TO AN ARTIST TO A SOFTWARE ENGINEER 16 TO A CHEMICAL ENGINEER. 17 PEOPLE -- 18 THE COURT: 19 MR. VAN NEST: 20 THE COURT: IT'S ENORMOUS AND NONE OF THESE I'M SORRY TO INTERRUPT YOU. YEAH. BUT THE COMPANIES THEMSELVES IDENTIFIED 21 WHO THEY BELIEVE THEIR PEERS WERE FOR TALENT AND THEY DID 22 BASICALLY IDENTIFY EACH OTHER AS PEERS. 23 SPECIFIC EXHIBIT NUMBERS IF YOU WANT TO GO THERE. 24 25 I MEAN, I HAVE BUT THEY DID DO SOME ANALYSIS OF WHO WOULD BE COMPETING FOR THE SAME TALENT AND THEY WOULD SAY THE OTHER COMPANIES. UNITED STATES COURT REPORTERS 25 26 1 SO I HEAR WHAT YOU'RE SAYING, YOU KNOW, THE WAFER MASK 2 DESIGNER IS DIFFERENT THAN, YOU KNOW, SOMEONE DESIGNING APPS 3 SOMEWHERE ELSE. 4 BUT EFFECTIVELY -- 5 MR. VAN NEST: NOT JUST THAT, YOUR HONOR, BUT I 6 THINK, AS YOU NOTED LAST TIME AND IN YOUR ORDER, OBVIOUSLY SOME 7 CATEGORIES OF EMPLOYEES WERE MORE IMPORTANT THAN OTHERS, OR 8 MORE -- PEOPLE WERE MORE CONCERNED ABOUT SOME CATEGORIES THAN 9 OTHERS, OBVIOUSLY. 10 AND HERE WHERE ONE OF THE COMPANIES WITH TWO-THIRDS OF THE 11 CLASS IS PRIMARILY ENGAGED IN AN AREA THAT NO OTHER DEFENDANT 12 IS ENGAGED IN -- YOU KNOW, INTEL HAS -- THERE'S ONLY A CLAIM OF 13 ONE BILATERAL AGREEMENT BETWEEN INTEL AND GOOGLE, NOT A LOT OF 14 AUDITORS. 15 AND EVEN THERE, THERE ARE SO MANY -- THIS IS WHAT YOU SAID 16 LAST TIME. 17 BIG AND SO LARGE AND SO DIVERSE THAT THERE ARE PEOPLE IN IT 18 THAT WEREN'T IMPACTED AND THAT SUFFERED NO INJURY? 19 ONE OF YOUR TWO BIG CONCERNS WAS, IS THE CLASS SO AND OBVIOUSLY WHERE YOU HAVE MORE THAN HALF OF THE FOLKS 20 OUTSIDE OF SILICON VALLEY, SUBJECT TO DIFFERENT PAY STRUCTURE 21 ALTOGETHER, AND WHERE TWO-THIRDS OF THEM WORK FOR A COMPANY 22 THAT DOES SOMETHING UNIQUE, WE'VE GOT AN ENORMOUS PROBLEM. 23 NO OTHER CASE, NOT WEISBERG, NOT REED, NOT FLEISHMAN, NO 24 OTHER CASE HAS CERTIFIED A CLASS ANYWHERE NEAR THIS SIZE IN A 25 WAGE SUPPRESSION CASE BECAUSE THEY'RE LOOKING AT, HEY, WHAT, UNITED STATES COURT REPORTERS 26 27 1 WHAT POSITIONS ARE COMPARABLE? 2 HOW ARE THEY GOING TO BE ABLE TO SHOW IMPACT ACROSS THE WHOLE 3 GROUP? 4 HOW MUCH HOMOGENEITY IS THERE? IT MAKES NO LOGICAL SENSE THAT THE ABSENCE OF A CALL TO AN 5 ENGINEER IN SILICON VALLEY WOULD AFFECT A MASK DESIGNER IN 6 MASSACHUSETTS OR ARIZONA OR NEW MEXICO, AND THAT'S WHAT 7 THEY'RE -- THEY'RE HERE CLAIMING THAT THESE 2400 JOB TITLES ARE 8 ALL SOMEHOW LINKED TOGETHER. 9 INTEL, ALMOST 400 OF THEM AT GOOGLE, 350 OF THEM AT APPLE, AND 10 11 12 THERE'S 800 OF THEM ALONE AT THEY'RE SAYING THIS IS ALL LINKED TOGETHER. IN THE OTHER CASES WHERE THIS HAS COME UP, THE CLAIM HAS BEEN THAT ONE -- 13 THE COURT: BUT THERE IS -- 14 MR. VAN NEST: 15 THE COURT: -- JOB TITLE -- -- EVIDENCE FOR EACH OF THE DEFENDANTS 16 THAT THEY HAD THESE JOB FAMILIES, THAT THEY HAD THESE PAY 17 RANGES THAT ARE SIMILAR TO CRIMINAL SENTENCING, YOU HAD THE 18 LOW, THE MEDIUM, AND THE HIGH. 19 20 (LAUGHTER.) THE COURT: AND THAT IN SOME INSTANCES, IF YOU WANTED 21 TO GO OUTSIDE THAT RANGE, YOU HAD TO GET AN EXTRA LEVEL OF 22 APPROVAL; THAT THEY WERE ALWAYS AWARE, WHEN THEY WERE BRINGING 23 A LATERAL PERSON IN, WHERE EVERYONE ELSE STOOD SO THERE 24 WOULDN'T BE AN ISSUE OF DISPARITY. 25 SO I -- LET ME ASK YOU A QUESTION. AT THE LAST HEARING THE UNITED STATES COURT REPORTERS 27 28 1 DEFENDANTS' COUNSEL SAID THAT -- I'LL JUST QUOTE IT -- "AND I 2 ADMIT AT THE START, WE ARE NOT SAYING THAT NOBODY WAS 3 IMPACTED." 4 5 SO LET ME ASK -- I JUST WANT TO FOLLOW-UP. IMPACTED? WHO WAS IMPACTED? 6 MR. VAN NEST: 7 THE COURT: 8 MR. VAN NEST: 9 THE COURT: UM-HUM. -- TO KNOW THAT. WELL, HOW CAN YOU SAY THAT NO ONE WAS IMPACTED? 12 13 WELL, I DON'T THINK THERE'S ANY WAY -- BUT WHAT WE DO KNOW -- 10 11 HOW MANY WERE MR. VAN NEST: I'M NOT SAYING THAT NO ONE WAS IMPACTED. 14 THE COURT: OKAY. 15 MR. VAN NEST: BUT FOR THE PURPOSE OF -- WHAT WE 16 UNDERSTOOD TO BE YOUR HONOR'S CONCERN WAS, CAN THE PLAINTIFF 17 SHOW, IN ORDER TO ESTABLISH CLASS-WIDE INJURY -- 18 THE COURT: LET ME ASK YOU A QUESTION. I BELIEVE 19 THAT WAS MR. MITTELSTAEDT AT THE TIME. 20 NOT SAYING THAT NOBODY WAS IMPACTED," WHAT DID THAT MEAN? 21 MR. VAN NEST: WHEN HE SAYS, "WE'RE I THINK WHAT HE MEANT WAS FOR THE 22 PURPOSES OF CLASS CERT, WE'RE NOT TAKING THE POSITION THAT THEY 23 CAN'T SHOW ANY IMPACT. 24 25 THE ISSUE IS, CAN THEY SHOW IMPACT TO ALL OR NEARLY ALL OF THE MEMBERS OF THE CLASS? UNITED STATES COURT REPORTERS 28 29 1 I THINK THAT'S ALL MR. MITTELSTAEDT MEANT, AND THAT'S ALL I 2 MEAN, TOO. 3 PROPER, HOW MANY. 4 ANYTHING. 5 WE'RE NOT GOING TO DEBATE TODAY, I DON'T THINK IT'S I'M NOT SURE THEY'RE GOING TO PROVE MUCH OF THE COURT: WELL, HOW MUCH IS REQUIRED? IN ORDER TO 6 CERTIFY CLASS, THEY DON'T HAVE TO SHOW THAT 60,000 WAS ENOUGH. 7 40 IS USUALLY ENOUGH. 8 THE NUMBER THAT THEY'RE -- SEPARATE FROM WHETHER THEY'VE SHOWN 9 IMPACT OR NOT, WHAT IS THE MINIMUM LEVEL OF SHOWING IN TERMS OF 10 WHAT'S PEOPLE THAT THEY NEED TO MAKE IN ORDER TO GET CERTIFIED? 11 12 SOMETIMES 20 MIGHT BE ENOUGH. MR. VAN NEST: THEY NEED TO SHOW THAT NEARLY ALL -- IF THEY WANT TO PROCEED AS A CLASS -- 13 THE COURT: OKAY. 14 MR. VAN NEST: -- THEY NEED TO SHOW -- AND YOU 15 RECOGNIZED THIS AT PAGE 46 OF YOUR ORDER LAST TIME -- THEY NEED 16 TO SHOW THAT THE WAGE STRUCTURES WERE SO, SO RIGID THAT THEY 17 WOULD HAVE AFFECTED ALL OR NEARLY ALL MEMBERS OF THE CLASS. 18 THAT'S EXACTLY WHAT YOU SAID AND THAT'S EXACTLY RIGHT. 19 THESE CASES ALL SAY, IF WE'RE GOING TO PROCEED AS A CLASS, 20 YOU'VE GOT TO SHOW THAT CLASS-WIDE IMPACT, AND CLASS-WIDE MEANS 21 ALL OR NEARLY ALL. 22 NOT EVERYBODY. NOT 60,000, CERTAINLY. BUT IT'S -- IT'S GOT TO BE A SITUATION WHERE THEY PROVE, IN 23 ONE TRIAL, THAT VIRTUALLY ALL MEMBERS OF THE CLASS WERE 24 IMPACTED. 25 AND THEN YOU GO ON, IF THEY PREVAIL, TO TRY TO ESTABLISH UNITED STATES COURT REPORTERS 29 30 1 2 DAMAGES. SO WHAT WE'VE DONE HERE IS THEY'VE COME IN, AND YOU PUT 3 THEM TO IT LAST TIME, YOU SAID, "CAN YOU SHOW ME THAT THE 4 STRUCTURES FOR WAGES AT THE COMPANIES WERE SO RIGID THAT AN 5 IMPACT ON SOME PEOPLE WOULD HAVE PROPAGATED TO ALL OR NEARLY 6 ALL?" 7 AND THEY ABSOLUTELY HAVE FAILED TO DO THAT. DR. LEAMER 8 SAYS HE CAN'T REACH THAT CONCLUSION. HE FLAT OUT ADMITTED IN 9 DEPOSITION -- AND I HAVE THE CITATION, YOUR HONOR -- THAT "I 10 CAN'T TELL YOU THAT ADOBE'S STRUCTURE WAS SO RIGID THAT IMPACT 11 TO SOME WOULD, WOULD FLOW DOWN TO IMPACT TO OTHERS." 12 SAYS, "I DON'T BELIEVE THAT IT WOULD." 13 AND HE NOW, YOU HAVE, FROM DR. MURPHY, YOUR HONOR, THE -- 14 THE COURT: LET ME ASK YOU A QUESTION. 15 THIS PROCEEDS ALONG INDIVIDUAL CLAIMS. 16 LET'S SAY WORK? 17 MR. VAN NEST: 18 THE COURT: 19 MR. VAN NEST: HOW IS THAT GOING TO I WOULD CALL THAT A MASS ACTION. A CLASS -NO, I WOULDN'T. ACTUALLY, I THINK 20 THAT IS AN EASIER, MORE EFFICIENT WAY TO HANDLE THIS. 21 WE WILL CALL THAT A MASS ACTION, NOT A CLASS ACTION. 22 IF THERE ARE PEOPLE, AND CERTAINLY THE CLASS REPS WOULD BE 23 AMONG THEM, WHO BELIEVE THEY WERE INJURED, THEY WOULD COME IN, 24 THEY WOULD PRESENT THEIR COMPLAINT, MAYBE WE'D HAVE 200 OF 25 THEM, MAYBE WE'D HAVE 300 OF THEM, BUT WHAT WE WOULD DO IS WE UNITED STATES COURT REPORTERS 30 31 1 WOULD NEGOTIATE A REPRESENTATIVE FEW OF THOSE TO TRY THE FIRST 2 COUPLE OF CASES, OR THE FIRST CASE, AND SEE WHERE WE COME OUT 3 AND TRY TO BENCHMARK WHETHER THEY CAN ESTABLISH LIABILITY IN 4 THE FIRST PLACE, AND IF THEY CAN, WHAT ARE THE RANGES OF 5 DAMAGES. 6 NOW, REMEMBER, WE'RE TALKING -- 7 THE COURT: SO YOU'RE GOING TO HAVE BELLWETHER TRIALS 8 WHICH ARE THEN GOING TO EXTRAPOLATE THE CLASS AND SETTLE ON A 9 CLASS SIZE. 10 11 THAT'S WHAT'S GOING TO HAPPEN? MR. VAN NEST: HAPPENS ALL THE TIME. AND IN THIS CASE, I'D SAY, YOUR HONOR, IT'S ABSOLUTELY 12 APPROPRIATE. 13 WHY? 14 AGREEMENTS. 15 THERE'S ONLY EVIDENCE SO FAR OF THESE BILATERAL AGREEMENTS 16 BETWEEN COMPANIES. 17 18 19 BECAUSE WHAT THEY'RE ALLEGING IS A BUNCH OF BILATERAL THEY CAN TALK ABOUT OVERARCHING CONSPIRACY, BUT THE COURT: SO YOU'RE SAYING 200 BELLWETHER TRIALS AND FROM THERE WE'LL EXTRAPOLATE TO 60,000? MR. VAN NEST: NO, NO, NO. I'M SAYING IF WE HAD 200 20 PEOPLE MAKING CLAIMS -- I DON'T KNOW HOW MANY PEOPLE ACTUALLY 21 FEEL THEY HAVE A CLAIM. 22 PLAINTIFFS, WE WOULD CONDUCT A FEW, ONE, TWO, OR THREE 23 BELLWETHER TRIALS, NOT A LOT, AND THAT HAPPENS ALL THE TIME. 24 25 I'M SAYING IF WE HAVE 200 OR 300 AND HERE IT'S APPROPRIATE, YOUR HONOR, BECAUSE THEY FAILED TO SHOW, AFTER YOU GAVE THEM A CLEAR ROADMAP, THAT THE SALARY UNITED STATES COURT REPORTERS 31 32 1 2 STRUCTURES ARE SO RIGID -THE COURT: SO LET ME ASK YOU, AFTER THE THREE 3 BELLWETHER TRIALS, THEN WHAT'S GOING TO HAPPEN? 4 TO ASSUME, OKAY, THIS 1,000, 2,000 GROUP OF CLASS MEMBERS HAVE 5 CLAIMS THAT ARE SOMEWHAT SIMILAR TO BELLWETHER TRIAL NUMBER TWO 6 AND SO, THEREFORE, THEIR DAMAGES SHOULD ROUGHLY APPROXIMATE -- 7 MR. VAN NEST: 8 THE COURT: 9 10 YOU'RE GOING THAT'S RIGHT. -- WHATEVER THE FINDING WAS IN BELLWETHER TRIAL NUMBER TWO? MR. VAN NEST: THAT'S WHAT TYPICALLY TAKES PLACE. 11 THAT'S WHAT'S TAKING PLACE IN A LOT OF THESE MASS TORT CASES 12 THAT ARE BEING HANDLED AROUND THE COUNTRY. 13 AFTER A COUPLE OF TRIALS, SMART TRIAL LAWYERS, 14 SOPHISTICATED COUNSEL FIGURE OUT WHAT'S HAPPENING. 15 THE CASES AND YOU GO. 16 YOU PRICE TO ME, GIVEN THE EVIDENCE YOU HAVE, THEY ARE SWINGING FOR 17 THE FENCES WITH THIS CLASS THEY WANT, AND THEY HAVEN'T SHOWN 18 THE BASIC PREDICATE. 19 20 21 THEY NOW ADMIT THAT THE SALARY STRUCTURES ARE NOT SO RIGID THAT IMPACT ON SOME WOULD HAVE IMPACTED ALL. THE COURT: ACTUALLY, I DISAGREE WITH YOU. I THINK 22 ON THE INTERNAL EQUITY AND ON THE RIGID WAGE STRUCTURE, IT'S 23 MUCH STRONGER NOW THAN IT WAS LAST TIME AROUND. 24 25 MR. VAN NEST: WELL, IF I COULD HAND UP WHAT I THINK ARE THE KEY PIECES OF EVIDENCE, YOUR HONOR, AND ASK THE COURT UNITED STATES COURT REPORTERS 32 33 1 TO TAKE A LOOK AT JUST THE VERY FIRST TAB (HANDING) -- I HAVE 2 ONE FOR THE COURT AND ONE FOR THE CLERK. 3 MR. GLACKIN: 4 MR. VAN NEST: I HAVE ONE. THE QUESTION YOU ASKED LAST TIME, YOUR 5 HONOR, WAS CAN YOU SHOW, WITH CLASS-WIDE EVIDENCE, THAT 6 IMPACT -- THAT THE STRUCTURE IS SO RIGID THAT IMPACT TO ONE 7 WOULD AFFECT ALL? 8 TAB 1 IS FROM DR. LEAMER'S MOST RECENT DEPOSITION. 9 10 THE COURT: RIGHT. AND WE'RE GOING TO GET INTO THIS. LET ME ASK MY QUESTIONS IF YOU DON'T MIND. 11 MR. VAN NEST: 12 THE COURT: 13 MR. VAN NEST: 14 THE COURT: 15 SURE. OKAY? OF COURSE. ALL RIGHT. LET ME GO TO THE PLAINTIFFS. WHAT EXACTLY IS YOUR THEORY OF IMPACT? HOW ARE YOU 16 EXPLAINING HOW, IF A COLD CALL WAS MADE, HOW THE INCREASE IN 17 SALARY WOULD AFFECT MORE PEOPLE THAN JUST THE RECIPIENT OF THE 18 CALL? 19 20 21 22 23 MR. GLACKIN: SO I THINK THAT WE WOULD SAY THAT THERE ARE A NUMBER OF WAYS IN WHICH THIS WOULD HAVE OCCURRED. AND OF COURSE WE'LL NEVER KNOW EXACTLY WHAT WOULD HAVE HAPPENED BECAUSE OF THE AGREEMENTS. BUT THE -- OUR THEORY OF IMPACT IS THAT IT'S NOT JUST ONE 24 COLD CALL THAT WOULD HAVE MOVED THE DEFENDANTS' ENTIRE 25 COMPENSATION STRUCTURE. WE'VE NEVER ADVOCATED THAT. UNITED STATES COURT REPORTERS I AGREE 33 34 1 THAT'S CRAZY TO SAY THAT ONE SINGLE COLD CALL IS GOING TO MOVE 2 THE COMPENSATION STRUCTURE FOR THOUSANDS OF EMPLOYEES. 3 INSTEAD, IF YOU LOOK AT MR. CAMPBELL'S TESTIMONY, THE CEO 4 OF INTUIT WHO ALSO IS A FIGURE AT GOOGLE AND APPLE, HE EXPLAINS 5 THAT WHAT HE WAS CONCERNED ABOUT AND THE REASON HE WANTED IN ON 6 THIS WAS IT WAS THE WAVES OF COLD CALLS. 7 GOOGLE PICKING UP THE PHONE AND STARTING AT THE LETTER A ON, 8 YOU KNOW, THE LIST OF ENGINEERS AT INTUIT AND CALLING AND JUST 9 DIALING DOWN THE PHONE TREE AND CALLING EVERY SINGLE ONE OF 10 11 IT WAS SOMEBODY AT THEM. AND IT WAS THE DISRUPTION THAT WAS CAUSED BY THAT WAVE OF 12 CALLS, OR THOSE WAVES OF CALLS, THAT THE DEFENDANTS WERE TRYING 13 TO HEAD OFF THROUGH THESE ANTI-SOLICITATION AGREEMENTS. 14 NOW, HAD THOSE -- HAD THE AGREEMENTS NOT BEEN IN PLACE, WE 15 THINK THAT THE WORLD WOULD HAVE BEEN DIFFERENT IN A NUMBER OF 16 DIFFERENT WAYS. 17 WE THINK THAT WHEN THE WAVES OF COLD CALLS HAPPENED, THAT 18 THAT WOULD HAVE PUT UPWARD PRESSURE ON THE ENTIRE SALARY 19 STRUCTURE BECAUSE MANAGERS WOULD LET THE -- YOU KNOW, THE LOWER 20 LEVEL MANAGERS WOULD LET THE HIGHER LEVEL MANAGERS KNOW THAT 21 THE COMPANY'S EMPLOYEES WERE VULNERABLE, AND THAT WOULD HAVE 22 LED TO ADJUSTMENTS AT THE TOP OF THE SALARY STRUCTURE TO 23 IMPROVE THE SALARIES, OR THE COMPENSATION OF ALL EMPLOYEES. 24 BUT THE CEOS THEMSELVES, I MEAN, WHO ENTERED INTO THESE 25 AGREEMENTS IN THE FIRST PLACE WOULD HAVE BEEN AWARE, WOULD HAVE UNITED STATES COURT REPORTERS 34 35 1 KNOWN THAT THEY FACED INCREASED COMPETITION FROM OTHER, FROM 2 THEIR OTHER PEER COMPANIES IN SILICON VALLEY AND WOULD HAVE -- 3 AND ELSEWHERE IN NORTHERN CALIFORNIA -- AND WOULD HAVE ACTED 4 PREEMPTIVELY. THEY AND THEIR MANAGERS WOULD HAVE ACTED 5 PREEMPTIVELY. THEY WOULD HAVE RESPONDED TO THE THREAT OF 6 COMPETITION AS WELL BY IMPROVING THE SALARIES OF THEIR 7 EMPLOYEES, OR THE COMPENSATION OF THEIR EMPLOYEES. 8 9 SO I THINK THAT, YOU KNOW, THE INCREASE -- IF YOU LOOK AT THE -- IF YOU LOOK AT THE COMPANIES THEMSELVES -- THE REASON 10 I'M BEING A LITTLE GENERAL IS BECAUSE EACH OF THEM MANAGED 11 THEIR COMPENSATION IN SLIGHTLY DIFFERENT WAYS. 12 DIDN'T -- THEY ALL USED THEIR OWN PROPRIETARY, YOU KNOW, 13 PAYMENT TOOL, WHICH IS -- OR WHATEVER SORT OF COMPUTER PROGRAM 14 THEIR MANAGERS WERE SUPPOSED TO LOG INTO. 15 THE COURT: I MEAN, THEY I GUESS I DON'T UNDERSTAND HOW THIS 16 UPWARD PRESSURE ON THE ENTIRE SALARY STRUCTURE, HOW WAS THAT 17 SUPPOSED TO HAPPEN? 18 MR. GLACKIN: WELL, YOU -- THE EMPLOYEES -- YOU MEAN 19 FROM THE INCOMING COLD CALLS? 20 THE COURT: 21 MR. GLACKIN: 22 THE COURT: 23 YEAH. SO THE -- WHAT'S THE CHAIN OF EVENTS THAT CAUSES THAT TO HAPPEN? 24 MR. GLACKIN: 25 THE COURT: YEAH. BECAUSE I DON'T SEE IT. UNITED STATES COURT REPORTERS 35 36 1 MR. GLACKIN: SO THE CHAIN OF EVENTS IS THAT SOMEBODY 2 AT -- YOU KNOW, ONE OF THE 800 RECRUITERS AT GOOGLE, FOR 3 EXAMPLE, PICKS UP THE PHONE, OR MAYBE SEVERAL OF THEM PICK UP 4 THEIR PHONES AND THEY NEED TO HIRE A SOFTWARE ENGINEER, AND SO 5 THEY GET, YOU KNOW, WHATEVER PHONE LIST THEY HAVE FOR INTUIT 6 AND THEY START AT LETTER A AND THEY GO DOWN TO LETTER Z AND 7 THEY CALL ALL THOSE PEOPLE, AND MAYBE THEY GET SOME LEADS, OR 8 MAYBE THEY DON'T. 9 BUT EITHER WAY, RIGHT THERE, THE PEOPLE WHO RECEIVED THOSE 10 CALLS HAVE GAINED SOME INFORMATION ABOUT HOW THEY ARE PERHAPS 11 MORE VALUABLE THAN WHAT THEY'RE BEING PAID AT INTUIT. 12 IF THE -- IF IT GOES TO ANOTHER LEVEL WHERE THEY RECEIVE 13 JOB INTERVIEWS OR OFFERS OR IF THEY GET A NEW JOB AND LEAVE, 14 THERE'S AN ADDITIONAL AND GREATER LEVEL OF DISRUPTION THAT 15 HAPPENS TO INTUIT. 16 THE COURT: WELL, I GUESS I -- I GUESS I DON'T SEE 17 HOW THAT'S HAPPENING. 18 RECIPIENT OF THE CALL NOW HAVING A BETTER SENSE OF HOW MUCH HE 19 OR SHE IS WORTH, BUT I GUESS I'M NOT SEEING THE RELATIONSHIP 20 BETWEEN THAT ONE PERSON'S BETTER REALIZATION OF THEIR MARKET 21 VALUE AND HOW THAT TRANSLATES TO THE ENTIRE SALARY STRUCTURE. 22 MR. GLACKIN: I SEE WHAT YOU'RE SAYING ABOUT THE WELL, THE POINT -- SO LET'S ASSUME THAT 23 SOMEBODY AT GOOGLE HAS PICKED UP THE PHONE AND CALLED 100 24 SOFTWARE ENGINEERS AT INTUIT, SO ALL OF A SUDDEN YOU'VE GOT 100 25 SOFTWARE ENGINEERS WHO HAVE GAINED SOME INFORMATION, AND THEN UNITED STATES COURT REPORTERS 36 37 1 YOU MAYBE ULTIMATELY GET A SMALLER NUMBER WHO HAVE RECEIVED JOB 2 OFFERS OR HAVE BEEN INVITED IN FOR INTERVIEWS WHO ARE GOING TO 3 GET MORE INFORMATION ABOUT THEIR WORTH. 4 THOSE SOFTWARE ENGINEERS -- NOW, ONCE THEY LEARN THAT 5 THEY'RE MORE VALUABLE, THEY'RE NOT JUST GOING TO SIT THERE AND 6 SAY, "OKAY, I UNDERSTAND THAT THE GOOGLE PEOPLE WOULD REALLY 7 LOVE TO HIRE ME, BUT I'M SO HAPPY AT INTUIT, I DON'T CARE WHAT 8 INTUIT PAYS ME." 9 I MEAN, THEY'RE GOING TO AGGREGATE. THEY'RE GOING TO TALK 10 TO THEIR MANAGER. 11 WANT MORE MONEY OR THAT THEY FEEL THEY ARE AT RISK OF BEING 12 HIRED AWAY AND THAT'S GOING TO PUT PRESSURE ON THE COMPANY. 13 THEY'RE GOING TO MAKE IT KNOWN THAT THEY AND THE DOCUMENTS SHOW THAT THE COMPANIES ARE AWARE OF THIS 14 THREAT AND THEY TAKE IT INTO CONSIDERATION. YOU KNOW, ONE 15 DOCUMENT I WOULD POINT TO IS -- IT WAS EXHIBIT 17, I BELIEVE, 16 TO MR. HARVEY'S ORIGINAL DECLARATION FROM 2012, WHICH IS THIS 17 DONNA MORRIS E-MAIL WHICH IS ADOBE_008692 AND IN WHICH 18 MS. MORRIS IS DESCRIBING THIS EXACT PROCESS. 19 SHE SAYS, "SALARIES ARE GETTING OUT OF WHACK, OUR 20 EMPLOYEES' SALARIES ARE MOVING APART, THERE'S NOT ENOUGH 21 COMPRESSION, WE NEED TO DO AN OUT OF CYCLE ADJUSTMENT TO DEAL 22 WITH THE COMPETITION THAT WE'RE GETTING FOR OUR COMPANIES," 23 EXCUSE ME, "FOR OUR EMPLOYEES." 24 THE COURT: UM-HUM. 25 MR. GLACKIN: AND IT'S THAT KIND -- AND THIS WAS IN UNITED STATES COURT REPORTERS 37 38 1 FEBRUARY OF 2005, MERE MONTHS BEFORE ADOBE ENTERED INTO ITS 2 COMPANY-WIDE AGREEMENT WITH MR. JOBS. 3 AND SO THIS IS EXACTLY THE KIND OF THING THAT WE SAY WOULD 4 HAVE HAPPENED A LOT MORE OFTEN HAD THESE DEFENDANTS NOT ENTERED 5 INTO THESE AGREEMENTS. 6 THE COURT: WELL, I GUESS I'M STILL CONFUSED AS TO 7 IF -- LET'S SAY THE GOOGLE PERSON IS CALLING A THROUGH Z AT 8 INTUIT WITHIN A SPECIFIC JOB FAMILY. 9 THAT JOB FAMILY, SALARIES MIGHT GO UP AT INTUIT. 10 11 I CAN SEE WHY, WITHIN BUT WHAT I DON'T SEE IS WHY OTHER JOB FAMILIES AT INTUIT WOULD BE AFFECTED BY THE INCREASE. 12 MR. GLACKIN: 13 THE COURT: OH, OKAY. YEAH. I UNDERSTAND. IF THESE ARE THE DIFFERENT SILOS, 14 HOW IS THAT COMPENSATION INFORMATION SUPPOSED TO BE TRANSLATED 15 ACROSS THE DIFFERENT FAMILIES? 16 MR. GLACKIN: 17 THE COURT: 18 MR. GLACKIN: RIGHT. OR -THIS IS -- I THINK WHEN YOU GET TO THE 19 LEVEL OF JOB FAMILIES AND JOB TITLES, THIS IS WHERE INTERNAL 20 EQUITY AND THE WAY THAT THESE COMPANIES STRUCTURE THEIR 21 COMPENSATION SYSTEMS STARTS TO PLAY THE BIG ROLE, BECAUSE THE 22 EVIDENCE SHOWS THAT THESE -- AND THIS IS SUMMARIZED IN OUR, AT 23 LENGTH IN THE BRIEFS AND IN DR. HALLOCK'S REPORT, THAT THESE 24 COMPANIES CARE ABOUT MAINTAINING RELATIVE POSITIONING BETWEEN 25 THEIR JOB TITLES AND THEIR JOB FAMILIES. UNITED STATES COURT REPORTERS 38 39 1 I MEAN, IT JUST MAKES SENSE, RIGHT, THAT YOU WOULD CARE 2 ABOUT HOW SOFTWARE ENGINEER 1 IS PAID RELATIVE TO SOFTWARE 3 ENGINEER 6, OR HOW A PARTICULAR FAMILY OF ENGINEERS IS PAID 4 RELATIVE TO ANOTHER FAMILY OF ENGINEERS. 5 6 IT'S NOT, I DON'T THINK, PARTICULARLY CONTROVERSIAL AT THIS POINT ACTUALLY. 7 8 THE COURT: BUT TELL ME ABOUT THE RADFORD DATA. WHICH COMPANIES ARE INCLUDED IN THAT DATA? 9 MR. GLACKIN: IT'S -- MY UNDERSTANDING IS THAT IT IS 10 A LARGE -- I MEAN, IT'S A LARGE GROUP OF COMPANIES. 11 THAN JUST THESE FIRMS, THAT'S FOR SURE. 12 IT'S MORE AND I THINK THAT YOU CAN BE -- IF YOU'RE A SUBSCRIBER TO 13 THE RADFORD DATA AS A COMPANY, I THINK YOU CAN BE SELECTIVE 14 ABOUT THE KINDS OF COMPANIES THAT YOU WANT DATA FOR, AGGREGATE 15 DATA FOR. 16 THE COURT: ARE THE DEFENDANTS THAT ARE IN THIS CASE 17 INCLUDED IN THE RADFORD DATA? 18 MR. GLACKIN: 19 THE COURT: 20 I BELIEVE SO. HOW -- AND HOW IS THAT DATA ORGANIZED? I KNOW -- I SAW SOMEWHERE THAT IT'S JOB TITLE AND CATEGORY. 21 MR. GLACKIN: RIGHT. I -- MY UNDERSTANDING IS THAT 22 THERE ARE -- YOU KNOW, THERE ARE CERTAIN BENCHMARK JOB TITLES 23 THAT ARE -- WHERE MARKET AVERAGES ARE REPORTED BY RADFORD FOR 24 A -- 25 THE COURT: AND WHAT ARE THOSE? UNITED STATES COURT REPORTERS 39 40 1 2 3 4 MR. GLACKIN: WHAT ARE THE SPECIFIC BENCHMARK JOB TITLES? THE COURT: DO THEY INCLUDE ANY THAT WOULD BE IN YOUR ALLEGED TECHNICAL EMPLOYEE CLASS? 5 MR. GLACKIN: 6 THE COURT: 7 YES, THEY DO. MR. GLACKIN: WHAT -I HAVE TO CONFESS TO YOU, I DON'T KNOW 8 THEM OFF THE TOP OF MY HEAD. 9 THE COURT: 10 OKAY. INCLUDE JOB TITLES THAT ARE IN -- 11 MR. GLACKIN: 12 THE COURT: 13 MR. GLACKIN: 14 THE COURT: 15 16 BUT YOU THINK THAT THEY WOULD YES. -- THE TECHNICAL CLASS? CERTAINLY. AND WHAT DO YOU MEAN BY "BENCHMARK"? WHY DON'T YOU EXPLAIN THAT? MR. GLACKIN: SURE. SO, I MEAN, THE WAY THAT 17 COMPANIES, IN GENERAL, USE THE RADFORD DATA IS THAT THE RADFORD 18 DATA SAYS -- THE DATA THAT THEY GET FROM RADFORD TELLS THEM 19 THAT A PARTICULAR KIND OF EMPLOYEE IN THE MARKET IS BEING PAID 20 ON AVERAGE A PARTICULAR WAGE, OR A PARTICULAR RANGE OF WAGES, 21 AND THE COMPANY DECIDES THEN, WHERE DO WE WANT TO BE RELATIVE 22 TO THE RADFORD DATA? 23 WHICH WOULD MEAN WE'RE RIGHT AT THE MEDIAN? 24 75TH PERCENTILE? 25 BE LOWER PERHAPS? DO WE WANT TO BE IN THE 50TH PERCENTILE, DO WE WANT TO BE OR DO WE WANT TO BE HIGHER OR DO WE WANT TO UNITED STATES COURT REPORTERS 40 41 1 AND THEN THEY WOULD USE THE -- THEN THEY WOULD JUST COMPUTE 2 OUT OF THE RADFORD DATA WHAT THAT BENCHMARK WOULD BE FOR THEIR 3 INTERNAL USE AND USE THAT TO SET THE SALARY STRUCTURES. 4 5 THE COURT: GEOGRAPHY IN ADDITION TO JOB TITLE? 6 7 MR. GLACKIN: FOR SURE. 8 9 10 IS THE RADFORD DATA BROKEN DOWN BY I WOULD SUSPECT IT IS, BUT I DON'T KNOW I COULD ASK. THE COURT: DO YOU KNOW? DO ANY OF THE DEFENDANTS -- MR. VAN NEST, I'M CURIOUS ABOUT THIS, YOU KNOW, BENCHMARKING AND -- 11 MR. VAN NEST: 12 THE COURT: 13 MR. VAN NEST: YOUR HONOR -- -- THE RADFORD DATA. YOU'VE GOT YOUR FINGER ON EXACTLY THE 14 PROBLEM, AND THE PROBLEM IS THAT YOU HAVE 2400 JOB TITLES, AND 15 YOU'RE QUITE RIGHT, IT MAKES NO SENSE THAT IF SOMEONE IN 16 SANTA CLARA THAT'S A SOFTWARE ENGINEER GETS OR DOESN'T GET A 17 CALL, A MASK DESIGNER OR A SEMICONDUCTOR PERSON IN NEW MEXICO 18 WOULD BE IMPACTED. 19 MAKE ANY SENSE. THERE'S NO EVIDENCE OF THAT AND IT DOESN'T 20 RADFORD IS MADE UP OF THOUSANDS OF COMPANIES, AND THERE ARE 21 THOUSANDS OF JOB TITLES, AND WHAT THE DEFENDANTS HAVE TESTIFIED 22 IS THAT WHEN THEY LOOK AT A JOB TITLE, THEY'RE BENCHMARKING TO 23 A SPECIFIC JOB TITLE. 24 25 INTERNAL EQUITY IS A FACTOR THAT ONE MIGHT USE IN LOOKING AT SIMILAR EMPLOYEES DOING A SIMILAR THING AND PERFORMING THE UNITED STATES COURT REPORTERS 41 42 1 2 SAME WAY, SURE. THE COURT: BUT ISN'T THE BENCHMARK THE WAY YOU'RE 3 ABLE TO DETERMINE WHERE YOU STAND RELATIVE TO YOUR PEERS IN 4 TERMS OF COMPENSATION? 5 MR. VAN NEST: 6 JOB TITLE, TO TELL WHERE YOU FELL WITHIN THE RANGE. 7 THE COURT: 8 MR. VAN NEST: 9 10 IT WOULD ALLOW YOU, FOR A PARTICULAR UM-HUM. BUT, AGAIN, IT'S THOUSANDS OF COMPANIES AND THOUSANDS OF JOB TITLES. AND THEIR WHOLE THEORY -- YOU'VE GOT YOUR FINGER RIGHT ON 11 IT -- IS THAT EVERY ONE OF THESE 2400 JOB TITLES WOULD HAVE 12 AFFECTED EVERY OTHER ONE. 13 AND WHEN WE ASKED DR. LEAMER, "CAN YOU SHOW THAT THE 14 STRUCTURES ARE SO RIGID THAT IMPACT ON SOME WAS IMPACT ON ALL?" 15 HE NOT ONLY SAID, "NO, I DIDN'T SHOW THAT," BUT HE SAID, "I 16 DON'T BELIEVE IT'S TRUE." 17 TABS 1 AND 2 ARE THE QUOTES FROM HIS DEPOSITION, YOUR 18 HONOR, WHERE THIS WAS MADE ABUNDANTLY CLEAR THAT HE DID NOT -- 19 HE WAS NOT ABLE TO CORRELATE TITLE TO TITLE; HE WAS NOT ABLE TO 20 SAY THAT A CHANGE TO SOME WOULD BE A CHANGE TO ALL; AND HE WAS 21 NOT ABLE TO SAY THAT IF YOU AFFECT THE SALARIES OF SOME PEOPLE, 22 YOU THEREFORE WILL AFFECT THE SALARIES OF SOME OR ALL BECAUSE 23 THE JOB STRUCTURE IS RIGID. 24 25 AND WE KNOW -THE COURT: TELL ME, WHAT ARE THE RADFORD BENCHMARKS UNITED STATES COURT REPORTERS 42 43 1 FOR JOB TITLES THAT MIGHT BE WITHIN THIS PUTATIVE TECHNICAL 2 EMPLOYEE CLASS? IS THERE, LIKE, SOFTWARE ENGINEER? 3 MR. GLACKIN: 4 THE COURT: 5 MR. GLACKIN: YEAH. TECHNICAL ENGINEER? I MEAN, I BELIEVE, FOR EXAMPLE, THAT 6 THE TESTIMONY WAS THAT AT INTEL, YOU KNOW, THEY COULD BENCHMARK 7 80 PERCENT, 75 PERCENT OF THEIR WORK FORCE DIRECTLY OFF OF 8 RADFORD JOB TITLES. 9 SO I THINK THERE -- AS MR. VAN NEST SAYS, THERE ARE 10 THOUSANDS OF COMPANIES IN THE DATA SET, THERE'S LOTS OF JOB 11 TITLES, AND IF YOU'RE INTEL OR GOOGLE OR INTUIT, YOU CAN 12 REQUEST FROM RADFORD THE BENCHMARKS THAT YOU THINK ARE RELEVANT 13 TO YOU. 14 AND I DON'T -- I DON'T KNOW THE LIST OFF THE TOP OF MY 15 HEAD, BUT THE TESTIMONY IN GENERAL WAS THAT THESE COMPANIES 16 FOUND THIS TO BE VERY USEFUL BECAUSE THERE WAS VERY -- PRETTY 17 COMPREHENSIVE COVERAGE OF THEIR WORK FORCES. 18 AND INDEED, YOU CAN SEE WHY THERE WOULD BE AN INCENTIVE TO 19 STANDARDIZE YOUR WORK FORCE AROUND THIS PARTICULAR DATA SET. 20 IT WOULD HELP YOU BE ORGANIZED. 21 THE COURT: DID ANY OF THE FOUR REMAINING DEFENDANTS 22 BENCHMARK COMPENSATION AGAINST EACH OTHER OR AGAINST ANY OF THE 23 OTHER -- 24 25 MR. VAN NEST: THERE'S NO EVIDENCE OF THAT, YOUR HONOR. UNITED STATES COURT REPORTERS 43 44 1 MS. DERMODY: YES, THERE IS. 2 MR. GLACKIN: WELL, I DON'T -- THEY DIDN'T BENCHMARK 3 AGAINST EACH OTHER. 4 INCLUDED EACH OTHER'S DATA. 5 THINK WE'RE ARGUING THAT THEY -- THIS ISN'T -- WE'RE NOT SAYING 6 THEY CALLED EACH OTHER UP AND SET PRICE LEVELS. 7 8 MR. VAN NEST: 11 I MEAN, I -- WE'RE NOT -- I DON'T YOUR HONOR, I DON'T THINK THAT ALL FOUR REMAINING DEFENDANTS EVEN USED RADFORD. 9 10 THEY BENCHMARKED AGAINST RADFORD, WHICH THERE'S NO EVIDENCE THAT ANY DEFENDANT BENCHMARKED OFF OF IT. THAT'S NEVER BEEN THEIR THEORY. THEIR THEORY HAS BEEN THAT IF SOME EMPLOYEES WERE AFFECTED, 12 THERE WOULD THEN BE THIS RIPPLE THAT RIPPLES OUT, AND AS YOU 13 POINTED OUT, MAYBE THERE'S A RIPPLE TO THE FOLKS AROUND YOU IN 14 YOUR JOB, YOU KNOW, AREA. 15 BUT CERTAINLY NO EVIDENCE, EITHER ANECDOTALLY OR 16 ECONOMICALLY, OF ANYTHING GOING ANY PARTICULAR DISTANCE, 17 PARTICULARLY WHEN WE'RE TALKING ABOUT 60,000 PEOPLE. 18 OUR POINT. 19 20 21 THAT'S SO RADFORD IS UNIVERSAL -THE COURT: DO ANY OF THE REMAINING FOUR DEFENDANTS USE RADFORD? 22 MR. GLACKIN: 23 THE COURT: 24 MR. GLACKIN: 25 THE COURT: I BELIEVE THEY ALL DO. YEAH, THAT WAS MY IMPRESSION. YEAH. OKAY. SO I'M LOOKING AT A SLIDE FROM UNITED STATES COURT REPORTERS 44 45 1 GOOGLE ENTITLED "BENCHMARKING OVERVIEW. 2 INTENDED POSITION RELATIVE TO MARKET, NON-SALES." 3 WHAT IS GOOGLE'S AND IT TALKS ABOUT THE ELEMENT OF PAY, BASE SALARY, 4 INCENTIVE, EQUITY COMPOSITION, HOW DO WE MEASURE THE MARKET, 5 PEER COMPARATOR COMPANIES, AND IT LISTS APPLE, INTEL, INTUIT, 6 AND ADOBE, ALONG WITH OTHERS. 7 8 9 SO I READ THAT AND IT APPEARS THAT GOOGLE IS BENCHMARKING ITS PAY AGAINST GOOGLE, INTEL, INTUIT, AND ADOBE. AND THERE ARE SIMILAR DOCUMENTS FOR APPLE, SIMILAR 10 DOCUMENTS FOR ADOBE WHERE THEY ARE BENCHMARKING AGAINST EACH 11 OTHER. 12 SO -- 13 MR. VAN NEST: 14 THE COURT: 15 MR. VAN NEST: 16 THE COURT: 17 MR. VAN NEST: 18 THE COURT: 19 DO YOU WANT TO RESPOND TO THAT? THE POINT IS THAT RADFORD IS -- NO, THIS IS NOT RADFORD. THIS IS A GOOGLE DOCUMENT SAYING WE BENCHMARK -MR. VAN NEST: 21 THE COURT: 22 MR. VAN NEST: 23 THE COURT: 25 YEAH, ABSOLUTELY. YEAH. 20 24 YOUR HONOR -- THAT'S RIGHT. -- AGAINST OUR PEER COMPARATOR COMPANIES. BY -- -- WHICH INCLUDE APPLE, INTEL, INTUIT, AND ADOBE. MR. VAN NEST: BY JOB. BY JOB TITLE. UNITED STATES COURT REPORTERS BY JOB TITLE, 45 46 1 RIGHT? THAT'S OUR POINT. 2 THE COURT: IT DOESN'T SAY THAT. 3 MR. VAN NEST: 4 THE COURT: 5 MR. VAN NEST: WELL, I -- GO AHEAD. WELL, BUT THAT'S HOW ALL THESE SURVEYS 6 AND THAT'S HOW ALL THE EVIDENCE SHAKES OUT IS THERE ARE, AS I 7 SAID, THOUSANDS OF DIFFERENT JOB CATEGORIES, AND ALL THIS DATA 8 IS ORGANIZED BY JOB CATEGORY, AND SO WHILE THE COMPANIES WANT 9 TO KNOW WHERE THEY STAND WITHIN A PARTICULAR JOB TITLE, THERE'S 10 NO EVIDENCE OF ANY RIPPLE AFFECT THAT WOULD AFFECT THE WHOLE 11 JOB STRUCTURE. 12 THAT'S MY POINT. THE COURT: SO THEN SHOULD THERE JUST BE A CLASS 13 CERTIFICATION FOR EACH JOB TITLE AND SAY, OKAY, SOFTWARE 14 ENGINEER, THERE'S BENCHMARKING AMONGST THESE REMAINING 15 DEFENDANTS, AMONGST EACH OTHER, AND SO FOR THAT JOB TITLE, THAT 16 WILL BE CLASS NUMBER ONE, SOFTWARE ENGINEER. 17 MR. VAN NEST: 18 THE COURT: 19 MR. VAN NEST: 20 THE COURT: 21 MR. VAN NEST: 22 THE COURT: 23 MR. VAN NEST: THEY -- THEY -- WHY NOT? WELL, THEY HAVEN'T -- WHY NOT? LET ME SAY TWO THINGS. OKAY. THEY HAVEN'T SHOWN FOR ANY ONE TITLE 24 THAT IF SOME FOLKS IN THAT TITLE GET A BENEFIT, OR DON'T, IT'LL 25 AFFECT EVERYBODY. THEY HAVEN'T SHOWN THAT BECAUSE WHAT UNITED STATES COURT REPORTERS 46 47 1 DR. MURPHY SHOWS, AND WHAT THE RAW DATA SHOWS, IS THAT THERE'S 2 HUGE VARIATION YEAR TO YEAR WITHIN A TITLE. 3 IN OTHER WORDS, THE AVERAGES MOVE, BUT MANY PEOPLE WITHIN A 4 JOB TITLE MOVE CONTRA TO THE AVERAGE, SOME BY A LITTLE, SOME BY 5 A LOT. 6 IF YOU LOOK AT TAB 4, YOUR HONOR, WHICH I'VE PLACED BEFORE 7 YOU, DR. MURPHY PUTS THE RAW DATA FOR EVERY YEAR, FOR VARIOUS 8 TITLES, AND WHAT YOU SEE ARE CHARTS EXACTLY LIKE THE ONE THAT 9 YOU SEE IN TAB 4 WHERE YOU HAVE MOVEMENT UP BY A LITTLE FOR 10 SOME EMPLOYEES, MOVEMENT UP BY A LOT, MOVEMENT DOWN BY A 11 LITTLE, MOVEMENT DOWN BY A LOT. 12 THERE IS NO -- 13 14 THE COURT: AND I AM GOING TO GET TO ALL OF THE MURPHY AND LEAMER CHARTS AND MATERIALS. 15 MR. VAN NEST: BUT CERTAINLY -- CERTAINLY, YOUR 16 HONOR, CERTAINLY THERE IS MERIT IN SAYING YOU CAN'T CERTIFY A 17 60,000 EMPLOYEE CLASS WITH 2400 JOB TITLES WHERE THEY DON'T 18 HAVE ANY EVIDENCE OF ANY CORRELATION BETWEEN AND AMONG JOB 19 TITLES. 20 AND AS YOU POINTED OUT LAST TIME, CLEARLY THERE ARE SOME 21 CATEGORIES OF EMPLOYEES THAT FOLKS CARED ABOUT MORE THAN 22 OTHERS. 23 THE COURT: 24 MR. VAN NEST: 25 AND WHICH ONES ARE THOSE? WELL, I THINK MOST OF THE PEOPLE IN THE DOCUMENTS YOUR HONOR CITED LAST TIME ARE SOFTWARE ENGINEERS UNITED STATES COURT REPORTERS 47 48 1 AND THEY TENDED TO BE PEOPLE MORE SENIOR THAN OTHERS, AND THE 2 TOP TALENT, I THINK, WAS THE QUOTE THAT YOU GAVE AND THE 3 SOFTWARE ENGINEERS MAKE UP -- AND THERE'S A WIDE RANGE OF 4 SOFTWARE ENGINEERS, TOO, SO THEY DO A WIDE VARIETY OF THINGS. 5 BUT CERTAINLY HERE WHERE WE'VE GOT TWO-THIRDS OF OUR CLASS 6 AT INTEL WITH JOBS LIKE SEMICONDUCTOR MANUFACTURER AND CHEMICAL 7 ENGINEER, ELECTRICAL ENGINEER, MASK DESIGNER, THEY HAVE NOTHING 8 TO DO WITH ANY OF THE DOCUMENTS YOUR HONOR HAS SEEN OR CITED, 9 OR ANY OF THE EVIDENCE IN THE CASE. 10 AND IF THEY HAD GONE AND SAID -- AND TAKEN YOUR ADVICE AND 11 TRIED TO FIGURE OUT WHICH OF THESE CLASSES OR TITLES CAN I SHOW 12 SOME CORRELATION WITHIN, MAYBE WE'D HAVE SOMETHING TO TALK 13 ABOUT. 14 THEY HAVEN'T DONE EVEN THAT. THEY HAVEN'T DONE EVEN THAT 15 BECAUSE, AS TAB 4 SHOWS -- AND I'VE GOT A COUPLE OTHER TABS 16 WHEN WE GET TO THEM, YOUR HONOR -- THERE IS HUGE VARIATION 17 WITHIN EACH TITLE. 18 FOR EXAMPLE -- 19 THE COURT: SO LET ME MAKE SURE I UNDERSTAND. 20 SO THE DEFENDANTS WOULD CONCEDE THAT THERE'S BENCHMARKING 21 WITHIN A JOB TITLE, BUT YOU'RE SAYING THERE'S NO RELATIONSHIP 22 ACROSS JOB TITLES? 23 MR. VAN NEST: 24 THE COURT: 25 MR. VAN NEST: WE'RE -- YES. WE'RE SAYING THAT -- OKAY. -- WHEN PEOPLE SAY, "I WANT TO BE 65 UNITED STATES COURT REPORTERS 48 49 1 PERCENT OF SOMETHING," THEY'RE LOOKING AT A SPECIFIC JOB 2 CLASSIFICATION. 3 4 5 6 THERE IS NO BENCHMARKING -THE COURT: SO THE CLASSIFICATION CAN CERTAINLY INCLUDE A FAMILY OF JOB TITLES, THOUGH. MR. VAN NEST: I THINK THEY'RE RATHER SPECIFIC IN 7 RADFORD, BUT, YOU KNOW, I DON'T WANT TO SPEAK -- RADFORD IS NOT 8 THE ONLY SURVEY OUT THERE. 9 10 11 BUT CERTAINLY, YOUR HONOR, CERTAINLY NOBODY IS LOOKING AT RADFORD TO BENCHMARK ACROSS JOB TITLES. AND, AGAIN, EVEN WITHIN TITLES, THE POINT THAT WE'RE MAKING 12 IS THERE IS AN ENORMOUS RANGE OF DISCRETION. 13 BANDS WHICH AFFECTED SOME OF THE BASE SALARIES, SOME OF THEM 14 WERE $100,000, $100,000 WITHIN A BAND, AND THAT'S JUST SALARY, 15 NOT BONUS OR EQUITY. 16 17 18 THESE SALARY THAT'S WHY YOU SEE THINGS LIKE TAB 4 WHERE SOME EMPLOYEES -THE COURT: WE'RE GOING TO GET TO MR. MURPHY, BUT I 19 THINK WE'LL HAVE WAY MORE THAN ENOUGH STATISTICS THAN WE ALL 20 WANT BY THE END OF THE DAY. 21 MR. VAN NEST: 22 THE COURT: 23 MR. VAN NEST: 24 THE COURT: 25 I THINK -- LET ME ASK A QUESTION. SURE. AND THIS GOES TO MR. GLACKIN. WHAT EVIDENCE CAN YOU CITE TO THAT THE DEFENDANTS VIEWED UNITED STATES COURT REPORTERS 49 50 1 EACH OTHER AS PEERS FOR COMPARING COMPENSATION, FOR HAVING SOME 2 TYPE OF COMPENSATION EQUITY ACROSS COMPANIES? 3 4 5 MR. GLACKIN: SO I'M LOOKING AT SOMETHING THAT WAS JUST KINDLY HANDED TO ME. DO YOU KNOW WHAT THIS IS AN EXHIBIT TO? 6 MR. HARVEY: 7 CISNEROS DECLARATION. 8 THAT'S EXHIBIT NUMBER -- THAT'S THE MR. GLACKIN: 9 SO THIS WOULD BE AN EXHIBIT TO MS. CISNEROS'S DECLARATION, IT'S PLAINTIFF'S 621, WHICH IS A 10 FAIRLY TYPICAL DOCUMENT. 11 OUGHT TO JUST LET MR. VAN NEST AT LEAST SEE WHAT I'M TALKING 12 ABOUT. 13 MR. VAN NEST: 14 MR. GLACKIN: 15 IT'S AN E-MAIL WHERE -- I FEEL LIKE I THANK YOU. IN FACT, WE CAN STAND HERE TOGETHER. THIS IS AN E-MAIL, AN INTERNAL E-MAIL TO GOOGLE. THE TOP 16 LINE RECIPIENT IS SHONA BROWN, WHO'S THE HEAD PERSON AT GOOGLE 17 WITH RESPECT TO H.R. AND COMPENSATION, AND IT'S A -- THERE'S A 18 SPECIFIC CALL OUT IN THE SECOND PAGE -- AND THIS IS PLAINTIFF'S 19 621, GOOGLE/HIGH-TECH -- 20 EXCUSE ME, BOB. 21 MR. VAN NEST: 22 MR. GLACKIN: SURE. YEAH, 00336877. 23 AND, YOU KNOW, PARTWAY THROUGH THE E-MAIL, THEY ASK 24 THEMSELVES THE QUESTION, WELL, HOW DOES OUR OVERALL BUDGET 25 COMPARE TO WHO WE CONSIDER TO BE OUR PEERS? UNITED STATES COURT REPORTERS 50 51 1 2 3 4 5 6 7 8 9 10 AND THE -- THE PEERS THAT ARE LISTED HERE ARE ADOBE, AMAZON, APPLE, CISCO, AND INTEL. AND THEY ASK, HOW DOES WHAT WE'RE DOING IN TERMS OF MERIT INCREASES AND BONUS POOL THIS YEAR COMPARE TO THOSE COMPANIES? AND I THINK THERE ARE -THE COURT: WHAT'S THE -- WHAT'S THAT EXHIBIT NUMBER? THAT'S THE CISNEROS DECLARATION? MR. GLACKIN: IT'S PLAINTIFF'S EXHIBIT 621, AND I'LL READ THE BATES NUMBER IN CASE THAT NEEDS TO BE LOOKED AT LATER. IT'S GOOGLE/HIGH-TECH -- 00 -- 621 TO CISNEROS, 00336877. 11 THE COURT: 0033687? 12 MR. GLACKIN: 13 THE COURT: 14 MR. GLACKIN: 6877. OKAY. THAT'S THE BATES NUMBER. AND, YOU KNOW, I DEPOSED MR. SMITH, THE 15 CEO OF INTUIT, AND THERE WAS A -- YOU KNOW, THERE WAS A -- 16 THERE WAS AN AWARENESS AMONG, CERTAINLY AT INTUIT, AND I 17 BELIEVE AT THESE OTHER FIRMS, OF WHAT IT MEANT TO BE SORT OF A 18 TOP RANKED FIRM AND THEY HAD A VIEW OF THEMSELVES AND A DESIRE 19 TO BE THAT, AND THE OTHER TOP RANKED FIRMS IN SILICON VALLEY 20 ARE THE DEFENDANTS, YOU KNOW, INTEL, APPLE, GOOGLE. 21 I MEAN, THESE COMPANIES ARE THE -- THEY ARE THE STABLE 22 INSTITUTIONAL, YOU KNOW, CREME DE LA CREME, TOP OF THE CROP IN 23 TERMS OF WHO YOU'D WANT TO WORK FOR, AND THERE ARE -- THERE ARE 24 MANY EXAMPLES IN THE RECORD OF THEM LOOKING AT EACH OTHER TO 25 COMPARE THEMSELVES IN TERMS OF COMPENSATION. UNITED STATES COURT REPORTERS 51 52 1 THE COURT: BUT HOW DOES THAT -- IT APPEARS THAT EACH 2 OF THE REMAINING DEFENDANTS HAD THESE ON-LINE TOOLS TO GET 3 INFORMATION ABOUT A SPECIFIC JOB TITLE, THE SALARY BAND AND 4 WHATNOT, AND ALSO TO SORT OF DO SOME BENCHMARKING. 5 WHERE DID -- DID YOU GET INTO, IN ANY OF THE DEPOSITIONS, 6 HOW THOSE ON-LINE TOOLS WERE CREATED, WHAT INFORMATION WAS USED 7 AND INPUTTED TO CREATE THAT SYSTEM? 8 9 MR. GLACKIN: OR -- WELL, I THINK WE DID GET INTO THAT IN THE DEPOSITIONS. 10 THE COURT: OKAY. 11 MR. GLACKIN: THE -- YOU KNOW, THE ANSWER IS THAT THE 12 H.R. DEPARTMENT WOULD INPUT THINGS LIKE RADFORD DATA, OR WHAT 13 PERCENTILE THEY WANTED TO BE AT VIS-A-VIS THE RADFORD DATA. 14 AND ANYTHING ELSE IN TERMS OF LIKE -- YOU KNOW, FOR 15 EXAMPLE, WHAT THE -- YOU SEE THIS IN THE BRIEFS. I MEAN, WHAT 16 THE APPROPRIATE BONUS WAS FOR ONE OF FIVE PERFORMANCE RANKINGS, 17 SO THAT WOULD BE SOMETHING THAT WOULD BE DETERMINED AT THE TOP, 18 WHAT THE APPROPRIATE PERCENTAGE OR EQUITY GRANT WAS FOR A 19 PARTICULAR -- YOU KNOW, HOW YOU DID THAT IN TERMS OF YOUR 20 PERFORMANCE RANKING. 21 AND THEN IF YOU'RE THE -- AND ALL OF THAT ALSO WE SEE IN 22 THE DOCUMENTS, AND THIS IS EXPLAINED IN THE BRIEF, IS CURVED 23 OUT. 24 25 I MEAN, IT'S ALL SET RELATIVE. SO, FOR EXAMPLE, AT INTEL, INTEL -- YOU KNOW, THERE'S A LOT OF TALK ABOUT VARIABLE COMPENSATION, BUT INTEL WANTED TO MAKE UNITED STATES COURT REPORTERS 52 53 1 SURE THAT 60 TO 70 PERCENT OF ITS MANAGERS, OR EXCUSE ME, OF 2 ITS EMPLOYEES WERE RATED MEDIUM, AND THEN IT WANTED TO MAKE 3 SURE THAT DIFFERENT PERCENTILES AT THE TOP AND THE BOTTOM WERE 4 RATED EXCELLENT OR, YOU KNOW, NEEDS IMPROVEMENT. 5 AND IT WAS STRUCTURED OUT ON A CURVE, JUST LIKE IT WAS AT 6 ADOBE. ADOBE'S H.R. MANAGER TESTIFIED THAT THEY SET 7 COMPENSATION ON A BELL CURVE. 8 MORE STRUCTURED COMPENSATION SYSTEM. 9 THE COURT: I MEAN, IT'S HARD TO IMAGINE A WHAT ARE THE THOUSANDS OF COMPANIES THAT 10 ARE IN RADFORD? 11 NOT ALL TECH, ARE IN RADFORD? 12 WHAT OTHER TYPES OF JOBS, I'M ASSUMING IT'S MR. GLACKIN: NO. RADFORD IS A HUGE COMPANY AND IT 13 SERVES ALL KINDS OF DIFFERENT CORPORATIONS IN AMERICA, 14 INCLUDING PEOPLE -- YOU KNOW, COMPANIES THAT HAVE NOTHING TO DO 15 WITH TECH. 16 AND WHAT YOU ARE -- IF YOU'RE A CLIENT OF RADFORD, YOU GIVE 17 THEM -- YOU TELL THEM WHAT YOU'RE INTERESTED IN. 18 WANT TO KNOW ABOUT THESE KINDS OF JOBS OR THESE JOB TITLES. 19 EMPLOY THESE KINDS OF PEOPLE. 20 OF WORK." 21 22 23 24 25 YOU SAY, "I I I EMPLOY PEOPLE WHO DO THIS KIND AND THEN RADFORD GIVES YOU, YOU KNOW, A SELECTION OF 30 OR 50 OR 100 OR MAYBE MORE JOB TITLES. THE COURT: AND WHERE ARE ALL THESE COMPANIES BASED? IS IT WORLDWIDE? MR. GLACKIN: WELL, THERE'S A -- I MEAN, RADFORD UNITED STATES COURT REPORTERS 53 54 1 HAS -- I DON'T KNOW THE ANSWER TO THAT QUESTION. 2 I DON'T KNOW IF RADFORD INCLUDES INTERNATIONAL DATA. 3 BUT I KNOW THAT RADFORD DOES HAVE A SUBSET OF TECH SECTOR 4 DATA WHICH WOULD HAVE BEEN THE SUBSET THAT THIS -- THAT THESE 5 FAMILY OF COMPANIES, OR GROUP OF COMPANIES WOULD HAVE 6 SUBSCRIBED TO, OR DID SUBSCRIBE TO. 7 8 9 10 11 THE COURT: MR. VAN NEST, DO YOU KNOW IF RADFORD HAS GLOBAL SALARY INFORMATION? MR. VAN NEST: I BELIEVE IT DOES, YOUR HONOR. YOU CAN GET VARIOUS SLICES OF RADFORD. BUT A MORE IMPORTANT POINT, I THINK, YOUR HONOR, IS RADFORD 12 REALLY IS NOT RELEVANT TO THEIR THEORY OF THIS CASE. 13 A PRICE FIXING CASE. 14 BUT IT'S NOT THAT'S NOT THE POINT. THEIR THEORY IS THAT WHEN SOME COLD -- WHEN COLD CALLS WERE 15 PROHIBITED, SOME PEOPLE IN EACH COMPANY DIDN'T GET A CALL AND 16 DIDN'T GET INFORMATION AND, THEREFORE, THAT INFORMATION DIDN'T 17 BUBBLE UP AND, THEREFORE, THERE WAS SUPPRESSION THAT PROPAGATED 18 OUT TO EVERYBODY. 19 RADFORD HAS ABSOLUTELY NOTHING TO DO WITH THAT. RADFORD IS 20 MARKET DATA FROM THOUSANDS OF COMPANIES THAT ALL COMPANIES LOOK 21 AT, NOT JUST THESE, BUT HEWLETT-PACKARD AND EVERYBODY HERE IN 22 THE VALLEY AND EVERYWHERE ACROSS THE UNITED STATES. 23 NOT A PART OF THEIR THEORY OF IMPACT. 24 25 RADFORD IS AND WHAT I KEEP COMING BACK TO IS THERE IS NO CORRELATION BETWEEN JOB TITLES, EITHER WITHIN A COMPANY OR ACROSS UNITED STATES COURT REPORTERS 54 55 1 COMPANIES. 2 HE COULDN'T FIND CORRELATION BETWEEN JOB TITLES ACROSS 3 COMPANIES BECAUSE THERE IS NONE, AND THAT'S WHAT I KEEP COMING 4 BACK TO. 5 6 DR. LEAMER LOOKED AT ALL OF THIS AND HE CONCLUDED IF YOU WANT TO CERTIFY SOMETHING, IT CAN'T POSSIBLY BE A CLASS OF 2400 JOB TITLES. 7 NOW, EVEN WITHIN A FEW JOB TITLES, WE HAVE SHOWN, AND I 8 DON'T THINK THEY'RE DISPUTING IT, THAT THERE'S A WIDE VARIATION 9 IN WHAT PEOPLE ARE PAID, BECAUSE MANAGERS -- AND THERE ARE 10 12,000 OF THEM IN THESE COMPANIES THAT ARE, THAT ARE 11 DEFENDANTS -- THEY HAD ABILITY, WITHIN WIDE BANDS, TO AWARD 12 DIFFERENT SALARIES, DIFFERENT BONUSES, DIFFERENT EQUITY, AND 13 THAT'S WHY TAB 4 LOOKS LIKE IT DOES. 14 15 16 17 THE COURT: WE'RE GOING TO GET TO THAT. I HAVE SPECIFIC QUESTIONS ABOUT THOSE CHARTS. MR. VAN NEST: OKAY. BUT THAT'S -- MY POINT IS THERE'S WIDE VARIATION AND FLEXIBILITY. 18 THE COURT: I HEAR YOU. 19 MR. VAN NEST: 20 MR. GLACKIN: NOT LOCKSTEP. MAY I RESPOND TO ONE OF YOUR QUESTIONS 21 NOW THAT I HAVE BETTER INFORMATION, WHICH IS THE DATA THAT 22 THESE COMPANIES SUBSCRIBED TO FROM RADFORD WAS U.S., SO THESE 23 COMPANIES WERE GETTING THE TECH SECTOR SLICE OF U.S. WAGE DATA 24 THAT WAS BEING COLLECTED BY RADFORD. 25 MR. VAN NEST: YOU CAN CUT IT THINNER THAN THAT, TOO. UNITED STATES COURT REPORTERS 55 56 1 INSIDE SILICON VALLEY, OUTSIDE SILICON VALLEY. 2 OF INTEL'S EMPLOYEES ARE OUTSIDE SILICON VALLEY. 3 HALF OF THE PROPOSED CLASS IS OUTSIDE SILICON VALLEY. 4 5 6 OBVIOUSLY MOST MORE THAN SO, AGAIN, I THINK, YOUR HONOR, RADFORD, WE'RE SORT OF BARKING UP THE WRONG TREE. THE COURT: IT'S NOT THEIR THEORY OF IMPACT. WELL, IT'S A WAY THAT YOU CAN GET A 7 SPREADING OF EITHER THE SUPPRESSION OR -- I SHOULD SAY THE 8 ALLEGED SUPPRESSION OR ALLEGED SALARY INCREASE BASED ON THE 9 COLD CALLING IS IF IT SORT OF GETS INCORPORATED INTO RADFORD 10 AND THEN OTHER COMPANIES ARE BENCHMARKING OFF OF RADFORD, YOU 11 CAN SEE HOW THE EFFECTS COULD GET PROPAGATED AND SPREAD -- 12 MR. GLACKIN: 13 THE COURT: 14 YES. -- BY BENCHMARKING THROUGH THESE, IN ADDITION TO JUST WORD OF MOUTH AND -- 15 MR. VAN NEST: THERE ARE THOUSANDS OF -- 16 THE COURT: 17 MR. VAN NEST: 18 THE COURT: 19 MR. VAN NEST: 20 FEED THE RADFORD DATA. 21 THAT THESE COMPANIES, EITHER ONE OF THEM OR ALL FOUR OF THEM, 22 COULD AFFECT THE RADFORD DATA. -- INTERNAL EQUITY. EXCUSE ME. GO AHEAD. THERE ARE THOUSANDS OF COMPANIES THAT THEY HAVEN'T EVEN ATTEMPTED TO SHOW 23 I MEAN, THERE ARE THOUSANDS -- YOU'VE GOT HEWLETT-PACKARD. 24 YOU'VE GOT -- HOW MANY COMPANIES DO WE HAVE DOWN HERE THAT ARE 25 NOT IN THE GROUP, NOT TO MENTION PEOPLE AROUND THE UNITED STATES COURT REPORTERS 56 57 1 2 3 4 UNITED STATES, ENORMOUS TECH COMPANIES? SO RADFORD IS NOT IMPACTED BY WHAT THESE COMPANIES DO, NOR ARE THEY CLAIMING THAT. WHAT THEY'RE CLAIMING IS PEOPLE IN THE COMPANIES DIDN'T 5 GET THE INFORMATION THEY WANTED AND, THEREFORE, THEIR WAGES 6 WERE SUPPRESSED AND, THEREFORE, THAT SUPPRESSION WOULD HAVE 7 PROPAGATED OUT ACROSS JOB TITLES. 8 9 10 11 12 AND THAT'S WHERE WE'RE SAYING THEY HAVE THIS COMPLETE FAILURE OF PROOF. THEY CAN'T SHOW THAT. THEY'VE TRIED TO SHOW, THROUGH AVERAGING, THAT THERE'S SOME SIMILARITY WITHIN TITLES. THAT'S WHAT DR. LEAMER DID. BUT AVERAGING DOES EXACTLY WHAT YOU TOLD THEM NOT TO DO 13 LAST TIME. 14 VARIATION, THAT THE STRUCTURE WAS SO RIGID THAT AN IMPACT ON 15 SOME WOULD IMPACT OTHERS." 16 17 18 YOU SAID, "TELL ME HOW YOU CAN SHOW, WITH ALL THIS AND INSTEAD OF LOOKING AT THE KIND OF VARIATION THAT EXISTS, HE AVERAGED IT. AND THAT'S WHAT JUDGE ALSUP IN GPU AND WHAT JUDGE BRADY IN 19 REED -- JUDGE GRADY IN REED SAID. 20 WHETHER THERE IS IMPACT ON ALL OR NEARLY ALL, OR ON A WIDE 21 GROUP, YOU CAN'T AVERAGE, BECAUSE THE FACT THAT AN AVERAGE GOES 22 UP OR DOWN DOESN'T TELL YOU WHETHER SOME, A LOT, A FEW, OR MANY 23 WERE IMPACTED. 24 25 IF YOU'RE LOOKING TO SEE THAT'S THE WHOLE POINT. AND THEY DID EXACTLY WHAT JUDGE ALSUP, JUDGE GRADY, THE WEISFELDT CASE, THE FLEISHMAN CASE, ALL THESE CASES SAY WHEN UNITED STATES COURT REPORTERS 57 58 1 THE ISSUE IS, IS THERE A BAND OF EMPLOYEES FOR WHOM WE CAN 2 PROVE THAT ALL OR NEARLY ALL WERE IMPACTED, YOU CANNOT AVERAGE. 3 THAT IS BECAUSE -- BECAUSE THE AVERAGING TAKES AWAY THE WIDE 4 VARIATION THAT EXISTS, AND THAT'S WHY JUDGE ALSUP REFUSED TO 5 CERTIFY IN GPU. 6 7 8 9 JUDGE GRADY REFUSED TO CERTIFY -THE COURT: WELL, HE DID CERTIFY THE CLASS IN GPU. I AGREE THAT HE DID ALSO DENY CERTIFYING -MR. VAN NEST: 10 THE COURT: 11 MR. VAN NEST: RIGHT. THERE WAS A VERY -- HE DENIED IN SOME AND GRANTED IN OTHERS. WHAT HE GRANTED WAS A VERY SMALL GROUP 12 OF PEOPLE WHO DID EVERYTHING IN A SAME WAY ON A WEBSITE AND 13 BOUGHT THE SAME PRODUCT AT THE SAME TIME. 14 THAT'S VERY DIFFERENT -- IN THE REED CASE, JUDGE GRADY 15 SAID, "I'M NOT GOING TO CERTIFY A CLASS OF EVEN 19,000 NURSES 16 THAT ALL HAVE THE SAME TITLE WHO ARE PAID ON A WAGE GRID THAT 17 DOESN'T EVEN MEASURE PERFORMANCE, JUST YEARS OF SERVICE." 18 THE COURT: UM-HUM. 19 MR. VAN NEST: HE SAID, "BECAUSE YOU AVERAGED, YOU'RE 20 NOT TELLING ME WHETHER OR NOT THERE IS IMPACT ON SOME, ALL, OR 21 NEARLY ALL MEMBERS OF THE CLASS." 22 AND SO HE SAID, "NO CERT. YOU HAVE TO PROCEED BY 23 INDIVIDUAL CLAIMS OR IN A MASS ACTION," AS I MENTIONED EARLIER, 24 WHICH IS EXACTLY THE RESULT THAT SHOULD FLOW HERE, PARTICULARLY 25 WHERE YOU MADE VERY CLEAR LAST TIME THAT BASED ON THEIR UNITED STATES COURT REPORTERS 58 59 1 THEORY -- 2 THE COURT: LET ME INTERRUPT YOU ONE SECOND. 3 MR. VAN NEST: 4 THE COURT: YEAH. SO THE PLAINTIFFS HAVE SUBMITTED EVIDENCE 5 THAT ADOBE USES SALARY MATRIXES, A SALARY PLANNING TOOL, AN 6 ON-LINE SALARY RANGE WEBSITE FOR MANAGERS, AND SOMETHING CALLED 7 THE OMNITURE CURRENT COST STRUCTURE. 8 9 10 11 CAN YOU GIVE US A LITTLE INFORMATION ABOUT WHAT THAT OMNITURE CURRENT COST STRUCTURE IS? OR MAYBE THE PLAINTIFFS KNOW. WHOEVER KNOWS THE ANSWER TO THIS QUESTION. 12 MR. VAN NEST: 13 THE COURT: 14 MR. VAN NEST: 15 THE COURT: 16 MR. VAN NEST: YOUR HONOR, I CAN ANSWER GENERALLY -- OKAY. -- THAT ALL THESE COMPANIES -- UM-HUM. -- HAVE SOME KIND OF COMPENSATION 17 TOOLS THAT THEY USE. 18 LIKE INTEL, YOU'VE GOT TO HAVE SOME KIND OF TOOL TO HELP YOU 19 MANAGE COMPENSATION. 20 OBVIOUSLY IF YOU HAVE 100,000 EMPLOYEES THE POINT OF ALL OF THESE -- 21 THE COURT: 22 MR. VAN NEST: 23 THE COURT: 24 MR. VAN NEST: 25 AND WHY IS THAT, FOR INTERNAL EQUITY? NO, TO MANAGE THE COMPANY. WHY IS THAT? IF YOU'VE GOT A HUNDRED THOUSAND PEOPLE, SOMEBODY HAS TO KNOW WHAT THEY'RE BEING PAID. UNITED STATES COURT REPORTERS SOMEBODY 59 60 1 HAS TO KNOW -- 2 THE COURT: YOU DON'T NEED A TOOL FOR THAT. YOU JUST 3 NEED A SPREADSHEET WITH THE NAME AND AMOUNT OF MONEY THEY'RE 4 MAKING. 5 WHAT IS THE OMNITURE, PLEASE? 6 MR. VAN NEST: 7 THE COURT: 8 MR. VAN NEST: 9 IT'S A COMPANY THAT ADOBE ACQUIRED. OKAY. OMNITURE WAS BASICALLY AN ON-LINE ASSISTANT FOR MARKETING. IT'S NOT REALLY SOMETHING THAT DID 10 TOO MUCH WITH COMPENSATION. 11 ON-LINE MARKETING AND THEY WERE ACQUIRED BY ADOBE SEVERAL YEARS 12 AGO. 13 14 THE MAIN POINT OF OMNITURE WAS MY DAUGHTER USED TO WORK THERE, SO I KNOW. BUT GETTING BACK TO MY PRINCIPAL POINT, YOUR HONOR -THE COURT: WELL, LET ME ASK MR. GLACKIN, DO YOU HAVE 15 ANY OTHER INFORMATION ON THIS, OR IS IT NOT REALLY RELEVANT TO 16 COMPENSATION? 17 18 MR. GLACKIN: I DON'T HAVE ANY MORE INFORMATION FOR YOU, YOUR HONOR. 19 THE COURT: OKAY. 20 MR. GLACKIN: 21 THE COURT: 22 MR. GLACKIN: SORRY. ALL RIGHT. I'D BE HAPPY TO RESPOND TO SOME THINGS 23 THAT MR. VAN NEST HAS SAID ABOUT OTHER CASES. 24 TAKE YOUR QUESTIONS. 25 THE COURT: I'M HAPPY TO YOU KNOW, WE TALKED A LOT ABOUT REED AND UNITED STATES COURT REPORTERS 60 61 1 2 GPU LAST TIME, SO I'M OKAY. LET ME ASK THE NEXT QUESTION. LET ME ASK MR. GLACKIN, LAST 3 TIME AROUND YOU ALL HAD ARGUED THAT THE COURT SHOULD GRANT 4 CLASS CERT IF COMMON PROOF OF THE DEFENDANTS' ANTITRUST 5 CONSPIRACY WOULD BE THE PROMINENT ISSUE AT TRIAL. 6 MR. GLACKIN: 7 THE COURT: 8 MR. GLACKIN: 9 CORRECT. IS THAT -- IS THAT STILL YOUR POSITION? YES, YOUR HONOR. I MEAN, WE THINK -- WE -- OUR POSITION IS THAT CLASS CERTIFICATION COULD BE GRANTED 10 BASED SOLELY ON THE FACT -- ON THE OVERWHELMING ISSUE OF THE 11 DEFENDANTS' LIABILITY FOR THE COMMON ILLEGAL AGREEMENTS. 12 THE COURT: BUT HOW WOULD THAT PLAY OUT? 13 MR. GLACKIN: WELL, I MEAN, I THINK THAT THIS GETS -- 14 BACKS INTO A LITTLE BIT OF THE CONVERSATION WE WERE HAVING 15 EARLIER ABOUT TREATING THIS AS A MASS TORT ACTION -- 16 THE COURT: UM-HUM. 17 MR. GLACKIN: -- WHICH IS THAT WHETHER -- REGARDLESS 18 OF HOW THIS ACTION IS BROUGHT, THE PROOF IS GOING TO BE THE 19 SAME. 20 IF YOU -- IF MR. HARIHARAN CAME IN HERE AND TRIED TO 21 MAINTAIN AN INDIVIDUAL ACTION AGAINST THESE COMPANIES FOR THIS 22 VIOLATION, HE'D BE MAKING THE SAME ARGUMENTS AND ADVANCING THE 23 SAME PROOF ABOUT THE SEMI-RIGID JOB STRUCTURE AT THE FIRMS, 24 WHICH MEANT THAT ANY REACTION TO THIS INCREASED LEVEL OF 25 COMPETITION WAS GOING TO BE -- TO HAVE TO HAPPEN FIRM-WIDE. UNITED STATES COURT REPORTERS 61 62 1 SO THERE'S NO -- I MEAN, THIS IS WHERE WE KIND OF GET INTO 2 THE AMGEN AREA. 3 METHODOLOGY FOR MOVING IMPACT. 4 YOU KNOW, WE ARE REQUIRED TO SHOW A PLAUSIBLE THE COURT: WE'VE -- WELL, THAT'S -- THAT'S FROM 5 JUDGE ILLSTON'S CASE, RIGHT, THE METHODOLOGY? 6 JUDGE ILLSTON'S CASE, SAYS PLAUSIBLE METHODOLOGY IS ENOUGH? 7 THERE ANYTHING ELSE? 8 9 MR. GLACKIN: WHAT, OTHER THAN IS I'D HAVE TO GO BACK -- I COULD LOOK AT THE LCDS CASE AND SEE WHAT SHE'S CITING THERE. I THINK THERE 10 ARE A NUMBER OF CASES THAT HAVE USED THE PHRASEOLOGY PLAUSIBLE 11 METHODOLOGY FOR PROVING IMPACT. THE COURT: 12 13 AREN'T PEOPLE NOW SAYING SIGNIFICANT PROOF? 14 MR. VAN NEST: 15 MR. GLACKIN: 16 THE COURT: UM-HUM. NO, ABSOLUTELY NOT. I WILL JUST TELL YOU, AS MUCH RESPECT AS 17 I HAVE FOR JUDGE ILLSTON, I WOULD FEEL RELUCTANT TO RELY ON A 18 DISTRICT COURT CASE THAT'S PRE-AMGEN, PRE-COMCAST, THAT WAS 19 AGGREGATED ON OTHER GROUNDS. 20 I DON'T KNOW. WAS HER CLASS CERT ISSUE ACTUALLY EVEN 21 REVIEWED BY THE CIRCUIT COURT? 22 MR. GLACKIN: 23 WROTE THE OPPOSITION. 24 25 WELL, A 23(F) POSITION WAS FILED. I SO, YEAH, I MEAN -THE COURT: SO WAS IT -- UNITED STATES COURT REPORTERS 62 63 1 MR. GLACKIN: A 23(F) PETITION WENT UP AND IT WAS 2 DENIED. THE PETITION PRESUMABLY WENT TO THE PANEL, THE MOTIONS 3 PANEL OF THE NINTH CIRCUIT. 4 THE COURT: UH-HUH. 5 MR. GLACKIN: AND THEY READ THE PETITION, THEY READ 6 OUR OPPOSITION, AND ABOUT 30 DAYS LATER THEY REJECTED THE 7 PETITION. 8 9 10 11 SO IF I -- IF I COULD ADDRESS THIS -THE COURT: YOU MEAN REJECTED THE PETITION TO JUST OVERTURN THE CLASS CERT DECISION? MR. GLACKIN: CORRECT. WELL, THEY DENIED -- IT'S A 12 PETITION FOR REVIEW, AND THEN THEY COULD, I THINK IN THEORY, 13 REQUEST FURTHER BRIEFING OR THEY COULD DECIDE -- THEY COULD 14 DECIDE THE QUESTION BASED SIMPLY ON THE PETITION AND THE 15 RESPONSE, WHICH I THINK IS TOTALLY NORMAL. 16 17 18 BUT IN THE -- IN ANY EVENT, THEY DENIED THE PETITION IS WHAT THEY DID. THE COURT: BUT WHY SHOULD I USE THE PLAUSIBLE 19 METHODOLOGY? 20 ENVIRONMENT WHEN ALL THE CASE LAW HAS BEEN CHANGING SO MUCH. 21 THAT SEEMS LIKE THAT'S A RISKY MOVE IN THIS MR. GLACKIN: WELL, I THINK THAT THE -- THE 22 SIGNIFICANT PROOF STANDARD THAT -- THE SIGNIFICANT PROOF OR THE 23 CONVINCING PROOF STANDARD THAT'S BEEN CITED BY THE 24 DEFENDANTS -- 25 THE COURT: YEAH. UNITED STATES COURT REPORTERS 63 64 1 2 3 MR. GLACKIN: -- IF YOU LOOK AND SEE WHERE THAT COMES FROM, EVERY SINGLE TIME IT COMES FROM DUKES. AND WHEN WE WERE HERE LAST TIME WE TALKED ABOUT THE FACT 4 THAT DUKES IS A CASE THAT'S ABOUT 23(A). 5 SUPREME COURT SAID THAT IF YOU ARE ARGUING THAT IT IS THE 6 ABSENCE OF A POLICY THAT HAS CAUSED HARM BY LEADING TO 7 DISCRIMINATION AGAINST A MILLION WORKERS AND THAT IS THE -- IT 8 IS THE ABSENCE OF THE POLICY THAT IS YOUR VIOLATION, AND IF 9 YOUR ONLY EVIDENCE THAT THIS IS TRULY A COMMON ISSUE IS AND IN DUKES THE 10 STATISTICAL PROOF, IF THIS IS THE ONLY EVIDENCE OF ANY COMMON 11 ISSUE IN THE CASE UNDER RULE 23(A), THEN THAT PROOF, THEY 12 USED -- IN ONE PLACE THEY USED STRONG PROOF, IN ANOTHER PLACE 13 THEY USED CONVINCING PROOF. 14 I THINK THE NINTH CIRCUIT, IN ELLIS VERSUS COSTCO, 15 ADDRESSING THE SAME QUESTION, USED THE PHRASE SIGNIFICANT 16 PROOF. 17 SO THAT IS THE STANDARD WHEN YOU HAVE -- WHEN YOU ARE 18 ASKING WHETHER THE ONLY QUESTION UNDER 23(A) THAT COULD 19 POSSIBLY BE COMMON IS REALLY COMMON WHEN THE ONLY EVIDENCE OF 20 IT IS STATISTICAL EVIDENCE. 21 THERE IS -- WE ARE -- WE CLEAR 23(A) BY A COUNTRY MILE. 22 THIS -- WHEN IT COMES TO RULE 23(A), THIS TRULY IS A TYPICAL 23 ANTITRUST CASE WHERE THERE IS A COMMON ISSUE, AN OVERWHELMING 24 COMMON ISSUE ABOUT WHETHER OR NOT THE DEFENDANTS VIOLATED THE 25 LAW. UNITED STATES COURT REPORTERS 64 65 1 2 AND THAT IS GOING TO BE -- THAT IS -- YOU KNOW, PERIOD, FULL STOP. 3 4 THE COURT: BUT YOU'RE REALLY ASKING FOR CERTIFICATION UNDER (B)(3); RIGHT? 5 MR. GLACKIN: CORRECT. BUT THE POINT IS THAT THE 6 DUKES CASE IS A CASE THAT'S ABOUT RULE 23(A) AND IT'S ABOUT 7 THIS UNUSUAL CIRCUMSTANCE WHERE THE ONLY POSSIBLE -- THE ONLY 8 COMMON -- I MEAN, THIS IS THE TRIAL THAT THE SUPREME COURT WAS 9 LOOKING AT, A TRIAL WHERE AN EXPERT WITNESS TAKES THE STAND AND 10 THE ONLY EVIDENCE OF A VIOLATION THAT IS COMPANY-WIDE IS 11 STATISTICAL, AND THAT IS THE ONLY COMMON ISSUE IN THE CASE. 12 AND AT THE TIME THE COMPANY HAS -- SHOULD, IN THEORY, HAVE, 13 AS A DEFENSE AGAINST THIS CASE, THE INDIVIDUAL DECISIONS OF THE 14 MANAGERS THAT ARE ALLEGED TO BE DISCRIMINATORY. 15 SO IN THAT SITUATION, THE SUPREME COURT SAID THAT WHEN YOU 16 HAVE -- AND THIS IS WHY DUKES HAS NOT, I MEAN, HAS NOT 17 MEANINGFULLY CHANGED THE LANDSCAPE. 18 CLASS CASES IT HAS NOT HAD A MEANINGFUL EFFECT, BECAUSE IN AN 19 ANTITRUST CASE, THE COMMON ISSUE IS SOMETHING WE BLOW BY VERY 20 QUICKLY AND THEY, IN FACT, CONCEDED THAT AT THE BEGINNING OF 21 THE FIRST ARGUMENT. CERTAINLY IN ANTITRUST 22 SO WHAT WE'RE ASKING IS WE'RE IN 23(B)(3), AND THE 23 QUESTION IS, HAVING OTHERWISE MET THE REQUIREMENTS FOR A CLASS 24 ACTION, SHOULD WE BE ALLOWED TO GO FORWARD WITH A DAMAGES CLASS 25 ACTION? UNITED STATES COURT REPORTERS 65 66 1 AND THERE THE STANDARD IS, HAVE WE ADVANCED A PLAUSIBLE 2 METHODOLOGY FOR PROVING IMPACT? 3 THE COURT: AND THE REASON -- BUT YOU'RE GOING TO HAVE TO GIVE ME SOME 4 AUTHORITY, OTHER THAN THE LCD ORDER, FOR PLAUSIBLE METHODOLOGY. 5 DO YOU HAVE -- IS THERE ANYTHING ELSE? 6 7 MR. GLACKIN: WELL, I WOULD -- I WOULD RESPECTFULLY SUBMIT THAT -- 8 THE COURT: 9 MR. GLACKIN: UH-HUH. -- THE AMGEN CASE IS THE BEST AUTHORITY 10 FOR THIS POINT, BECAUSE WHAT THE SUPREME COURT SAYS IN AMGEN IS 11 THAT -- WHAT I THINK THE DEFENDANTS WANT YOU TO DO, WHICH IS 12 CALL A WINNER OR A LOSER ON THIS QUESTION OF WHETHER OR NOT 13 WE'VE PROVEN COMMON IMPACT, THAT IS EXACTLY WHAT THE COURT IS 14 NOT SUPPOSED TO DO. 15 THE COURT IS SUPPOSED TO SIMPLY INQUIRE WHETHER OR NOT THE 16 ISSUE IS COMMON. 17 RISE OR FALL ON COMMON PROOF, THEN IT'S APPROPRIATE TO CERTIFY 18 A CLASS ACTION. 19 20 21 AND IF THE ISSUE IS COMMON, IF IT'S GOING TO AND IT'S NOT APPROPRIATE FOR THE COURT TO WEIGH THE INFERENCES THAT ARE BEING OFFERED BY THE PARTIES. THE COURT: LET ME ASK YOU TO COMMENT ON 22 MR. VAN NEST'S SUGGESTION ABOUT THE MASS TORT BELLWETHER MODEL. 23 HOW WOULD THAT -- I GUESS I'M JUST NOT CLEAR. 24 SAYING, OBVIOUSLY THIS IS YOUR DEFAULT, DEFAULT, DEFAULT, 25 DEFAULT POSITION, JUST CERTIFY A CLASS ON ANTITRUST LIABILITY, UNITED STATES COURT REPORTERS IF YOU'RE 66 67 1 HOW WOULD THAT PLAY OUT? 2 TRIALS ON INDIVIDUAL IMPACT AND DAMAGES? 3 MR. GLACKIN: WE'RE GOING TO HAVE, WHAT, INDIVIDUAL OR WHAT? WELL, THIS IS -- I MEAN, THIS IS 4 EXACTLY WHY IT WOULD BE, I THINK, THE WRONG -- BECAUSE, OKAY, 5 TO TELL YOU HOW IT WOULD PLAY OUT -- 6 THE COURT: 7 MR. GLACKIN: 8 9 10 YEAH. -- IN THE HYPOTHETICAL SCENARIO WHERE THAT HAPPENED -THE COURT: UM-HUM. MR. GLACKIN: -- WE WOULD HAVE THE TRIAL ON 11 LIABILITY, THAT WOULD HAPPEN. 12 GUESS WE WOULD BRING IN THE EMPLOYEES OF THESE COMPANIES ONE AT 13 A TIME TO PROVE IMPACT. 14 AND THEN WE WOULD BRING -- I BUT IN EVERY SINGLE CASE, THE PROOF OF IMPACT WOULD BE THE 15 OPINION THAT THIS CONDUCT, THAT THIS CONDUCT AFFECTED THE PAY 16 STRUCTURE OF THE ENTIRE COMPANY. 17 AND I DON'T -- YOU KNOW, WE'RE NOT ASKING FOR THAT KIND OF 18 A CLASS TO BE CERTIFIED. 19 THAT WAY, FRANKLY. 20 I SEE NO WAY TO PROSECUTE THE CASE IT MAKES ABSOLUTELY NO SENSE. THE COURT: ALL RIGHT. SO IF I'M NOT GOING TO -- SO 21 THEN YOU WOULDN'T WANT A CLASS CERTIFIED JUST BASED ON 22 ANTITRUST LIABILITY? 23 MR. GLACKIN: NO, BECAUSE I CAN'T -- I REALLY CAN'T 24 SEE A PLAN AFTER THAT THAT WOULD MAKE ANY SENSE, JUST LIKE I 25 CAN'T SEE HOW A MASS TORT PLAN WOULD MAKE ANY SENSE, BECAUSE UNITED STATES COURT REPORTERS 67 68 1 THE WHOLE POINT HERE THAT WE ESTABLISHED WITH MR. MITTELSTAEDT 2 AT THE FIRST HEARING IS THAT WE'RE NEVER GOING TO KNOW WHO 3 WOULD HAVE GOTTEN THE COLD CALLS. 4 WHICH SPECIFIC JOB TITLES WOULD HAVE GOTTEN THE WAVES OF -- THE 5 COLD CALLS FROM THE 800 GOOGLE RECRUITERS. 6 BECAUSE IT DIDN'T HAPPEN. 7 THE IMPACT FROM THE COLD CALL THAT DIDN'T HAPPEN BECAUSE WE 8 DON'T KNOW WHERE THAT COLD CALL WENT. 9 WE'RE NEVER GOING TO KNOW WE'LL NEVER KNOW SO WE CAN NEVER TRACE OUT, YOU KNOW, AND THAT'S WHY THE DEFENDANTS WANT THIS STANDARD. IF THE 10 STANDARD IS WE HAVE TO SHOW -- THAT WE HAVE TO PROVE THAT A 11 COLD CALL HAPPENED, WOULD HAVE HAPPENED TO A SPECIFIC PERSON 12 AND SHOW THE PROPAGATION OUTWARD FROM THAT COLD CALL, I MEAN, 13 WE CAN'T WIN. 14 THAT STANDARD IS SO FAVORABLE TO THEM. 15 I MEAN, WE MIGHT AS WELL GO HOME, AND THAT'S WHY THE COURT: WELL, LAST TIME WHEN WE HAD SEVEN 16 DEFENDANTS, THE PARTIES PREDICTED THAT THE TRIAL WOULD BE 17 17 DAYS. 18 INTUIT? 19 WHAT IS IT NOW THAT IT'S MINUS LUCASFILM, PIXAR, AND MR. GLACKIN: I'M THINKING. I MEAN, I WOULD IMAGINE 20 THAT THE PLAINTIFFS' CASE PROBABLY COULD BE PUT ON IN SOMETHING 21 LIKE SIX OR SEVEN TRIAL DAYS, MAYBE EIGHT OR NINE. 22 KNOW. I DON'T I'M A LITTLE HESITANT. 23 I WOULD IMAGINE THAT THE REDUCTION IN THE NUMBER OF 24 DEFENDANTS WOULD MEAN THAT YOU WOULD HAVE, YOU KNOW, FEWER 25 DEFENDANTS WHO WANTED TO PUT ONE OR TWO CORPORATE UNITED STATES COURT REPORTERS 68 69 1 REPRESENTATIVES ON THE STAND TO SAY EITHER THAT THEY DIDN'T DO 2 ANYTHING WRONG OR THE AGREEMENTS NEVER WOULD HAVE HAD THIS 3 IMPACT. 4 SO I WOULD SUSPECT THAT ON THE DEFENSE SIDE, THE BACK END 5 WOULD GET LOWER. 6 MATTER WHAT. 7 I THINK OUR CASE IS KIND OF THE SAME NO THE COURT: WHAT ABOUT FOR THE DEFENDANTS? 8 THE NEW ESTIMATED TRIAL LENGTH? 9 MR. VAN NEST: WHAT IS 10 11 I HAVEN'T THOUGHT THAT THROUGH CAREFULLY ENOUGH, YOUR HONOR. BUT I WOULD SAY, I THINK IT DOES MATTER. IF THE EVIDENCE 12 FOR LUCASFILM AND PIXAR AND INTUIT IS OUT, WHICH I THINK IT 13 SHOULD BE, THEN ARGUABLY WE COULD DO IT IN LESS TIME. 14 THAT'S CLEARLY RIGHT. 15 I THINK AND IF -- IF THEY'RE SAYING THEY WANT TO PROVE JUST EXACTLY 16 WHAT THEY STARTED OFF WITH, THEN I DON'T THINK THE TIME 17 SHRINKS. 18 BUT IN MY VIEW, THE EVIDENCE AFFECTING THOSE COMPANIES IS 19 DIFFERENT AND NOT REALLY RELATED ANYMORE AND IT WOULD BE A 20 LITTLE SHORTER. 21 I -- 22 THE COURT: 23 MR. VAN NEST: 24 THE COURT: 25 LET ME -OH, SORRY. LET ME HEAR FROM MR. GLACKIN. YOUR -- TELL ME HOW YOUR CASE AT TRIAL WOULD LOOK. UNITED STATES COURT REPORTERS FOR HOW WOULD 69 70 1 IT BREAK DOWN BETWEEN LIABILITY VERSUS IMPACT VERSUS DAMAGES? 2 MR. GLACKIN: WELL, I CAN TELL YOU THAT, HAVING DONE 3 ONE OF THESE CASES, THAT THE IMPACT AND DAMAGES PART OF THE 4 CASE IS NOT GOING TO TAKE A LOT OF TIME. 5 SPEND A LOT OF TIME ON THOSE ISSUES AT CLASS CERTIFICATION, BUT 6 AT TRIAL, THE DIRECT EXPERT TESTIMONY ON THOSE POINTS WILL BE 7 OVER IN TWO TO THREE HOURS I WOULD SUSPECT ON IMPACT AND 8 DAMAGES. 9 I MEAN, WE -- WE AND THEN I WOULD SUSPECT THAT THE DEFENDANTS ARE GOING TO 10 HAVE AT LEAST ONE OR POSSIBLY TWO ECONOMETRICIANS WHO WILL COME 11 IN AND SAY THAT OUR ECONOMETRICIAN IS WRONG. 12 YOU KNOW, THIS CASE -- I SUPPOSE I MIGHT HAVE TO EXPAND 13 THAT ESTIMATE A BIT IF WE'RE GOING TO HAVE EXPERT TESTIMONY -- 14 IF WE'RE BUILDING INTO THAT CATEGORY EXPERT TESTIMONY ABOUT 15 THESE COMPANIES' COMPENSATION STRUCTURES. 16 BUT, AGAIN, IT'S NOT A BIG PART OF THE CASE. MOST OF THE 17 CASE WILL BE ABOUT THE AGREEMENTS AND THE, THE SUBJECTIVE 18 INTENT OF THE PEOPLE WHO REACHED THEM. 19 20 21 22 23 BY THE WAY, I HAVE -MR. VAN NEST: I HAVE A DIFFERENT VIEW, OBVIOUSLY, YOUR HONOR, ON A NUMBER OF THESE POINTS. MR. GLACKIN: I HAVE A PLAUSIBLE METHODOLOGY CASE FOR YOU, YOUR HONOR. 24 THE COURT: ALL RIGHT. 25 MR. GLACKIN: WHAT'S THAT? I'D OFFER YOU THE GPUS DECISION, WHICH UNITED STATES COURT REPORTERS 70 71 1 WE QUOTED IN OUR BRIEF, AND I WOULD ACTUALLY OFFER THE PASSAGE 2 THAT WE QUOTED, I THINK IN OUR REPLY BRIEF, WHICH SAYS -- 3 THE COURT: YOU KNOW, I FEEL SOMEWHAT HESITANT ON 4 RELYING ON ANY DISTRICT COURT CASE THAT WAS BEFORE THE SUPREME 5 COURT CASES. 6 BECAUSE THEY MAY ADDRESS ISSUES THAT ARE MORE ON POINT. 7 8 I MEAN, OBVIOUSLY THEY'RE -- WE MAY HAVE TO JUST BUT ANYWAY, GO AHEAD. SO YOU WANTED GPU, JUDGE ALSUP'S DECISION. 9 MR. GLACKIN: JUDGE ALSUP'S DECISION, WHICH IS THE 10 AUTHORITY THAT THE DEFENDANTS HAVE -- I MEAN, WE BLOCK QUOTED 11 THIS IN OUR BRIEF. 12 PLAINTIFFS DID IN THAT CASE WASN'T ENOUGH, HE WAS CAREFUL TO 13 QUALIFY IT BY SAYING, "THIS ORDER AGREES THAT SUCH METHODS WERE 14 PLAUSIBLY RELIABLE, SHOULD BE ALLOWED AS A MEANS OF COMMON 15 PROOF. 16 FREE PASS IN MANY INDUSTRIES." 17 WHEN HE -- WHEN HE RULED THAT WHAT THE TO RULE OTHERWISE WOULD ALLOW ANTITRUST VIOLATORS A THE COURT: ALL RIGHT. LET ME ASK MY QUESTION. LET 18 ME ASK MR. VAN NEST, AND I THINK WE'RE GETTING -- WE'VE BEEN 19 GOING ALMOST AN HOUR AND A HALF. 20 21 22 23 (DISCUSSION OFF THE RECORD BETWEEN THE COURT AND THE COURT REPORTER.) THE COURT: LET'S GO A LITTLE BIT MORE AND THEN WE'LL HAVE TO TAKE A BREAK. 24 LET ME ASK MR. VAN NEST, IT SEEMS -- IT SEEMS LIKE THE 25 DEFENDANTS ARE ARGUING THAT IT'S NOT ENOUGH THAT THERE ARE UNITED STATES COURT REPORTERS 71 72 1 COMMON QUESTIONS, BUT THAT THE RESULT HAS TO BE THE SAME FOR 2 ALL 60,000 CLASS MEMBERS. 3 4 DO YOU WANT TO COMMENT ON THE WHOLE SORT OF COMMON QUESTION VERSUS COMMON ANSWERS -- 5 MR. VAN NEST: 6 THE COURT: 7 -- ISSUE AND WHAT'S REQUIRED BY THE CASE LAW -- 8 MR. VAN NEST: 9 THE COURT: 10 11 SURE. YEAH. -- CURRENTLY? MR. VAN NEST: ABSOLUTELY, YOUR HONOR. THAT'S NOT WHAT WE'RE ARGUING. WE'RE ARGUING -- WE'RE 12 FOLLOWING UP ON WHAT YOU SAID LAST TIME, WHICH IS THAT IF YOU 13 WANT TO PROCEED AS A CLASS, A (B)(3) CLASS WHERE PEOPLE ARE 14 GOING TO GET DAMAGES, AND YOU WANT TO DO IT IN ONE BIG TRIAL, 15 YOU HAVE TO SHOW THAT ALL OR NEARLY ALL OF THE CLASS MEMBERS 16 WERE IMPACTED, BECAUSE IMPACT IS AN ELEMENT OF LIABILITY. 17 THAT'S THE WHOLE POINT. 18 IMPACTED IS NECESSARY TO ESTABLISH LIABILITY. 19 IN AN ANTITRUST CASE, WHETHER THEY'RE SO IF WE'RE GOING TO DO IT FOR A CLASS, THE RULE IS -- AND 20 THIS IS WHAT JUDGE ALSUP SAID IN GPU AND JUDGE GRADY SAID IN 21 REED -- YOU HAVE TO SHOW THAT ALL OR NEARLY ALL MEMBERS OF THE 22 CLASS WERE IMPACTED. 23 24 25 AND YOU SAID THAT LAST TIME, TOO. THAT'S THE ASSIGNMENT YOU GAVE US. NOW, IN ORDER TO SHOW THAT, YOU'RE QUITE RIGHT, THERE'S UNITED STATES COURT REPORTERS 72 73 1 NO -- NO LONGER IS A PLAUSIBLE THEORY ENOUGH. 2 THAT, DUKES CHANGED THAT, AND ELLIS IN THE NINTH CIRCUIT 3 CHANGED THAT. 4 COMCAST CHANGED AND YOU SAID -- YOU GOT IT RIGHT AT PAGE 16 OF YOUR ORDER 5 WHERE YOU SUMMARIZE ALL OF THIS. 6 RELY ON PLAUSIBLE THEORIES. 7 THOROUGH REVIEW OF THEIR THEORY AND YOU HAVE TO DO A RIGOROUS 8 EVALUATION AND ANALYSIS TO SEE IF THIS IS REALLY PERSUASIVE." 9 AND WHAT YOU SAID LAST TIME WAS, "IF YOU GUYS WANT TO YOU SAID, "I'M NOT GOING TO I THINK YOU HAVE TO CONDUCT A 10 CERTIFY A CLASS, YOU HAVE TO SATISFY TWO REQUIREMENTS. 11 HAVE TO SHOW THAT THE COMP STRUCTURES WERE SO RIGID THAT IMPACT 12 ON SOME WOULD AFFECT EVERYBODY, OR NEARLY EVERYBODY; AND YOU 13 HAVE TO SHOW THAT YOUR CLASS IS NARROWLY DRAWN SO THERE AREN'T 14 A WHOLE LOT OF PEOPLE IN IT THAT WEREN'T IMPACTED AT ALL AND 15 WEREN'T INJURED AND DAMAGED," AND THEY FLUNKED ON BOTH OF THOSE 16 UNDER ANY STANDARD. 17 18 19 YOU REMEMBER, UNDER THE STANDARD THAT JUDGE ALSUP APPLIED IN GPU, HE DENIED CERT EVEN THERE. THEY FAILED TO SHOW THAT THE SALARY STRUCTURES ARE SO RIGID 20 THAT WHATEVER HAPPENED WHEN PEOPLE DIDN'T GET CALLS WOULD 21 PROPAGATE. 22 AND AS I POINTED OUT, TAB 1 AND TAB 2, DR. LEAMER ADMITS 23 THAT HE CAN'T MAKE THAT SHOWING AND HE DOESN'T THINK IT'S TRUE. 24 25 SO IF THAT'S THE CASE, NOW WE'RE LOOKING AT, OKAY, WHAT DO WE HAVE? DO WE HAVE SOME TITLES THAT -- WHERE WE CAN SHOW UNITED STATES COURT REPORTERS 73 74 1 2 PROPAGATION EVEN WITHIN A TITLE? AND THE ANSWER TO THAT IS THE MURPHY EXHIBITS SHOWING LOTS 3 OF VARIATION IN THE SAME JOB TITLE YEAR IN AND YEAR OUT AT 4 EVERY ONE OF THE DEFENDANTS. 5 SO THERE ISN'T A RIGID WAGE STRUCTURE, AND -- 6 7 THE COURT: WEREN'T EVEN REALLY CHALLENGING LIABILITY, SO -- 8 9 YOU KNOW, LAST TIME AROUND YOU ALL MR. VAN NEST: WELL, BUT -- NO, WE WERE CHALLENGING THE SAME THING. 10 THE COURT: BUT -- 11 MR. VAN NEST: 12 THE COURT: 13 CONCEDED LIABILITY LAST TIME. WELL, I MEAN, NO. 14 MR. VAN NEST: 15 THE COURT: 16 NO, NO. NO. YOU BASICALLY SORT OF WHAT WAS -- SO I'M CURIOUS, NOW YOU'RE SAYING, "OH, LET'S GO BACK" -- 17 MR. VAN NEST: 18 THE COURT: 19 IMPACT IS -- NO. -- "AND LIABILITY AND IMPACT IS PART OF LIABILITY," BUT YOU ESSENTIALLY CONCEDED THAT POINT LAST TIME. 20 MR. VAN NEST: NO, NO. WHAT WAS SAID LAST TIME, YOUR 21 HONOR, IS -- YOU JUST INVITED THEM, DO THEY WANT TO HAVE A 22 CLASS CERTIFIED OVER WHETHER THERE WAS A CONSPIRACY TO IMPACT 23 WAGES, ET CETERA, ET CETERA. 24 25 AND THEY DON'T WANT THAT. KAHUNA. THEY WANT -- THEY WANT THE WHOLE THEY WANT EVERYTHING IN ONE TRIAL. UNITED STATES COURT REPORTERS 74 75 1 FAIR ENOUGH. FAIR ENOUGH. 2 IF THEY WANT -- WHAT WE SAID LAST TIME WAS WE'RE NOT 3 CHALLENGING THAT PROOF OF THE CONSPIRACY IS NOT COMMON. 4 COMMON. THAT'S WE SAID THAT'S A COMMON ISSUE. 5 BUT THAT DOES NOT ENTITLE YOU TO CERTIFICATION BECAUSE YOU 6 HAVE TO SHOW THAT COMMON ISSUES PREDOMINATE, AND THE BIG ISSUE 7 FOR THEM IS GOING TO BE -- AND BELIEVE ME, IT'S NOT A COUPLE 8 HOURS -- THE HUGE ISSUE IN THIS CASE IS GOING TO BE, GIVEN THE 9 NATURE OF WHAT THEY'RE ALLEGING, CAN THEY SHOW IMPACT TO ALL OR 10 NEARLY ALL MEMBERS OF THE CLASS? 11 THAT'S GOING TO REQUIRE TESTIMONY FROM THE H.R. PEOPLE AT 12 EVERY SINGLE DEFENDANT. 13 EXPERTS ABOUT WHAT THE DEFENDANTS' PAY STRUCTURES AND PRACTICES 14 WERE. 15 WHAT THEY DID AND WHY. 16 EXPERTS UP TO TALK ABOUT THE BIG PICTURE. 17 IT'S GOING TO REQUIRE TESTIMONY FROM THERE'S GOING TO BE TESTIMONY FROM EACH COMPANY ABOUT IT'S NOT JUST PUTTING A COUPLE OF THE JURY WOULD HAVE TO KNOW, BECAUSE YOU'RE TALKING ABOUT 18 THIS MANY EMPLOYEES, HOW DO THESE COMPANIES MANAGE H.R.? 19 DID THEY LOOK AT? 20 WHAT HOW MUCH VARIATION WAS THERE? WE WILL PROBABLY BE CALLING MANAGERS TO SAY, "I WOULD 21 NEVER RAISE THE SALARY OF EVERYBODY IN MY UNIT BECAUSE I'VE GOT 22 TO PROTECT MY TOP PERFORMER. 23 WOULD BE CRAZY." I'D RUN OUT OF BUDGET. THAT 24 AND THERE'S NO EVIDENCE THAT ANYBODY EVER DID THAT. 25 ALL THE EVIDENCE IS THAT IF YOU HAVE SOMEBODY THAT'S A UNITED STATES COURT REPORTERS 75 76 1 HIGH PERFORMER YOU HAVE TO PROTECT, THEY GET A BIG SALARY 2 SPIKE, JUST LIKE TAB 4 AND TAB 5 SHOW. 3 AND SO THE BIG ISSUE THAT WE UNDERSTOOD FROM YOUR HONOR'S 4 ORDER, ONE OF THE BIG ISSUES THAT WAS LEFT OVER WAS, CAN THEY 5 SHOW IMPACT ON A CLASS-WIDE BASIS? 6 THAT'S WHY, IN MY VIEW, A -- 7 THE COURT: SO DO YOU BELIEVE THAT THE TEST RIGHT NOW 8 IS JUST WHETHER COMMON QUESTIONS PREDOMINATE FOR A 23(B)(3) 9 CLASS -- 10 MR. VAN NEST: 11 THE COURT: 12 MR. GLACKIN: 13 THE COURT: 14 MR. VAN NEST: 15 THE COURT: 16 MR. VAN NEST: YOU HAVE -- -- TO BE CERTIFIED? ARE YOU POSITING THAT TO ME OR TO HIM? TO MR. VAN NEST. FOR A (B)(3) CLASS -- YES. -- YOU HAVE TO SHOW THAT COMMON 17 QUESTIONS PREDOMINATE AND THAT THERE IS, THAT THERE IS A THEORY 18 THAT PASSES A RIGOROUS ANALYSIS BASED ON RELIABLE EVIDENCE THAT 19 THERE WAS IMPACT TO ALL OR NEARLY ALL MEMBERS OF THE CLASS. 20 21 IF YOU DON'T HAVE THAT, THEN YOU CAN PROCEED WITH BELLWETHER TRIALS, CERTAINLY, AND WITH A BELLWETHER TRIAL -- 22 THE COURT: AND YOU'RE RELYING, FOR THAT SECOND HALF, 23 SEPARATE FROM WHETHER COMMON QUESTIONS PREDOMINATE, JUST ON MY 24 ORDER? 25 THAT'S WHAT YOU'RE BASING IT ON? MR. VAN NEST: I'M RELYING PRIMARILY ON YOUR ORDER. UNITED STATES COURT REPORTERS 76 77 1 2 BUT THAT'S WHAT JUDGE ALSUP AND JUDGE GRADY, ALL THESE CASES -- THE WHOLE POINT -- 3 4 THE COURT: WHAT ARE YOU RELYING ON FOR YOUR SECOND -- ARTICULATE THE SECOND HALF -- 5 MR. VAN NEST: 6 THE COURT: 7 8 9 THE SECOND HALF -- -- OF WHAT YOU BELIEVE THE STANDARD TO BE. MR. VAN NEST: I BELIEVE THE STANDARD IS THAT THE PLAINTIFFS HAVE TO SHOW THAT THEY CAN PROVE, BY COMMON 10 EVIDENCE, THAT THERE WAS CLASS-WIDE IMPACT, AND I'LL CITE 11 COMCAST FOR THAT, I'LL CITE AMCHEM FOR THAT, I'LL CITE REED FOR 12 THAT, I'LL CITE GPU FOR THAT. 13 ALL THESE CASES SAY THAT YOU HAVE TO BE ABLE TO PROVE, FOR 14 A (B)(3) CLASS -- WHICH IS A HIGHER STANDARD, BY THE WAY, THAN 15 JUST A 23(A) -- YOU HAVE TO PROVE THAT THERE WAS IMPACT, 16 CLASS-WIDE IMPACT AS PART OF YOUR ANTITRUST CLAIM. 17 18 19 AND THEY DIDN'T DISAGREE WITH THAT. THE COURT: SO YOUR STANDARD IS COMMON EVIDENCE TO PROVE CLASS-WIDE IMPACT? 20 MR. VAN NEST: 21 THE COURT: 22 23 RIGHT. OKAY. BECAUSE YOU HAD OTHER EXTRA ADVERBS AND ADJECTIVES IN THERE EARLIER. MR. VAN NEST: WELL, I'M -- WHAT YOU -- THE WAY YOU 24 DESCRIBED IT IN THE ORDER, YOU DESCRIBED IT AS PROVING THAT 25 THERE WAS IMPACT TO ALL OR NEARLY ALL MEMBERS OF THE CLASS. UNITED STATES COURT REPORTERS 77 78 1 THAT'S WHAT YOU SAID IN YOUR ORDER. 2 AND I WOULD AGREE WITH THAT. THAT'S WHAT THESE CASES ALL 3 REQUIRE WHEN THEY SAY YOU HAVE TO HAVE PROOF OF CLASS-WIDE 4 IMPACT. 5 AND YOU CAN SEE -- PAGE 43 OF YOUR ORDER IS WHAT I'M 6 DRAWING ON. 7 THE STANDARD YOU SET UP AND THAT'S THE STANDARD THAT APPLIES. 8 9 PAGE 36 TO THE SAME EFFECT. AND THEY HAVEN'T MET IT. THAT'S WHAT -- THAT'S THEY HAVEN'T MET IT BECAUSE DR. LEAMER ADMITS THAT HE CAN'T SAY THAT THE SALARY STRUCTURES 10 WERE SO RIGID THAT CHANGES TO SOME WOULD HAVE TRANSLATED INTO 11 CHANGES FOR ALL. 12 AND THE RAW DATA THAT WE'VE PRESENTED AND THAT DR. MURPHY 13 ANALYZED PROVES IT AGAIN, NAMELY, THERE'S HUGE VARIATION AND 14 FLEXIBILITY IN PAY AND IT'S BASED ON INDIVIDUAL FACTORS. 15 AND WHAT DR. SHAW DID, OUR ECONOMIST FROM STANFORD -- SHE 16 HAS BEEN IN SILICON VALLEY FOR THE PAST 20 YEARS TALKING TO 17 H.R. PEOPLE, AND SHE SAYS THE DATA THAT COMES OUT OF THESE 18 COMPANIES IS CONSISTENT WITH THE PREVAILING PRINCIPLE IN 19 SILICON VALLEY, PAY FOR PERFORMANCE. PAY FOR PERFORMANCE. 20 THESE ARE ENTREPRENEURIAL COMPANIES. THEY ARE CUTTING EDGE. 21 THEY ARE NOT LOCKSTEP. 22 KNOW, GOVERNED BY COLLECTIVE BARGAINING AGREEMENTS WHERE 23 EVERYTHING IS IN SOME KIND OF A SCHEDULE. 24 PERFORMANCE, AND THE DATA PROVES THAT. 25 THEY ARE NOT LABOR. THEY ARE NOT, YOU IT'S PAY FOR AND GIVEN THAT THAT'S THE CASE, WE'RE BETTER OFF TRYING A UNITED STATES COURT REPORTERS 78 79 1 HANDFUL -- AND I MEAN A HANDFUL -- OF CASES WHERE AN INDIVIDUAL 2 PLAINTIFF COMES IN AND SAYS, "I WAS AT COMPANY A AND COMPANY A 3 HAD AN AGREEMENT WITH COMPANY B AND I AND MANY OTHERS WERE 4 PRIME PERFORMING CANDIDATES THAT WOULD HAVE GOTTEN COLD CALLS 5 AND HERE'S HOW I WAS INJURED. 6 PAY WOULD HAVE GONE UP," AND SO ON AND SO FORTH. I WOULD HAVE GOTTEN A CALL, MY 7 THAT'S GOING TO BE A BETTER WAY TO RESOLVE THIS CASE THAN 8 SOME TRIAL, WHICH THEY HAVEN'T ESTABLISHED A BASIS FOR, WHERE 9 THEY TRY TO PROVE CLASS-WIDE IMPACT ACROSS THE WHOLE CLASS WITH 10 11 12 COMMON EVIDENCE. AND YOUR HONOR, IT'S -THE COURT: YOU KNOW, I'M LOOKING AT THE DEFENDANTS' 13 ADMINISTRATIVE MOTION TO CONSIDER WHETHER CASES SHOULD BE 14 RELATED FILED ON JULY 19TH OF 2011, AND THE DEFENDANTS IN THIS 15 CASE BASICALLY SAID, "THESE CASES INVOLVE THE SAME ALLEGED 16 CLASS, SAME FACTUAL ALLEGATIONS, SAME CLAIMS FOR RELIEF. 17 BECAUSE THE CASES INVOLVE SUBSTANTIALLY THE SAME PARTIES, 18 EVENTS, AND ALLEGATIONS, AND BECAUSE IT APPEARS LIKELY THAT 19 THERE WILL BE AN UNDULY BURDENSOME DUPLICATION OF LABOR AND 20 EXPENSE OR CONFLICTING RESULTS IF THEY ARE HEARD BEFORE 21 DIFFERENT JUDGES, DEFENDANTS BELIEVE THEY ARE RELATED WITHIN 22 THE MEANING OF THE RELATED CASE." 23 MR. VAN NEST: 24 THE COURT: 25 I'LL STAND BY EVERY WORD OF THAT. THERE WAS A TIME WHERE YOU ALL WANTED ALL THIS CONSOLIDATED BECAUSE YOU CONCEDED THAT, FOR PURPOSES OF UNITED STATES COURT REPORTERS 79 80 1 ADMINISTRATION, IT MADE MUCH MORE SENSE -- 2 MR. VAN NEST: 3 THE COURT: 4 MR. VAN NEST: 5 IT DOES. -- TO HAVE THESE TOGETHER. ABSOLUTELY. AND I'M NOT SAYING ANYTHING DIFFERENT TODAY, YOUR HONOR. 6 THE COURT: UM-HUM. 7 MR. VAN NEST: THERE'S NO -- WE WOULDN'T WANT FIVE 8 JUDGES DECIDING THE ISSUE THAT YOUR HONOR IS EVALUATING NOW, 9 AND WE WOULDN'T WANT FIVE JUDGES HANDLING THE CASE, NO MATTER 10 HOW WE DID IT, BECAUSE AS WE SAID LAST TIME, IF THEY'RE GOING 11 TO PROVE A CONSPIRACY, THAT EVIDENCE IS COMMON TO EVERYONE. 12 RIGHT? 13 OF THIS WHERE YOU HAVE TO SHOW THAT SOMEBODY CONSPIRED TO DO 14 SOMETHING, THAT IS COMMON AND THEY INTEND TO PROVE THAT IN A 15 COMMON WAY. 16 THAT'S WHAT WE'RE SAYING IS THAT THE PROOF OF PART ONE WE GET THAT. NOW, YOU OFFERED THEM CERTIFICATION ON THAT AND THEY DON'T 17 WANT IT. 18 THEY WANT TO PUT 60,000 PEOPLE IN A CLASS AND START THROWING 19 SOME HUGE NUMBERS AROUND, WHICH IS WHAT THEY'RE DOING. 20 21 THEY DON'T WANT THAT BECAUSE AND WHAT WE'RE SAYING IS YOU HAVEN'T ESTABLISHED THE PREDICATE FOR THAT BECAUSE YOU HAVEN'T -- 22 23 THEY DON'T WANT THAT. THE COURT: OKAY. LET ME INTERRUPT YOU ONE SECOND, PLEASE. 24 MR. VAN NEST: 25 THE COURT: SURE. LET ME ASK MR. GLACKIN -- UNITED STATES COURT REPORTERS 80 81 1 MR. GLACKIN: I HAVE A FEW WORDS ABOUT THE LEGAL 2 STANDARD I THINK YOU'RE MULLING OVER, IF I COULD RESPOND TO 3 THAT BRIEFLY. 4 THE COURT: GO AHEAD, PLEASE. 5 MR. GLACKIN: SO FIRST I'D OFFER YOU ANOTHER DISTRICT 6 COURT CASE, WHICH IS PRE-AMGEN, OF COURSE, BUT I BELIEVE IT'S 7 POST-DUKES -- 8 THE COURT: OKAY. 9 MR. GLACKIN: -- WHICH IS THE IN RE: RAIL FREIGHT 10 DECISION OUT OF THE DISTRICT OF COLUMBIA, WHICH IS 2012 WL, 11 WEST LAW, 2870207 AT STAR 60. 12 THE COURT: 13 MR. GLACKIN: 14 THE COURT: 15 MR. GLACKIN: 2870207? 2870207, CORRECT. OKAY. AND I THINK THE URETHANES CASE THAT WE 16 CITED IN OUR MOST RECENT BRIEF, WHICH WAS A CASE IN WHICH THE 17 COURT, AFTER TRIAL, CONSIDERED A REQUEST TO DECERTIFY A CLASS 18 POST-COMCAST AND AMGEN -- I ALWAYS MIX UP AMCHEM AND AMGEN -- 19 POST-AMGEN AND COMCAST WOULD ALSO BE INSTRUCTIVE, AND IT WOULD 20 SEE -- YOU WOULD SEE A DISTRICT COURT IN AN ANTITRUST CASE 21 APPLYING THOSE NEW CASES AND DENYING A MOTION TO DECERTIFY A 22 CLASS. 23 THE COURT: 24 MR. GLACKIN: 25 WHICH CASE IS THAT? THAT IS -- IT'S IN OUR MOST RECENT REPLY BRIEF, IN RE: URETHANE ANTITRUST LITIGATION, 2013 U.S. UNITED STATES COURT REPORTERS 81 82 1 2 DIST LEXIS, IT'S THE LEXIS CITE, 69784. AND IF I COULD SAY JUST ONE MORE THING? I MEAN, WHAT I 3 UNDERSTAND YOUR HONOR TO BE GRAPPLING WITH A LITTLE BIT HERE IS 4 THE STRONG PROOF, CONVINCING PROOF VERSUS A COMMON QUESTION IS 5 ENOUGH REGARDLESS OF WHETHER OR NOT THE ANSWER TO THE COMMON 6 QUESTION IS YES OR NO. 7 THE COURT: 8 MR. GLACKIN: 9 UM-HUM. AND WHAT I WOULD POINT OUT IS THAT IF DUKES WAS ABOUT THE 23(B)(3) STANDARD, YOU COULD NOT RECONCILE 10 IT WITH AMGEN. 11 THE PLAINTIFFS HAVE TO DO, AND THE REASON IS THAT DUKES IS A 12 CASE ABOUT -- IN THE CIRCUMSTANCES I DESCRIBED, WHICH I WON'T 13 REPEAT, AND AMGEN IS A CASE THAT'S ACTUALLY ABOUT RULE 14 23(B)(3). 15 THE CASES SAY VERY DIFFERENT THINGS ABOUT WHAT SO I THINK THAT, YOU KNOW, THE LIGHT HERE IN TERMS OF WHAT 16 SHOULD BE FOLLOWED IN DECIDING WHETHER OR NOT WE'VE MET THE 17 STANDARD OF RULE 23(B)(3), WHICH IS PREDOMINANCE OF COMMON 18 QUESTIONS, IS AMGEN. 19 DUKES. IT'S CLEARLY AMGEN AND IT'S CLEARLY NOT 20 SO, YOU KNOW, I THINK THAT -- I WOULD JUST POINT OUT THAT 21 IF THE DEFENDANTS ARE RIGHT AND DUKES IS A 23(B)(3) CASE, THE 22 SUPREME COURT IN AMGEN WOULD HAVE HAD TO OVERTURN IT BECAUSE 23 YOU CAN'T RECONCILE THOSE TWO STANDARDS. 24 25 THE COURT: LET ME ASK, YOU KNOW, THE CASES -- THE AMOUNT OF DOCUMENTARY EVIDENCE IN THIS CASE IS SIGNIFICANTLY UNITED STATES COURT REPORTERS 82 83 1 GREATER, I THINK, THAN PRETTY MUCH ANY OF THE OTHER CASES. 2 KNOW, FOR EXAMPLE, IN DUKES THEY HAD SOME ANECDOTAL EVIDENCE OF 3 DISCRIMINATION FROM, WHAT, 200 -- 120 WOMEN. 4 STATISTICAL EVIDENCE AND THEN THEY HAD A SOCIOLOGIST TALK ABOUT 5 WAL-MART CULTURE. 6 THEY HAD WE DON'T HAVE THAT SITUATION. 7 MR. GLACKIN: 8 THE COURT: 9 YOU CORRECT. WE HAVE A POLICY, A SPECIFIC CONTRACTUAL POLICY AMONGST THE DEFENDANTS. 10 MR. GLACKIN: 11 THE COURT: CORRECT. WE'RE JUST NOT -- IF YOU LOOK AT THE 12 OTHER CASES, THEY JUST DON'T HAVE THIS LEVEL OF DOCUMENTARY 13 EVIDENCE. 14 MR. GLACKIN: 15 THE COURT: I MEAN, IF -- SO WHAT IS THE SIGNIFICANCE OF THE 16 STATISTICAL EVIDENCE? 17 THIS MUCH DOCUMENTARY EVIDENCE? 18 MR. GLACKIN: 19 20 HOW IMPORTANT IS IT IN A CASE THAT HAS WELL, I THINK THAT IT IS OF MUCH LESS IMPORTANCE. AND, YOU KNOW, AS AN EXERCISE, BECAUSE I WAS INTERESTED, 21 BEFORE WE CAME DOWN HERE I ASKED MY PARTNER, MR. HARVEY, TO 22 PULL THE EXPERT REPORTS IN GPUS, BECAUSE I WAS CURIOUS TO SEE 23 EXACTLY WHAT HAD HAPPENED BECAUSE JUDGE ALSUP'S OPINION IS A 24 LITTLE AMBIGUOUS. 25 THE DEFENDANTS CAN PULL THEM OFF OF ECF, AND YOU CAN DOWNLOAD AND WE'D BE HAPPY TO SUPPLY THEM TO YOU, AND UNITED STATES COURT REPORTERS 83 84 1 2 THEM FROM ECF, TOO. AND WHAT DR. TEECE HAS IN THAT CASE IS HE HAS A CORRELATION 3 ANALYSIS WHERE HE'S MASHED TOGETHER -- HE'S CALCULATED THREE 4 CORRELATIONS. 5 OF THE ACTION INTO THREE GROUPS AND SHOW THAT THEY CORRELATE. 6 7 8 9 HE'S MASHED TOGETHER ALL THE PRODUCTS IN TERMS HE'S GOT NO DOCUMENTARY EVIDENCE SHOWING THAT THERE WAS ANY STRUCTURE TO HOW THESE TRANSACTIONS WERE PRICED, NONE AT ALL. THIS IS -- THIS IS A CASE WHERE, IF I WERE GOING TO ANALOGIZE IT TO A PRICE FIXING CASE, WE HAVE THE AGREEMENT AND 10 THEN, ON THE QUESTION OF IMPACT -- I MEAN, THIS -- AND LET ME 11 BACK UP AND SAY THIS ISSUE COMES UP BECAUSE IN THE MODERN 12 CORPORATE WORLD IN THESE PRICE FIXING CASES THERE ARE -- YOU 13 KNOW, INEVITABLY THERE ARE THOUSANDS OF DIFFERENT PRODUCTS THAT 14 ARE INVOLVED BECAUSE THERE ARE HUNDREDS OF DIFFERENT GRADES OF 15 WHATEVER CHEMICAL IT IS, OR THERE MIGHT BE -- I THINK IN THE 16 LCDS CASE, THERE WERE -- AT ANY GIVEN TIME THERE WERE HUNDREDS, 17 IF NOT THOUSANDS, OF DIFFERENT MODELS OF TFTL SCREENS, TFT LCD 18 SCREENS, EACH OF WHICH WAS JUST A LITTLE BIT DIFFERENT IN THE 19 SENSE THAT THE SCREW WAS IN A DIFFERENT PLACE. 20 THE COURT: BUT YOU DON'T HAVE ANY CASE LAW THAT 21 REALLY SAYS THERE'S A SLIDING SCALE OF IMPORTANCE OF 22 STATISTICAL EVIDENCE BASED ON OTHER FORMS OF EVIDENCE, DO YOU? 23 24 25 MR. GLACKIN: I'M NOT AWARE OF A CASE THAT PUTS IT EXACTLY THAT WAY. THE COURT: UM-HUM. UNITED STATES COURT REPORTERS 84 85 1 MR. GLACKIN: BUT I WOULD OFFER THAT IF YOU HAD A 2 PRICE FIXING CASE, LIKE GPUS WHERE ALL YOU HAVE IS THREE 3 CORRELATIONS, YOU'RE LOOKING AT ONE THING. 4 THE COURT: 5 MR. GLACKIN: YEAH. IF YOU HAD A PRICE FIXING CASE WHERE 6 THE DEFENDANTS NOT ONLY DID THE VIOLATION, BUT THEN THEY ALL 7 CAME IN AND ADMITTED THAT THE THOUSANDS OF DIFFERENT PRODUCTS 8 WERE ALL PRICED OFF OF A BELL CURVE, THEN I THINK YOU WOULD BE 9 A LONG WAY TOWARDS PROVING THAT THE UNLAWFUL AGREEMENT THAT 10 AFFECTED THE PRICE OF SOME OF THESE THINGS HAD AN AFFECT ON ALL 11 OF THEM. 12 IT WOULD BE ALMOST AKIN TO SETTING, YOU KNOW, A PRICE 13 FIXING CONSPIRACY WHERE TARGETS WERE SET FOR BENCHMARK PRICES. 14 IF YOU COULD SHOW THEN THAT ALL THE PRICES WERE SET OFF A BELL 15 CURVE BECAUSE THAT'S JUST HOW THE DEFENDANTS DID BUSINESS, I'M 16 NOT ACTUALLY SURE -- I ACTUALLY THINK THAT TO SHOW IMPACT, YOU 17 WOULDN'T NEED TO DO ANYTHING ELSE. 18 19 20 YOU MIGHT NEED TO DO SOMETHING ELSE TO PROVE DAMAGES, WHICH IS A WHOLE DIFFERENT ISSUE. BUT TO SHOW IMPACT, IF YOU SHOWED, IN A PRICE FIXING CASE, 21 AN AGREEMENT TO FIX THE TARGET PRICE OF A HIGH VOLUME PRODUCT 22 AND THE DEFENDANTS CAME IN AND ADMITTED THAT THE PRICES OF THE 23 OTHER PRODUCTS WERE SET ON A BELL CURVE OFF THE HIGH VOLUME 24 PRODUCT, IN MY OPINION YOU'VE PROVEN IMPACT RIGHT THEN AND 25 THERE, OR YOU'VE CERTAINLY, IN THE ABSENCE OF ANY CONTRARY UNITED STATES COURT REPORTERS 85 86 1 EVIDENCE, MET YOUR BURDEN OF PRODUCTION. 2 THE COURT: LET'S GO TO AND START THE QUESTIONS ON -- 3 I WAS SAVING THE BEST FOR LAST -- ALL THE STATISTICAL QUESTIONS 4 FOR THE END. 5 LET'S -- 6 MR. VAN NEST: 7 THE COURT: CAN I -- OH, I'M SORRY. IT'S ACTUALLY 3:30. 8 MAYBE WE SHOULD -- DO YOU WANT TO JUST DO A QUICK -- TWO 9 MINUTES, PLEASE. 10 11 MR. VAN NEST: HONOR -- 12 THE COURT: 13 MR. VAN NEST: 14 THE COURT: 15 IN A MINUTE -- 17 MR. GLACKIN: 18 THE COURT: MINUTE. I CAN'T DO MUCH IN A MINUTE. OH, YES, YOU CAN. LET'S GO AHEAD -- I'LL GIVE YOU HALF A GO FOR IT. (LAUGHTER.) 21 MR. VAN NEST: 22 THE COURT: 23 WELL, MAYBE WE SHOULD TAKE A BREAK. MR. VAN NEST: 20 -- FOR LEE-ANNE. -- LET'S TAKE A BREAK. 16 19 I'LL DO WHATEVER YOU WANT, YOUR I CAN DO EVEN MORE IN HALF A MINUTE. I'M FEELING GENEROUS. (LAUGHTER.) 24 MR. GLACKIN: 25 THE COURT: NO IMPACT. GO AHEAD. UNITED STATES COURT REPORTERS 86 87 1 MR. VAN NEST: THE BIG PICTURE, YOUR HONOR, IS THAT 2 IF YOU LOOK AT ALL OF THE STATISTICS, WHAT YOU SEE IS THE 3 OPPOSITE OF A RIGID WAGE STRUCTURE. 4 IS BASED ON PAYING INDIVIDUAL PEOPLE ON A LOT OF DIFFERENT 5 FACTORS BASED ON THEIR PERFORMANCE WHERE THERE IS ENORMOUS 6 VARIABILITY, YEAR TO YEAR, WITHIN THE SAME JOB TITLES 7 EMPLOYEE-TO-EMPLOYEE. 8 VERY DISCRETIONARY. 9 YOU SEE A STRUCTURE WHICH THERE IS NO PATTERN. IT IS -- IT IS THAT IS THE OPPOSITE OF WHAT WOULD BE REQUIRED BASED ON 10 THEIR THEORY, THAT CALLS NOT MADE WOULD HAVE RESONATED THROUGH 11 THE WHOLE CLASS. 12 AND SO WHEN WE GET TO TALKING IN DETAIL -- AND I'VE ONLY 13 GOT A FEW PAGES OF THEM TO SHOW YOUR HONOR, JUST THE 14 HIGHLIGHTS -- YOU WILL SEE THAT WHETHER YOU LOOK AT IT WITHIN A 15 CLASS -- EXCUSE ME -- WITHIN A TITLE OR ACROSS TITLES OR ACROSS 16 COMPANIES, THERE IS NO RIGID STRUCTURE THAT COULD SUPPORT THE 17 THEORY THAT THEY ARE ADVANCING. 18 AND I WOULD SAY WITH RESPECT TO YOUR HONOR'S QUESTION ON 19 DOCUMENTARY EVIDENCE, THERE ISN'T ANY DOCUMENTARY EVIDENCE OF 20 IMPACT. 21 THAT'S THE IMPORTANT THING. IN A LOT OF THESE CASES THERE ARE -- THERE'S ACTUAL 22 AGREEMENT BY THE DEFENDANTS THAT THERE WAS A DO NOT HIRE 23 AGREEMENT IN PLACE, OR SOME SUCH THING. 24 CASE WHERE THERE THE COURT FAILED TO CERTIFY A MUCH SMALLER 25 CLASS, EVEN THOUGH LIABILITY WAS VIRTUALLY ADMITTED, BECAUSE THAT WAS THE WEISFELDT UNITED STATES COURT REPORTERS 87 88 1 THE COURT SAID "YOU HAVEN'T PROVEN THAT THERE WAS IMPACT TO THE 2 CLASS ON A CLASS-WIDE BASIS." 3 AND THE SAME IS TRUE HERE. ALL THE EVIDENCE YOUR HONOR IS 4 CITING, AND WE DON'T NEED TO DEBATE IT TODAY, ALL THAT GOES TO 5 WHETHER OR NOT THERE WERE AGREEMENTS, WHAT THE INTENT OF THEM 6 WAS, HOW WIDESPREAD THEY WERE, AND SO ON. 7 NONE OF IT GOES TO IMPACT. THERE AREN'T DOCUMENTS THAT 8 SHOW OR ANY DISCUSSION THAT SHOWS ANYBODY WAS IMPACTED. 9 WHAT'S LACKING. 10 11 THAT'S WHY THIS CASE IS GOING TO TURN ON STATISTICS AND STATISTICAL PROOF, AND THAT'S WHY -- 12 13 THAT'S THE COURT: BUT YOU'RE ASKING THEM TO PROVE A NEGATIVE. 14 MR. GLACKIN: 15 MR. VAN NEST: 16 THE COURT: THIS IS THE PROBLEM -NO. BECAUSE THEY HAD THE AGREEMENT, BECAUSE 17 THERE WAS NO COLD CALLING, BECAUSE PEOPLE COULD NOT SOLICIT 18 EACH OTHER'S EMPLOYEES. 19 MR. VAN NEST: 20 THE COURT: 21 MR. VAN NEST: I'M NOT, YOUR HONOR. WHAT'S THE -THEY SAID THEY COULD PROVE IT BECAUSE 22 THEIR WHOLE CASE THEORY WAS "WE'RE GOING TO SHOW THAT THERE'S A 23 RIGID JOB PAY STRUCTURE AT ALL OF THE DEFENDANTS, SO THAT IF WE 24 CAN SHOW THAT COLD CALLS WEREN'T MADE AND PEOPLE DIDN'T GET 25 INFORMATION, THAT THAT IMPACT ON THAT EMPLOYEE, OR THAT GROUP UNITED STATES COURT REPORTERS 88 89 1 2 OF EMPLOYEES, WOULD RESONATE THROUGH THE WHOLE FIRM." THAT WAS THE PROMISE THEY MADE. 3 ARGUED ON THE MOTION TO DISMISS. 4 THAT WAS THE THEORY THEY ARGUED LAST TIME. 5 6 7 8 AND YOU SAID, "FINE. IMPACT, PROVE IT. LET'S SEE WHAT THE NUMBERS SHOW." DR. LEAMER ADMITS THAT HE CAN'T SHOW IT. THE COURT: LET'S SAVE THAT FOR AFTER THE BREAK. MR. VAN NEST: 12 THE COURT: UNTIL 3:45. OKAY? 15 THE COURT: THE COURT: 22 THANK YOU, YOUR HONOR. THANK YOU ALL VERY MUCH. OKAY. LET'S GO TO DR. LEAMER'S OPENING EXPERT REPORT. 19 21 LET'S TAKE A BREAK (RECESS FROM 3:34 P.M. UNTIL 3:58 P.M.) 17 20 ALL RIGHT. THANK YOU. MR. VAN NEST: 18 VERY GOOD. OKAY? 14 16 WE ARE GOING TO GET INTO THE WEEDS ON THE STATS. 11 13 IF THAT'S YOUR THEORY OF COMMON THEY'VE COME BACK AND THEY'VE FAILED TO PROVE IT, AND 9 10 THAT WAS THE THEORY THEY MR. GLACKIN: YOU MEAN THE ONE DATED MAY 10TH, OF COURSE? THE COURT: YES, THE ONE DATED IN MAY. WHY DON'T YOU EXPLAIN -- LET'S START WITH EXHIBIT 2. WHY 23 DON'T YOU JUST EXPLAIN WHAT HIS CORRELATION ANALYSIS THEORY IS. 24 WHAT DO THESE DIFFERENT THINGS REPRESENT? 25 MR. GLACKIN: SURE. UNITED STATES COURT REPORTERS 89 90 1 THE COURT: START WITH EXHIBIT 2, APPLE. 2 MR. GLACKIN: EXHIBIT 2, APPLE. IS THERE A REASON 3 YOU DON'T WANT TO START WITH EXHIBIT 1, ADOBE? 4 EXACTLY THE SAME IN TERMS OF WHAT'S THERE AND THE ADOBE ONE HAS 5 SOME HIGHLIGHTING ON IT THAT MIGHT BE HELPFUL. 6 THE COURT: 7 MR. GLACKIN: 8 9 BECAUSE THEY'RE THAT'S FINE. WE CAN START WITH APPLE. IT'S THE SAME CHARTS EITHER WAY. EXHIBIT 1 IS THE OUTPUT OF THE REGRESSION ANALYSIS FOR 10 ADOBE; AND THEN EXHIBIT 2 IS THE OUTPUT OF THE REGRESSION 11 ANALYSIS FOR EVERY OTHER COMPANY. 12 13 THE COURT: WHY DOES IT LOOK DIFFERENT THAN THE APPLE ONE? 14 MR. GLACKIN: 15 THE COURT: 16 SO WE CAN START -- YOU MEAN WHY IS THERE HIGHLIGHTING? NO. IF YOU LOOK UNDER SECTION 1, THE CATEGORIES ARE DIFFERENT. 17 MR. GLACKIN: I THINK -- SO PROBABLY -- WHAT'S 18 DIFFERENT IS THE -- SECTION 1 IS ALL JUST A REPORT OF THE 19 CHARACTERISTICS OF THE TITLE IN TERMS OF HOW MANY EMPLOYEES ARE 20 THERE AND WHAT THE HIRING RATE IS FOR EMPLOYEES IN THAT TITLE. 21 I THINK THAT SOME OF THAT INFORMATION WAS OMITTED FROM 22 EXHIBIT 2 BECAUSE IT'S NOT THAT IMPORTANT AND IT ALLOWED THERE 23 TO BE MORE SPACE BETWEEN THE COEFFICIENTS ON THE REGRESSION 24 OUTPUTS, WHICH ARE ALL THE SAME -- I MEAN, ALL THE SAME 25 COLUMNS. I THINK THAT WAS THE ONLY REASON THAT WAS OMITTED. UNITED STATES COURT REPORTERS 90 91 1 2 3 BUT I COULD WALK THROUGH EITHER ONE AND EXPLAIN WHAT THEY MEAN. SO IN OTHER WORDS, THE ONLY -- THE DIFFERENT -- THE 4 REASON -- IF YOU LOOK AT SECTION 1 OF ADOBE AND COMPARE IT TO 5 SECTION 1 OF APPLE, THEY BOTH SHOW THE YEARS OF DATA FOR THE 6 TITLE, AND WHAT THAT MEANS IS -- THAT'S THE NUMBER OF YEARS FOR 7 WHICH WE HAVE DATA FOR THAT JOB TITLE BECAUSE THAT'S A RELEVANT 8 THING TO KNOW. 9 AND THEN THE NEXT COLUMN IS TOTAL EMPLOYEE YEARS, WHICH 10 TELLS YOU THE NEXT THING YOU NEED TO KNOW, WHICH IS HOW MANY -- 11 WHAT'S THE WEIGHT OF THAT JOB TITLE WITHIN THE DATA? 12 HAVE THE NUMBER OF YEARS. 13 14 15 SO YOU AND THEN YOU HAVE THE NUMBER OF YEARS WORKED BY EMPLOYEES IN THAT JOB TITLE, WHICH IS A RELEVANT THING TO KNOW. THEN THE OTHER COLUMNS IN THE ADOBE CHART ARE ABOUT THE -- 16 THEY'RE SORT OF OTHER WAYS OF -- OTHER DESCRIPTIONS OF THE 17 CHARACTERISTICS OF THE NUMBER OF EMPLOYEES IN THAT TITLE. 18 19 20 21 22 SO AV EMP IS THE AVERAGE NUMBER OF EMPLOYEES IN THAT TITLE AT ANY GIVEN TIME. D-LOG AVERAGE IS THE RATE OF CHANGE OF THE NUMBER OF EMPLOYEES IN THE TITLE. SO, FOR EXAMPLE, IF YOU -- LOOKING AT THE VERY TOP ONE 23 WHERE IT SAYS D-LOG AVERAGE IS .27, THAT MEANS THAT ON AVERAGE, 24 THAT TITLE WAS INCREASING BY 27 PERCENT PER YEAR. 25 AND THEN D-LOG STANDARD DEVIATION IS THE STANDARD DEVIATION UNITED STATES COURT REPORTERS 91 92 1 OF THE RATE OF CHANGE, AND THE BIGGER THAT NUMBER IS, THE MORE 2 FLUCTUATION THERE WAS AROUND THE CHANGE OF HEAD COUNT IN ANY 3 GIVEN YEAR. 4 SO IN OTHER WORDS, IF THE STANDARD DEVIATION WAS 0, THAT 5 WOULD, I THINK, IMPLY THAT THERE WAS A STATIC 27 PERCENT 6 INCREASE IN HEAD COUNT EVERY YEAR. 7 WITH A STANDARD DEVIATION -- 8 THE COURT: 9 MR. GLACKIN: 10 AND WHERE DO YOU GET THAT 27 PERCENT? ADOBE EXHIBIT 1. 11 THE COURT: 12 MR. GLACKIN: 13 IT'S .018 AND THEN IT'S MINUS .027. THE COURT: OH, YOU'RE LOOKING AT THE FIRST PAGE OF IT. 16 MR. GLACKIN: 17 THE COURT: 18 MR. GLACKIN: 19 20 WHAT I'M LOOKING AT IS EXHIBIT 1, WHICH IS ADOBE. 14 15 THAT'S D-LOG AVERAGE .27 ON THE YEAH. OKAY. I SEE. YOU SEE THE .27, THE VERY TOP ENTRY. SO THE .34 TELLS YOU THAT IT WASN'T .27 EVERY YEAR. THE HEAD COUNT -- HOW THE HEAD COUNT MOVED IS NOT SUPER 21 IMPORTANT TO THE ANALYSIS AND THAT'S WHY IT WAS OMITTED FROM 22 THE LARGER REPORT OF REGRESSION RESULTS IN EXHIBIT 2. 23 WHAT YOU REALLY NEED TO KNOW TO UNDERSTAND -- TO INTERPRET 24 THOSE RESULTS, I THINK, IS THE NUMBER OF EMPLOYEE YEARS AND THE 25 NUMBER OF YEARS OF DATA WE HAVE. THOSE ARE THE MOST IMPORTANT UNITED STATES COURT REPORTERS 92 93 1 THINGS TO KNOW. 2 THE COURT: OKAY. 3 MR. GLACKIN: WHAT DOES THE T-STAT SHOW? SO A T-STAT IS A MEASURE OF STATISTICAL 4 SIGNIFICANCE, AND A -- THE BEST WAY TO INTERPRET THEM IS THAT A 5 T-STAT OF 2.0 OR GREATER MEANS THAT THE COEFFICIENT IS 6 STATISTICALLY SIGNIFICANT TO CONVENTIONAL CONFIDENCE LEVELS, 7 WHICH I THINK IN THIS CASE WOULD BE 95 PERCENT LEVELS, OR 5 8 PERCENT LEVELS. 9 THE COURT: SO WHAT IS HIS THEORY? HIS THEORY IS 10 THAT IF HE CAN SHOW THAT THE AVERAGE COMPENSATION FOR A SINGLE 11 JOB TITLE, THAT THE CHANGES IN THAT COMPENSATION ARE CORRELATED 12 TO CHANGES IN THE AVERAGE COMPENSATION FOR THE ENTIRE TECHNICAL 13 CLASS, THAT THAT MEANS THEY'RE RISING AND FALLING TOGETHER? 14 THAT THE THEORY? 15 IS OR WHAT IS IT? MR. GLACKIN: SO IF YOU'LL INDULGE ME, IT MIGHT HELP 16 TO GO BACK TO THE BEGINNING A LITTLE BIT, WHICH IS TO GO BACK 17 TO THE COMMON FACTORS ANALYSIS FROM THE VERY FIRST REPORT. 18 AND THE REASON IT'S IMPORTANT TO GO BACK THERE IS THAT THE 19 DEFENDANTS' MAIN ATTACK ON THIS ANALYSIS HAS BEEN TO SAY THAT 20 DR. LEAMER IGNORED INDIVIDUAL LEVEL DATA AND DIDN'T TAKE INTO 21 ACCOUNT INDIVIDUAL VARIATION WITHIN JOB TITLE AND HOW IMPORTANT 22 THAT IS. 23 AND IT'S ABSOLUTELY NOT TRUE. THE VERY FIRST THING THAT 24 DR. LEAMER DID WAS TO ESTABLISH WHAT -- TO WHAT EXTENT COMMON 25 FACTORS LIKE JOB TITLE, AGE, AND COMPANY EXPLAIN THE UNITED STATES COURT REPORTERS 93 94 1 2 3 COMPENSATION OF INDIVIDUAL EMPLOYEES. AND THIS IS AT THE AREA OF, LIKE, PARAGRAPH 129 IN HIS VERY FIRST REPORT OF OCTOBER 1ST OF 2012. 4 THE COURT: BUT THAT DOESN'T EXPLAIN WHY HE DIDN'T 5 TAKE INDIVIDUAL COMPENSATION HERE, WHY HE AVERAGED IT BY JOB 6 TITLE. 7 MR. GLACKIN: WELL, IT DOES ACTUALLY, BECAUSE WHAT 8 THE -- WHAT THE COMMON FACTORS ANALYSIS SHOWED IS THAT -- AND 9 EVERYBODY AGREES ABOUT THIS AT THIS POINT -- IS THAT THESE 10 COMMON FACTORS EXPLAIN 90-PLUS PERCENT OF AN EMPLOYEE'S 11 COMPENSATION, WHICH IS -- WHICH MEANS THAT IF YOU KNOW THE 12 COMPANY, JOB TITLE, AGE, AND GENDER, I THINK, ARE THE FACTORS 13 OF ANY MEMBER OF THE CLASS, YOU CAN CALCULATE, ON AVERAGE, 14 THEIR COMPENSATION, 94 PERCENT OF THEIR COMPENSATION, OR YOU 15 CAN EXPLAIN 90-PLUS PERCENT OF THEIR COMPENSATION. 16 EXCUSE ME. AND EVERYONE AGREES THAT THAT RESULT IS MAINLY DRIVEN BY 17 TITLE, THAT IT'S ACTUALLY THE TITLE THAT DRIVES 90 PERCENT OF 18 THAT RESULT, EVEN ACCORDING TO DR. MURPHY. 19 SO -- AND OF COURSE WE EXPECT THAT, RIGHT? IF WE HAD A 20 CASE WHERE MOST OF THE EMPLOYEES' COMPENSATION WAS EXPLAINED BY 21 THEIR GENDER, THIS WOULD BE A TITLE 7 LAWSUIT, RIGHT? 22 NOT HOW COMPANIES PAY PEOPLE. 23 THEIR GENDER, OR THEY TRY NOT TO. 24 THEIR AGE TO THE EXTENT IT'S A PROXY FOR TENURE. 25 THAT'S THEY DON'T PAY THEM ACCORDING TO AND THEY DO PAY ACCORDING TO BUT JOB TITLE, EVERYONE AGREES, DRIVES 90 PERCENT PLUS OF UNITED STATES COURT REPORTERS 94 95 1 THE COMPENSATION OF EVERY MEMBER OF THE CLASS, AND DR. MURPHY 2 AGREED WITH THIS. 3 DEPOSITION. 4 HE AGREED TO IT UNDER OATH AT HIS SO THE VERY FIRST THING DR. LEAMER DID IS ESTABLISH THAT 5 THESE EMPLOYEES ARE EMBEDDED IN A SYSTEM THAT PAYS THEM BASED 6 ON THEIR JOB TITLE. 7 AND ALL OF THE VARIATION THE DEFENDANTS ARE TALKING ABOUT 8 IN TOTAL COMPENSATION -- BY THE WAY, THAT COMMON FACTORS 9 ANALYSIS IS A TOTAL COMP ANALYSIS. 10 11 IT'S NOT AN ANALYSIS ONLY OF BASE SALARY. ALL THE VARIATION THAT THE DEFENDANTS ARE SAYING IS SO 12 IMPORTANT IS IN THAT TOP AREA. 13 AREA. 14 BELOW IS DETERMINED BY COMPANY, TENURE, GENDER, AND JOB TITLE, 15 AND 90 PERCENT OF THAT IS DETERMINED BY JOB TITLE. 16 IT'S IN THAT 90 TO 100 PERCENT THAT'S WHERE ALL THE VARIATION IS HAPPENING. 90 AND NOW, THAT DOESN'T EVEN MEAN, BY THE WAY, THAT THE VARIATION 17 PART IS ALL DISCRETIONARY BECAUSE THERE'S OTHER FACTORS WE 18 DON'T KNOW, LIKE PEOPLE'S EDUCATION, WHICH IS NOT IN THE DATA 19 SET, THAT PROBABLY WOULD EXPLAIN EVEN MORE APPROACHING UP TO 20 THAT 100 PERCENT LEVEL. 21 22 SO THE BOTTOM LINE IS, AND THE REASON I'M -THE COURT: SO FROM WHAT I HEAR, WHAT YOU'RE SAYING 23 IS BECAUSE HE FELT THAT THE INDIVIDUAL VARIATIONS WOULD BE 24 MINOR AND WOULD BE EXPLAINABLE BY GENDER, JOB TITLE, AND 25 WHATEVER, HE DIDN'T FEEL LIKE HE NEEDED TO INCORPORATE UNITED STATES COURT REPORTERS 95 96 1 INDIVIDUAL AVERAGES IN THIS CORRELATION ANALYSIS, THAT HE 2 THOUGHT HE COULD JUST AVERAGE IT ACROSS THE WHOLE JOB TITLE? 3 IS THAT WHAT YOU'RE -- LIKE WHAT IS THE BOTTOM LINE OF WHAT 4 YOU'RE SAYING? 5 MR. GLACKIN: THAT IS ALMOST RIGHT, EXCEPT I'D SAY 6 IT'S EVEN A LITTLE STRONGER. 7 THE COURT: 8 MR. GLACKIN: 9 UM-HUM. ONCE YOU KNOW THAT 90 PERCENT OF HOW THE EMPLOYEES ARE PAID IS BASICALLY BASED ON THEIR JOB TITLE, 10 THEN THE QUESTION IS, IS THERE -- AND THIS IS THE QUESTION THAT 11 WE UNDERSTOOD, THE LINK THAT WE UNDERSTOOD THE COURT TO HAVE 12 FOUND MISSING, WHAT IS IT THAT -- IS THERE SOMETHING HOLDING 13 THOSE JOB TITLES TOGETHER? 14 REAL WORLD THE JOB TITLES GO LIKE THIS (INDICATING), AND I AM 15 MOVING MY ARMS UP AND DOWN, OR IS THE TRUTH THAT IN THE REAL 16 WORLD THE JOB TITLES MOVE TOGETHER AND ARE CORRELATED? RIGHT? IS THE TRUTH THAT IN THE 17 BECAUSE IF YOU SHOW THAT 90 PERCENT OF THE EMPLOYEE TOTAL 18 COMPENSATION IS DRIVEN BY THEIR JOB TITLE AND YOU SHOW THAT THE 19 JOB TITLES ARE CORRELATED, THEN YOU HAVE SHOWN THAT THERE IS A 20 PAY STRUCTURE IN PLACE THAT WILL TEND TO HAVE -- THAT WILL TEND 21 TO SPREAD THE EFFECTS OF THESE AGREEMENTS EXACTLY THE WAY THAT 22 DR. LEAMER POSITED THEY WOULD AS A MATTER OF ECONOMIC THEORY. 23 24 25 AND THAT IS EXACTLY WHAT WE HAVE SHOWN. THE COURT: WHAT -- YOU KNOW, IN TAB 3 OF WHAT MR. VAN NEST GAVE ME, I GUESS THAT'S PROBABLY FROM THE UNITED STATES COURT REPORTERS 96 97 1 SUPPLEMENTAL REPORT, HE SAYS HE'S WORKING WITH TITLE AVERAGES 2 BECAUSE INDIVIDUAL DATA IS LIKELY TO BE DOMINATED BY FORCES 3 THAT OPERATE AT THE INDIVIDUAL LEVEL. 4 5 WHAT IS THAT? SO THOSE ARE THE FACTORS THAT YOU'RE TALKING ABOUT RIGHT NOW? 6 MR. GLACKIN: 7 THE COURT: 8 9 10 11 WELL, THE -- OR WHAT? WHAT'S BEING REFERRED TO HERE? SIMILARLY WHEN HE SAYS IN HIS REPLY REPORT THAT AVERAGING ACROSS THE INDIVIDUALS AND ANY TITLE CAN REDUCE THE INDIVIDUAL IDIOSYNCRATIC EFFECTS, WHAT'S HE REFERRING TO? MR. GLACKIN: WELL, WHAT HE'S REFERRING TO IS THAT IF 12 YOU -- AND THIS IS THE SAME THING THAT DR. MURPHY, THE SAME 13 EXPLANATION DR. MURPHY GAVE FOR USING THE ACS DATA SET -- 14 EXCUSE ME -- AVERAGING, AGGREGATING AND AVERAGING THE DATA IN 15 THE ACS DATA SET, WHICH IS IF YOU WANT TO DETECT WHETHER OR NOT 16 THERE IS A STRUCTURE IN WHICH THESE JOB TITLES ARE EMBEDDED, 17 YOU HAVE TO LOOK AT THE AVERAGES, THE AVERAGE COMPENSATION 18 WITHIN THE JOB TITLE. 19 20 21 22 AND WE'VE ESTABLISHED THAT THAT'S THE APPROPRIATE LEVEL OF AGGREGATION IN A NUMBER OF WAYS. FIRST OF ALL, WE'VE SHOWN THAT 90 PERCENT OF THE EMPLOYEES' COMPENSATION IS DRIVEN BY JOB TITLE. 23 SECOND OF ALL -- 24 THE COURT: 25 MR. VAN NEST: DO YOU AGREE WITH THAT? I THINK -- I DON'T KNOW IF IT'S 90 UNITED STATES COURT REPORTERS 97 98 1 PERCENT, YOUR HONOR. I DISAGREE WITH THE SIGNIFICANCE OF IT, 2 BUT I THINK THAT JOB TITLE DOES EXPLAIN A LOT OF COMPENSATION. 3 BUT THE JOB TITLE RANGES ARE HUGE AND THEY INCLUDE SALARY, 4 BONUS, AND EQUITY, WHICH IS WHY DR. LEAMER HAD TO AVERAGE TO 5 GET EVEN THE RESULTS HE DID. 6 THE INDIVIDUAL FORCES HE'S TALKING ABOUT THAT DOMINATE ARE 7 THINGS LIKE HOW WELL DID THE INDIVIDUAL PERFORM? 8 REALLY IMPORTANT UNIT? 9 COMPANY DOING THAT YEAR? 10 11 WAS HE IN A HOW -- YOU KNOW, HOW WELL IS THE FOUR FACTORS THAT APPLY TO THE INDIVIDUAL. AND THOSE DOMINATE, AND THEY DOMINATE BECAUSE IN 12 SILICON VALLEY, PEOPLE ARE PAID BASED ON PERFORMANCE AND THERE 13 IS NO WRITTEN -- YOU KNOW, THERE'S NO RIGID STRUCTURE. 14 THE BANDS ARE -- 15 16 THE COURT: SOME OF BUT CAN YOU CONTROL FOR PERFORMANCE AND STILL HAVE THE COMPENSATION MOVING TOGETHER? 17 MR. VAN NEST: 18 THE COURT: 19 MR. VAN NEST: COULD YOU? YEAH. I'M NOT SURE, BECAUSE CERTAINLY THE 20 RAW DATA HERE SHOWS THAT THE COMPENSATION NEVER MOVES TOGETHER 21 FOR ANY TITLE FOR ANY OF THESE COMPANIES. 22 GET TO IN MY DATA, YOU KNOW, THE RAW DATA IN A MINUTE. 23 THAT'S WHAT WE'LL AND WHAT HE'S SAYING HERE, DR. LEAMER, IS "IF I HAD TO LOOK 24 AT INDIVIDUAL DATA, IT WOULD BE DOMINATED BY INDIVIDUAL 25 FACTORS." UNITED STATES COURT REPORTERS 98 99 1 AND THIS IS WHAT GRADY AND ALSUP BOTH SAID, TOO, IS THAT -- 2 3 THE COURT: FACTORS, THE IDIOSYNCRATIC EFFECTS? 4 5 BUT WHAT DID HE DEFINE AS THE INDIVIDUAL MR. VAN NEST: THE COURT: 7 MR. GLACKIN: 9 10 THINGS THAT OPERATE ON THE INDIVIDUAL LEVEL, LIKE PERFORMANCE OF THE INDIVIDUAL. 6 8 WHAT WAS HE REFERRING TO? DO YOU AGREE WITH THAT, MR. GLACKIN? NO, I DON'T AGREE THAT THAT'S THE ONLY FACTOR. THE COURT: BUT YOU AGREE THAT IT IS, THE PAID FOR PERFORMANCE? 11 MR. GLACKIN: 12 THE COURT: 13 MR. GLACKIN: YES. OKAY. I AGREE -WHAT ELSE? WHAT ELSE? ANOTHER FACTOR WOULD BE EDUCATION, 14 WHICH WE DON'T HAVE -- WHICH WE CAN'T USE AS A VARIABLE BECAUSE 15 IT WASN'T CONSISTENTLY RECORDED IN THE DATA, AND WE WOULD HAVE 16 LOVED TO DO THAT BECAUSE I THINK THEN WE WOULD BE ABLE TO 17 EXPLAIN EVEN MORE. 18 BUT THAT'S ONE. AND THEN ANOTHER IMPORTANT ONE IS TENURE, OR WE'VE INCLUDED 19 THE VARIABLE OF AGE, BUT THE FACTOR IS TENURE. 20 LONGER IN THE COMPANY ARE GOING TO -- AND MORE EXPERIENCED ARE 21 GOING TO GET PAID MORE THAN PEOPLE WHO ARE NEW, AND THAT'S JUST 22 A FACT OF LIFE. 23 PEOPLE WHO ARE AND SO IF YOU'RE TRYING TO ESTABLISH, OR DETERMINE I SHOULD 24 SAY, WHETHER OR NOT THERE'S A STRUCTURE HOLDING TOGETHER THESE 25 JOB TITLES, IT'S APPROPRIATE TO AVERAGE THE INDIVIDUAL DATA TO UNITED STATES COURT REPORTERS 99 100 1 2 REDUCE THE EFFECT OF THOSE FACTORS. AND THIS IS EXACTLY THE SAME APPROACH THAT DR. MURPHY TOOK 3 WITH RESPECT TO THE ACS DATA SET, AND HE EXPLAINED IT IN 4 EXACTLY THE SAME WORDS ACTUALLY. 5 MR. VAN NEST: 6 THE COURT: SO -- WELL, DOES -- WOULD DR. LEAMER AGREE THAT 7 THERE ARE SUBSTANTIAL VARIATIONS IN COMPENSATION WITHIN A JOB 8 TITLE? 9 MR. GLACKIN: I THINK HE'D CERTAINLY AGREE THAT 10 SOMETIMES THERE ARE, THAT THERE COULD BE. 11 THINK WE'RE RULING THAT OUT AS A POSSIBILITY. 12 IT DEPENDS WHAT YOU MEAN BY "SUBSTANTIAL." 13 14 15 I MEAN, I DON'T I MEAN, I THINK BUT THE -- YOU KNOW, LOOK, THE DIFFERENCES IN PAY LEVEL, I MEAN, THEY ARE WHAT THEY ARE. AND, YOU KNOW, THE DEFENDANTS HAVE NOT DONE AN 16 EMPLOYEE-BY-EMPLOYEE CORRELATION ANALYSIS TO SHOW THAT THE PAY 17 OF THE EMPLOYEES IS NOT CORRELATED TOGETHER. 18 TO DO THAT, YOU WOULD HAVE TO CREATE A MATRIX THAT WAS 19 60,000 -- OR FOR THE BIGGEST EMPLOYER, INTEL, YOU'D HAVE TO 20 CREATE A MATRIX THAT WAS 36,000 BY 36,000 ACROSS. 21 BUT IF YOU DID THAT, THE COMMON FACTORS ANALYSIS TELLS YOU 22 WHAT YOU WOULD SEE, WHICH IS THAT EMPLOYEES IN THE SAME JOB 23 TITLE, YOU KNOW, DO TEND TO HANG TOGETHER BECAUSE THEIR 24 COMPENSATION IS PRINCIPALLY DRIVEN BY JOB TITLE. 25 UNDISPUTED FACT AT THIS POINT, AS I UNDERSTAND IT, THAT JOB UNITED STATES COURT REPORTERS IT'S JUST AN 100 101 1 TITLE IS THE MAJOR DETERMINING FACTOR IN COMPENSATION. 2 HENCE THE INQUIRY THAT WE TURNED TO, WHICH IS, DOES THIS 3 STRUCTURE EXIST? 4 AND SO AND WE UNDERSTOOD THE CRITICISMS OF THE DEFENDANTS LAST 5 TIME TO BE THAT WE HAD NOT SHOWN THAT THIS CORRELATION HELD 6 OVER TIME, AND WE HAD NOT SHOWN THAT THE -- WE HAD NOT SHOWN 7 COMPREHENSIVELY THE CORRELATION OF THE JOB TITLES BECAUSE THE 8 CO-MOVEMENT CHARTS WERE SELECTIVE. 9 10 11 SO WE SET ABOUT TO ANSWER THOSE CRITICISMS, IN ADDITIONAL TO THE OVERBREADTH CONCERN I WOULD SAY. MR. VAN NEST: SO, YOUR HONOR, IT IS -- IT IS 12 DEFINITELY AGREED BY EVERYONE THAT PERFORMANCE IS A HUGE 13 FACTOR; AND IT IS NOT AGREED, CERTAINLY NOT BY US, AND I DON'T 14 THINK DR. LEAMER DISPUTES THIS, THAT THERE IS ENORMOUS 15 VARIATION IN PAY WITHIN EACH JOB TITLE. 16 THAT'S WHAT WE'RE SHOWING IN TABS 4 AND 5. IT'S NOT THAT 17 COMPLICATED, EITHER. WHAT WE SHOW HERE IN TAB 4 IS -- AND THIS 18 IS IN DR. MURPHY, EXHIBIT 1 -- THAT IF YOU PICK A TITLE, LIKE 19 ARCHITECT AT INTUIT, AND YOU PLOT THE PEOPLE IN THAT CATEGORY, 20 RIGHT THERE ON TAB 4 -- 21 THE COURT: 22 MR. VAN NEST: 23 THE COURT: 24 25 WELL, LET ME ASK YOU A QUESTION. -- YOU SEE HUGE VARIATION UP AND DOWN. I HEAR THAT. BUT YOU ALSO SEE THAT WITH GOOGLE AFTER THE BIG BANG WHERE THEY GAVE ACROSS THE BOARD 10 PERCENT INCREASE TO ALL EMPLOYEES UNITED STATES COURT REPORTERS 101 102 1 AND YOU STILL SEE THAT LEVEL OF VARIATION. 2 MR. VAN NEST: 3 THE COURT: 4 MR. VAN NEST: 5 THE COURT: THAT'S RIGHT. SO LET ME ASK -THERE'S AN EXPLANATION FOR THAT, TOO. -- WHY IS THAT? WHY ARE SOME PEOPLE'S 6 SALARIES GOING DOWN WHEN THE ENTIRE WORK FORCE IS GETTING A 10 7 PERCENT SALARY INCREASE? 8 MR. VAN NEST: THEY DIDN'T GET A 10 PERCENT SALARY 9 INCREASE WITH BIG BANG, YOUR HONOR. SO WHAT THEY GOT WAS A 10 CHANGE IN THE FORM OF COMPENSATION. PEOPLE GOT A BUMP IN THEIR 11 BASE PAY, BUT NOT NECESSARILY IN THEIR TOTAL COMP. 12 13 14 NOT EVERYBODY GOT AN INCREASE, BY THE WAY, AS DR. LEAMER'S TABLE SHOWS. WHAT HAPPENED WITH BIG BANG, BY THE WAY, IS NOT AN EXAMPLE 15 OF RIPPLE. 16 CHANGE A FEW, THEN EVERYBODY GETS CHANGED BECAUSE THE JOB 17 STRUCTURES ARE RIGID. 18 IT'S NOT AN EXAMPLE OF RIPPLE. RIPPLE -- OR EXCUSE ME. RIPPLE IS IF I BIG BANG WAS A VERY UNIQUE, AS 19 DR. LEAMER PUT IT, SPECIFIC RESPONSE TO ONE SET OF FACTS, WHICH 20 WAS ENORMOUS HIRING BY FACEBOOK OF GOOGLE EMPLOYEES, AND IT IS 21 AN EXTERNAL FACTOR. 22 EVERYTHING. IT'S A COMPANY-WIDE DECISION TO MOVE 23 IT'S NOT AN EXAMPLE OF DR. LEAMER'S THEORY. 24 IN BIG BANG, BY THE WAY, TOTAL COMP DID NOT GO UP ANY MORE 25 THAT YEAR THAN IN ANY OTHER YEAR AT GOOGLE, BECAUSE WHAT THEY UNITED STATES COURT REPORTERS 102 103 1 DID WAS THEY SAID, "WE'RE GOING TO PAY MORE IN BASE PAY, BUT 2 NOT AS MUCH IN BONUS AND EQUITY." 3 IT WAS A CHANGE IN THE MIX. GOOGLE EMPLOYEES WERE 4 OBJECTING TO A MIX OF PAY IN WHICH EQUITY WAS HEAVILY WEIGHED 5 BECAUSE THEY DIDN'T VALUE EQUITY AS HIGH, AS HIGHLY, AND SO 6 IT -- IT WAS A SHIFT IN THE FORM OF PAYMENT, NOT NECESSARILY 7 THE TOTAL. 8 9 AND AS YOU LOOK AT CHARTS LIKE THE CHART I'M SHOWING HERE IN TAB 4, YOUR HONOR, THE KEY POINT IS THAT PAY IS MOVING IN 10 EACH YEAR FOR SOME EMPLOYEES WITHIN THE SAME TITLE UP A LITTLE, 11 SOME DOWN A LITTLE, SOME UP A LOT, A FEW DOWN A LOT. 12 AND IF YOU LOOK AT HOW PEOPLE MOVED AGAINST THE AVERAGE, IN 13 MANY OF THESE YEARS, MORE THAN HALF THE PEOPLE IN A GIVEN TITLE 14 MOVE IN A DIFFERENT DIRECTION THAN THE AVERAGE. 15 AND WHAT WE'RE SAYING NOW -- 16 THE COURT: 17 MR. VAN NEST: 18 THE COURT: 19 20 21 OKAY. I'M SORRY. LET ME INTERRUPT YOU. YES. MY QUESTION WAS HOW TO EXPLAIN THE SALARY FALLS DURING THE BIG BANG YEAR. SO LET ME ASK THAT TO MR. GLACKIN. MR. GLACKIN: SURE. I MEAN, I -- SO THE -- WE'VE 22 NEVER DISPUTED -- WE'VE NEVER SAID THAT THE PLAINTIFF -- THAT 23 THE DEFENDANTS PAY ALL THEIR EMPLOYEES THE SAME OR THAT THEY 24 PAY THEM IN LOCKSTEP. 25 VARIATION. WE NEVER SAID THAT, THAT THERE'S NO THERE IS ABSOLUTELY VARIATION IN HOW THEY PAY THEIR UNITED STATES COURT REPORTERS 103 104 1 2 EMPLOYEES. BUT THE POINT I THINK -- I KNOW THE CHART YOU'RE THINKING 3 OF IN DR. LEAMER'S REPLY REPORT. WHAT YOU LEARN FROM THAT -- 4 SO YOU WANT -- THE ANSWER TO YOUR QUESTION IS WHY WOULD 5 SOMEBODY'S TOTAL COMP GO DOWN? 6 2010, THEY WERE -- PERHAPS THEY GOT A HIGHER, A HIGHER AMOUNT 7 OF TOTAL COMP BECAUSE THEY HAD A GOOD YEAR OR THEY GOT A BONUS. 8 I MEAN, THERE CERTAINLY CAN BE VARIABILITY IN PAY, AND SO IT 9 MIGHT BE THAT WHATEVER THEY GOT IN 2010, DESPITE THE BIG BANG, THE ANSWER MIGHT BE THAT IN 10 EXCEEDED WHAT THEY GOT IN 2011, BUT THEIR BASE SALARY, FROM 11 WHICH A LOT OF OTHER THINGS FLOW AT THESE COMPANIES, WAS 12 INCREASED BY 10 PERCENT IN 2011. 13 AND THAT'S -- THE POINT OF THAT CHART IS TO ILLUSTRATE WHY 14 IT IS MISLEADING TO LOOK AT THE INDIVIDUAL LEVEL DATA, BECAUSE 15 I COMPLETELY DISAGREE WITH MR. VAN NEST. 16 KIND OF PREEMPTIVE RESPONSE THAT IT IS OUR POSITION WOULD HAVE 17 OCCURRED HAD THESE AGREEMENTS NOT BEEN ENTERED INTO. 18 NOT HAVE BEEN 10 PERCENT EVERY YEAR, BUT IT WAS THESE KINDS OF 19 PREEMPTIVE RESPONSES THAT WE SAY WERE PRECLUDED BY THE 20 AGREEMENTS. 21 AND LET ME SAY ONE OTHER THING. THIS IS EXACTLY THE IT MIGHT I MEAN, WHEN MR. VAN NEST 22 SAYS THAT GOOGLE JUST SORT OF WASHED IT ALL OUT AND DIDN'T GIVE 23 THEIR EMPLOYEES ANY MONEY, GOOGLE TESTIFIED IN THIS CASE, AND I 24 WOULD HAVE TO GET THE CITE OUT OF THE BRIEFS, THAT THE BIG BANG 25 COST THEM $500 MILLION. SO SOMEHOW NOTWITHSTANDING THAT THEY UNITED STATES COURT REPORTERS 104 105 1 SMOOTHED EVERYTHING OUT AND IT DIDN'T REALLY HAVE ANY IMPACT, 2 IT COST THEM $500 MILLION. 3 4 5 SO I JUST DON'T AGREE WITH THAT AS A FACTUAL ASSERTION THAT THIS WAS A NON-EVENT FOR THE EMPLOYEES OF GOOGLE. THE COURT: SO LET ME ASK, WHAT IS YOUR BEST EVIDENCE 6 THAT COMPENSATION FOR EMPLOYEES MOVES TOGETHER WITHIN THE SAME 7 JOB TITLE? WHAT'S THE BEST EVIDENCE THAT YOU HAVE ON THAT? 8 MR. GLACKIN: 9 THE COURT: 10 THE BEST -- WITHIN THE JOB TITLE -- UM-HUM. MR. GLACKIN: -- THE BEST ANALYSIS WE HAVE IS THE 11 COMMON FACTORS ANALYSIS WHICH SHOWS THAT IT IS THE TITLE ITSELF 12 THAT DETERMINES 90 PERCENT, APPROXIMATELY, OF THE INDIVIDUAL 13 EMPLOYEE'S SALARY. 14 AND I JUST WANT TO STRESS AGAIN, THAT ANALYSIS WAS RUN ON 15 AN EMPLOYEE-BY-EMPLOYEE BASIS. 16 WE ASKED, WHAT PERCENT OF EACH EMPLOYEE'S COMPENSATION CAN YOU 17 EXPLAIN WITH THESE COMMON FACTORS? 18 KNOW, APPROXIMATELY 90 PERCENT IS EXPLAINED BY JOB TITLE. 19 IT WAS NOT AVERAGED. IT WAS -- AND THE ANSWER IS, YOU AND THAT IS THE EVIDENCE -- IT IS THAT EVIDENCE, PLUS THE 20 HUGE DOCUMENTARY RECORD, THAT THE DEFENDANTS OPERATE A 21 TITLE-BASED PAY SYSTEM. 22 SERIOUS DISPUTE AT THIS POINT THAT THE DEFENDANTS OPERATE A 23 TITLE-BASED -- THAT EACH OF THEM OPERATES A TITLE-BASED 24 COMPENSATION SYSTEM. 25 AGAIN, I CAN'T IMAGINE THAT THERE IS THE -- IT IS THOSE TWO FACTS THAT TELL US THAT JOB TITLE IS UNITED STATES COURT REPORTERS 105 106 1 THE RIGHT PLACE TO LOOK FOR THE EXISTENCE OF A STRUCTURE AND 2 THE RIGHT PLACE TO ASK THE QUESTION OF WHETHER OR NOT 3 COMPENSATION IS MOVING TOGETHER. 4 THE COURT: BUT YOU WOULD CONCEDE THAT AVERAGING IT 5 BY TITLE, AS DR. LEAMER DID, DOES MASK SOME OF THE INDIVIDUAL 6 VARIATIONS -- 7 MR. GLACKIN: 8 THE COURT: 9 MR. GLACKIN: THAT'S THE POINT -- -- THAT WOULD HAPPEN WITHIN A TITLE? I ABSOLUTELY AGREE. I CONCEDE THAT AND 10 I AGREE WITH IT. 11 MATTER OF GOOD STATISTICS, FOR THE VERY REASONS GIVEN BY 12 DR. MURPHY WHEN HE EXPLAINED DOING THIS WITH RESPECT TO THE ACS 13 DATA. 14 AND IN FACT, IT IS NECESSARY TO DO IT, AS A LET ME -- AGAIN, TO TALK ABOUT AVERAGING AND GPUS FOR A 15 MINUTE, GPUS DOES NOT STAND FOR THE PROPOSITION THAT ONE MAY 16 NEVER AVERAGE. 17 AVERAGING IS FUNDAMENTAL TO MOST STATISTICAL INQUIRIES. 18 YOU HAVE TO AVERAGE TO DO CORRELATION ANALYSIS. AND DR. MURPHY TESTIFIED THAT HE AVERAGES DATA ALL THE 19 TIME. HE SAID SOMETIMES HE DOESN'T, SOMETIMES HE DOESN'T USE 20 AGGREGATE OR AVERAGE DATA, BUT A LOT OF TIMES HE DOES. 21 CONCEDED, AVERAGING IS A BASIC, USEFUL STOOL IN STATISTICS. AND HE 22 WHAT HAPPENED IN GPUS, AS I SAID, AND YOU CAN PULL THE 23 REPORTS OFF ECF, DR. TEECE, I THINK, DID THREE CORRELATION 24 ANALYSES. 25 PURCHASERS OF THE LITTLE -- ALL THE LITTLE GUYS AND ALL THE BIG HE ASKED WHETHER YOU COULD CORRELATE ALL THE UNITED STATES COURT REPORTERS 106 107 1 GUYS AND WHETHER THOSE THINGS MOVED TOGETHER IN TIME, AND HE 2 MASHED TOGETHER ALL THE PRODUCTS, ALL OF THE DISTRIBUTION 3 CHANNELS, ALL OF THE DIFFERENT OEMS INTO BIG BLOCKS. 4 5 6 WE HAVE -- YOU CAN SEE HIS REPORT OF THE CORRELATION RESULTS. IT'S A SINGLE TABLE WITH THREE ROWS. WE HAVE DONE -- WE HAVE DONE THE CORRELATION ANALYSIS ON 7 THE 2400 JOB TITLES. 8 ENOUGH DATA. 9 10 WE HAVE -- WHERE POSSIBLE, WHERE WE HAVE WE HAVEN'T DONE IT FOR ALL 2400, TO BE CLEAR. WE HAVE EXPANDED THIS ANALYSIS TO INCLUDE ALL 2400 TITLES IN AN ATTEMPT -- 11 THE COURT: EVERYONE KEEPS SAYING 2400 AND I THOUGHT 12 THE ORIGINAL NUMBER WAS A LITTLE HIGHER THAN THAT. 13 DIFFERENCE BECAUSE INTUIT, LUCASFILM, AND PIXAR ARE GONE? 14 MR. GLACKIN: 15 DIFFERENCE. 16 2350-ISH. 17 18 BUT I DON'T HAVE -I THOUGHT IT WAS 2536 IS WHAT I READ FROM ONE OF THE EARLIER -- IT'S 2400 NOW? MR. GLACKIN: I THINK WE'RE USING THAT NUMBER LOOSELY. 21 THE COURT: 22 MR. GLACKIN: 23 THE COURT: 24 MR. VAN NEST: 25 NO, I DON'T THINK THAT MAKES ANY AND I THINK -- I WANT TO SAY THE NUMBER IS THE COURT: 19 20 IS THE OKAY. I WOULD GO WITH WHAT'S WRITTEN DOWN. OKAY. 2400 IS, IF NOT THE PRECISE NUMBER, YOUR HONOR, VERY CLOSE. UNITED STATES COURT REPORTERS 107 108 1 THE COURT: 2 MR. VAN NEST: 3 VERY CLOSE. MR. GLACKIN: 5 THE COURT: 8 THE COURT: 9 MR. VAN NEST: THE COURT: 11 MR. VAN NEST: AND THAT'S IN YOUR -- WE HAVE IT BEHIND TAB 6, YOUR HONOR. BEHIND TAB 6. AND IF YOU'D LIKE ME TO EXPLAIN THAT, I CAN. 13 THE COURT: LET ME ASK, HOW DO THE PLAINTIFFS RESPOND TO THIS? 15 MR. GLACKIN: 16 THE COURT: SURE. SO -- DOESN'T THIS UNDERMINE YOUR CORRELATION THEORY? 18 MR. GLACKIN: 19 THE COURT: 20 MR. GLACKIN: 21 WHICH ONE, YOUR HONOR? EXHIBITS 7 AND 8. 10 17 LET'S GO TO THE MURPHY EXHIBITS 7 AND 8. MR. VAN NEST: 14 YEAH, THERE'S A LOT OF TITLES. OKAY. 7 12 AND THERE'S NO DISPUTE ABOUT THAT. 4 6 RIGHT. NOT AT ALL. WHY NOT? THERE'S TWO REASONS THAT THESE CHARTS ARE MISLEADING. 22 YOU HAVE TO REMEMBER THAT THE THING WE'RE ASKING IS, IS 23 THERE A RELATIONSHIP BETWEEN THE TITLES OVER TIME, OR IS THERE 24 A RELATIONSHIP BETWEEN THE TITLES AND AVERAGE -- TECHNICALLY 25 WHAT WE'VE MEASURED IS A RELATIONSHIP BETWEEN THE TITLES AND UNITED STATES COURT REPORTERS 108 109 1 ALL THE OTHER TITLES AT THE SAME COMPANY. 2 RELATIONSHIP THERE, A POSITIVE RELATIONSHIP OVER TIME? 3 4 IS THERE A THE QUESTION ISN'T, DO THEY ALL MOVE TOGETHER AT EXACTLY THE SAME TIME? 5 THE QUESTION IS, IS THAT RELATION POSITIVE OVER TIME? 6 AND SO THAT PROPOSITION THAT THE RELATIONSHIP IS POSITIVE 7 OVER TIME IS COMPLETELY CONSISTENT WITH THERE SOMETIMES BEING 8 VARIATION AND WITH THEM SOMETIMES GOING IN DIFFERENT 9 DIRECTIONS. 10 BUT WHAT IT TELLS YOU IS, AND THIS WAS EXACTLY THE 11 QUESTION THAT WE UNDERSTOOD TO HAVE BEEN POSED, WHAT IT TELLS 12 YOU IS THAT OVER TIME, THE RELATIONSHIP IS POSITIVE AND THAT 13 THEY WILL TEND -- THEY ARE MOVING IN THE SAME DIRECTION 14 TOGETHER. 15 THE REASON THAT -- SO THAT'S WHY IT'S MISLEADING WITH 16 RESPECT TO THE FIRST CHART TO FOCUS ON -- I MEAN, CERTAINLY 17 THERE IS VARIATION. 18 CHART AND SIMPLY SAY, OH, YOU KNOW, THEY DIDN'T ALL MOVE THE 19 SAME WAY AT THE SAME TIME, HENCE, THERE'S NO STRUCTURE, BECAUSE 20 OVER TIME THERE IS A STRUCTURE. 21 BUT IT'S MISLEADING TO LOOK AT THE FIRST WITH RESPECT TO THE SECOND CHART, WHAT'S COMPLETELY 22 MISLEADING ABOUT THAT CHART IS THAT THOSE, THOSE DOTS ARE NOT 23 NECESSARILY THE SAME, IN THE SAME POSITION EVERY YEAR. 24 WHAT YOU'RE SEEING HERE IS -- WHAT THERE ARE -- WHAT THIS IS 25 SHOWING IS THAT IN 2002, ALL OF THE -- FOR EXAMPLE, AT ADOBE UNITED STATES COURT REPORTERS I MEAN, 109 110 1 THE JOB TOTAL AVERAGE COMPENSATION WENT DOWN AND IT WENT DOWN 2 BY DIFFERENT AMOUNTS FOR DIFFERENT TITLES, AND THEN YOU SEE THE 3 NEXT YEAR IT WENT UP FOR MOST TITLES, AND FOR SOME TITLES IT 4 WENT DOWN. 5 6 BUT IT DOESN'T -- AND THEN YOU SEE THAT IT'S -- ACTUALLY YOU CAN SEE A PATTERN THERE BEING REPEATED OVER TIME. 7 BUT THE BOTTOM DOT IS NOT ALWAYS THE BOTTOM DOT, RIGHT? 8 SO IT'S TOTALLY FINE. 9 YEAR, THERE MAY BE A DIVERGENCE. 10 11 I MEAN, WE AGREE THAT IN ANY GIVEN THERE MAY BE VARIABILITY. BUT WHAT THE STATISTICAL ANALYSIS TELLS US IS THAT OVER TIME, THAT VARIABILITY IS TIED TO A POSITIVE STRUCTURE. 12 THE COURT: MR. VAN NEST. 13 MR. VAN NEST: YOUR HONOR, YOU'VE HIT IT RIGHT ON THE 14 HEAD. 15 WITHIN A TITLE, THAT WAS TAB 4 AND 5, AND IT'S CONCEDED NOW 16 THAT THE AVERAGING MASKS THAT. 17 THIS -- WE WERE TALKING A MINUTE AGO ABOUT VARIATION THIS ASKS A DIFFERENT QUESTION. THIS IS BETWEEN TITLES. 18 CAN THEY SHOW THAT THERE'S A RIGID JOB STRUCTURE SO THAT THE 19 TITLES ARE CORRELATED BETWEEN THEMSELVES? 20 THE TOP OF THE PAGE, IN MY TAB, IS WHAT DR. LEAMER SAYS IS 21 HIS BEST CASE. 22 TITLES AT ADOBE, HE'S CHERRY PICKED SIX OF THEM, HE'S SHOWN THE 23 GRAPH AND HE SAYS THIS IS A GREAT CORRELATION BETWEEN TITLES. 24 25 THAT'S HIS BEST CORRELATION. HE'S TAKEN SOME ALL MURPHY DID WAS, AT THE BOTTOM OF THE PAGE, IS HE EXPANDED THE NUMBER OF TITLES WITHIN EACH COMPANY YOU LOOK AT. UNITED STATES COURT REPORTERS 110 111 1 HE LOOKED AT THE 50 MOST POPULATED, THE TITLES WITH THE MOST 2 EMPLOYEES, AND HE'S PLOTTING, YEAR TO YEAR, WHETHER THAT TITLE 3 MOVED UP OR MOVED DOWN. 4 5 AND AS YOUR HONOR CAN SEE, AND THIS HAS BEEN DEMONSTRATED OVER AND OVER AGAIN, THERE'S HUGE VARIATION. 6 EACH COMPANY, YEAR BY YEAR, SOME TITLES MOVE UP A LITTLE, 7 SOME MOVE UP A LOT, SOME MOVE DOWN A LITTLE, SOME MOVE DOWN A 8 LOT. 9 10 AND IT'S NOT THE SAME TITLES. OF ANY OF THIS. 11 THERE IS NO FIXED PATTERN THERE IS ENORMOUS VARIABILITY. AND WHAT EXHIBIT 7 AND EXHIBIT 8 ARE SHOWING RIGHT ON THE 12 HEAD IS THE SECOND PART OF THE EQUATION. 13 VARIATION WITHIN A TITLE. 14 TITLES BECAUSE IT SHOWS THAT WHEN YOU LOOK AT MORE THAN A FEW 15 AND YOU EXPAND IT TO THE TOP 50 FOR EACH COMPANY, YOU SEE, 16 OBVIOUSLY ON THE PAGE, AN ENORMOUS VARIATION UP AND DOWN OF 17 DIFFERENT TITLES YEAR AFTER YEAR AFTER YEAR, WHICH PROVES OUR 18 POINT THAT THERE ISN'T ANY SORT OF A RIGID JOB STRUCTURE WHERE 19 PEOPLE MOVE -- WHERE EVERYTHING -- WHERE A CHANGE IN SOME WOULD 20 AFFECT IN A CHANGE IN ALL, OR A CHANGE IN SOME WOULD PROPAGATE 21 OUT. 22 WE'VE SHOWN HUGE THIS SHOWS HUGE VARIATION ACROSS AND THINK ABOUT IT LOGICALLY. WHY IN THE WORLD WOULD THE 23 FACT THAT A SOFTWARE ENGINEER HERE IN SILICON VALLEY WHO DIDN'T 24 GET A CALL, WHY WOULD THAT AFFECT A MASK DESIGNER IN 25 NEW MEXICO? WHY WOULD THAT AFFECT A SEMICONDUCTOR UNITED STATES COURT REPORTERS 111 112 1 MANUFACTURING PERSON IN ARIZONA? 2 CONSTRUCTION MANAGER, AN ARTIST, A CHEMICAL ENGINEER, AN 3 ELECTRICAL ENGINEER? 4 PROBLEM AND 60,000 EMPLOYEES. 5 WHY WOULD THAT AFFECT A THAT'S THE POINT OF THIS 2400 TITLE IT'S UNPRECEDENTED FOR A REASON. NO COURT ANYWHERE HAS 6 EVER FOUND, IN A CASE LIKE THIS, THAT YOU CAN CERTIFY AND 7 EXPECT TO PROVE COMMON IMPACT OVER A GROUP THIS DISPARATE. 8 9 AND THIS TAB 6, EXHIBIT 7 FROM MURPHY, PROVES THAT THERE IS NO RIGID PAY STRUCTURE, RIGHT? IT IS A STRUCTURE BASED ON 10 PAYING FOR PERFORMANCE WHERE TITLES MOVE IN DIFFERENT 11 DIRECTIONS EACH YEAR AND WHERE INDIVIDUAL EMPLOYEES MOVE IN 12 DIFFERENT DIRECTIONS EACH YEAR. 13 AND THE ONLY WAY LEAMER CAN GET ANYWHERE CLOSE TO WHAT HE 14 GOT IS BY AVERAGING. 15 INDIVIDUAL EMPLOYEE PAY WITHIN A TITLE. 16 BASED ON AVERAGES. 17 HE AVERAGED EVERYTHING. HE AVERAGED HIS REGRESSIONS ARE HIS CORRELATIONS ARE BASED ON AVERAGES. AND WHAT THE CASE LAW SAYS REPEATEDLY IS NOT THAT YOU CAN 18 NEVER AVERAGE. 19 IN ECONOMIC ANALYSIS. 20 THAT'S NOT WHAT WE'RE SAYING. YOU CAN AVERAGE BUT WHEN THE QUESTION IS WHETHER YOU CAN PROVE COMMON 21 IMPACT WHEN WHAT'S INVOLVED ARE LOTS OF INDIVIDUAL PEOPLE AND 22 DECISIONS, AVERAGING THEM TELLS YOU NOTHING BECAUSE THE FACT 23 THAT AN AVERAGE GOES UP OR DOWN DOESN'T TELL YOU WHETHER ALL OR 24 NEARLY ALL PEOPLE WERE AFFECTED. 25 SO OUR POINT WITH TABS 4, 5, 6, AND 7 IS THEY FLUNKED THE UNITED STATES COURT REPORTERS 112 113 1 BASIC TEST THAT YOU GAVE THEM AND NOW THEY'RE WALKING AWAY FROM 2 IT, AND THEY FLUNKED IT SO BAD THAT DR. LEAMER HAS TO ADMIT, 3 WHICH IS IN TAB 1 -- WE ASKED HIM POINT BLANK, "DO YOUR 4 RESULTS, YOUR CORRELATION, YOUR REGRESSION, EVERYTHING YOU DID, 5 DO THEY ENABLE YOU TO CONCLUDE THAT ADOBE'S COMP STRUCTURE WAS 6 SO RIGID THAT RAISES FOR ONE OR A FEW WOULD HAVE NECESSARILY 7 PROPAGATED INTO RAISES FOR ALL?" 8 "NO. 9 AND HE CAN'T CONCLUDE IT BECAUSE THE DATA DOESN'T SUPPORT 10 THE COURT: LET ME ASK MR. GLACKIN, WHAT IS YOUR BEST EVIDENCE THAT COMPENSATION MOVES TOGETHER ACROSS JOB TITLES? 13 14 MR. GLACKIN: WELL, THERE'S -- I -- WHAT'S MY BEST EVIDENCE? 15 THE COURT: 16 MR. GLACKIN: 17 I DIDN'T CONCLUDE THAT." IT. 11 12 I CAN'T CONCLUDE THAT. YES. I HESITATE BECAUSE I FEEL THE RECORD IS SO RICH AND I'M NOT SURE I CAN ACTUALLY PICK A WINNER. 18 THE COURT: UM-HUM. 19 MR. GLACKIN: YOU KNOW, THERE'S THIS -- THERE'S THE 20 RICH DOCUMENTARY RECORD THAT SHOWS THAT THE DEFENDANTS 21 MODULATED THEIR ENTIRE PAY SYSTEMS AT THE JOB TITLE LEVEL AND 22 THAT THEY SET COMPENSATION ON A BELL CURVE IN A NUMBER OF 23 INSTANCES. 24 25 BUT IN ADDITION TO THAT, YOU KNOW -- AND AGAIN I HESITATE BECAUSE WE TOOK THE CRITICISMS VERY SERIOUSLY AND WE DIDN'T UNITED STATES COURT REPORTERS 113 114 1 JUST DO ONE ADDITIONAL STATISTICAL ANALYSIS. WE LOOKED AT THIS 2 FROM FOUR DIFFERENT -- I SHOULD SAY DR. LEAMER STATISTICALLY 3 LOOKED AT IT FROM FOUR DIFFERENT DIRECTIONS. 4 ON THE LEVEL OF CONTEMPORANEOUS CORRELATIONS, WHETHER OR NOT 5 THERE'S A SIMPLE CORRELATION, HE LOOKED AT THAT AT THE JOB 6 TITLE LEVEL, AND HE LOOKED AT IT AT THE ENTIRE COMPANY LEVEL BY 7 COMBINING SMALL TITLES INTO GROUPS. HE LOOKED AT IT 8 THEN HE RAN A MULTIPLE REGRESSION ANALYSIS WHICH ALLOWED 9 THE STRUCTURAL VARIABLES TO COMPETE WITH THE EXTERNAL VARIABLES 10 THAT THE DEFENDANTS SAY ARE SO IMPORTANT, AND THE EXTERNAL 11 VARIABLES LOST. 12 COEFFICIENTS, THE EXTERNAL MARKET FORCE VARIABLES HAD VERY LOW 13 COEFFICIENTS, WHICH CONFIRMS AGAIN WHAT WE KNEW FROM THE COMMON 14 FACTORS ANALYSIS, WHICH IS THAT THE MAJORITY OF WHAT THE 15 EMPLOYEES ARE PAID IS DETERMINED BY JOB TITLE. 16 THE STRUCTURAL VARIABLES HAD VERY HIGH SO HAVING DONE THAT ANALYSIS, IT REALLY IS -- YOU KNOW, 17 HAVING BEEN CRITICIZED FOR ONLY DISPLAYING CHARTS AND NOT 18 LOOKING AT EVERY TITLE IN THE COMPANY, WE HAVE NOW DONE THE 19 ANALYSIS OF LOOKING AT EVERY TITLE IN THE COMPANY, IN THE 20 COMPANIES. 21 THE COMPANIES, AND NOW THE DEFENDANTS ARE CHERRY PICKING THEIR 22 OWN CHARTS AND SAYING IF YOU LOOK AT THESE CHARTS, YOU SEE 23 THINGS MOVING IN A LOT OF DIFFERENT DIRECTIONS, WHICH WAS 24 EXACTLY WHAT WE WERE TAKEN TO TASK FOR THE FIRST TIME AROUND. 25 WE HAVE DONE MULTIPLE ANALYSES OF EVERY TITLE IN THEY HAVEN'T OFFERED A SINGLE -- DR. MURPHY HAS NOT OFFERED UNITED STATES COURT REPORTERS 114 115 1 A SINGLE LEGITIMATE CRITICISM OF THE MULTIPLE REGRESSION 2 ANALYSIS THAT DR. LEAMER HAS DONE. 3 IT IS, FRANKLY, AMAZING TO ME, AFTER THE YEARS THAT I HAVE 4 DONE THIS, THAT WE DO NOT SEE FROM DR. MURPHY A COMPETING 5 REGRESSION IN WHICH HE HAS ADDED A VARIABLE AND BLOWN THIS 6 REGRESSION UP. 7 THE OPENING REPORT. 8 THE FIRST THING THEY DO IS ADD THE S&P 500 TOTAL RETURN INDEX 9 AND SHOW THAT IT BLOWS UP WHATEVER THE PLAINTIFFS' EXPERT IS 10 11 THAT'S EXACTLY WHAT HE DID NUMEROUS TIMES IN IT IS A STANDARD DEFENSE TACTIC. IT IS -- TRYING TO DO. THERE IS NOT ONE SINGLE EXAMPLE OF THAT KIND OF ATTACK IN 12 HERE, AND IT IS BECAUSE THE REGRESSION IS TELLING THE TRUTH. 13 IT'S BECAUSE THE REGRESSION IS RIGHT, THAT THERE IS THIS 14 RELATIONSHIP BETWEEN THE TITLES OVER TIME, NOT THAT THEY HAVE 15 TO MOVE IN LOCKSTEP EVERY YEAR, BUT THERE IS A STRUCTURE THAT 16 BINDS THESE TITLES TOGETHER OVER TIME. 17 IT'S WHAT THE DEFENDANTS' EMPLOYEES SAY, THEIR H.R. 18 EMPLOYEES SAY, IT'S WHAT THE CEOS SAY, IT'S WHAT THE PEOPLE WHO 19 ENTERED INTO THESE AGREEMENTS SAY, AND IT'S WHAT THE DATA SAYS, 20 AND THEY HAVE NOT EVER ATTACKED THAT ANALYSIS. 21 THEIR ONLY RESORT IS TO GO BACK TO THE INDIVIDUAL LEVEL AND 22 SHOW THINGS MOVING IN A LOT OF DIFFERENT DIRECTIONS AND ACCUSE 23 US OF AVERAGING. 24 25 THE COURT: DR. MURPHY'S REPORT. SO LET ME GO TO PARAGRAPH 22 OF IT'S ON PAGE 8. WHY IS THE CORRELATION UNITED STATES COURT REPORTERS 115 116 1 NOT RELEVANT? 2 WHAT IS THE BENEFIT -- MR. VAN NEST: WHAT HE'S SAYING, YOUR HONOR -- AND 3 OBVIOUSLY DR. MURPHY IS HERE IF YOU WANT TO HEAR FROM HIM, AND 4 HE CAN PROBABLY EXPLAIN THIS BETTER THAN I CAN -- BUT THE 5 FUNDAMENTAL POINT IS THAT CORRELATION OF -- THIS CORRELATION 6 STUDY OR TEST IS MEANINGLESS. 7 ALL HE'S SAYING -- ALL LEAMER IS SAYING ON THE CORRELATION 8 IS IF I TAKE THE AVERAGE OF A JOB TITLE AND COMPARE IT TO THE 9 AVERAGE PAY OF CLASS MEMBERS AT THAT COMPANY, I SEE A 10 11 CORRELATION. WELL, OBVIOUSLY BOTH THE TITLES AT THE COMPANY AND ALL THE 12 EMPLOYEES IN THE TECH GROUP AT THE COMPANY, THEY'RE ALL SUBJECT 13 TO THE SAME EXACT EXTERNAL FACTORS, HOW WELL DID THE COMPANY DO 14 THAT YEAR, HOW WELL IS THE ECONOMY DOING, WHAT'S THE JOB 15 MARKET -- 16 THE COURT: 17 MR. VAN NEST: 18 THE COURT: 19 20 BUT WHAT'S THE BENEFIT OF -THERE ISN'T. -- MEASURING THE DEVIATION? WHAT'S THAT BENEFIT? MR. VAN NEST: THERE'S NO -- THERE'S NO BENEFIT IN 21 DETERMINING WHETHER THERE'S A RIGID JOB STRUCTURE. 22 CORRELATION DOESN'T TELL YOU THAT. 23 THE THAT'S WHY DR. LEAMER SAYS "I CAN'T TELL YOU THAT CHANGES 24 TO SOME EMPLOYEES WOULD PROPAGATE." THERE'S NO -- WHAT 25 DR. MURPHY IS SAYING IS CORRELATION, IN THIS CONTEXT WHERE UNITED STATES COURT REPORTERS 116 117 1 YOU'RE COMPARING A TITLE TO THE REST OF THE EMPLOYEES AT THE 2 COMPANY, THAT WILL MOVE TOGETHER WHETHER THE STRUCTURE IS RIGID 3 OR NOT BECAUSE THEY'RE ALL SUBJECT TO THE SAME SET OF FACTORS. 4 AND WHEN YOU LOOK AT EXHIBIT 8, OR FIGURE 8 AND FIGURE 7, 5 HE TESTED THE THEORY. 6 50 TITLES? 7 PATTERN? 8 10 DO THEY ALL SEEM TO -- IS THERE A TIGHT, RIGID ABSOLUTELY NOT. 9 WHAT HAPPENS WHEN YOU LOOK AT THESE TOP THE COURT: THERE'S HUGE VARIATION. WHY ISN'T ALL THIS MERITS ANALYSIS FOR LATER? 11 MR. VAN NEST: BECAUSE COMCAST AND ELLIS TELL US THAT 12 THE STANDARD FOR ESTABLISHING CERTIFIABILITY IN (B)(3) IS 13 EXTREMELY HIGH. 14 YOU ASKED EARLIER ABOUT CASE LAW. COMCAST CITES DUKES AND 15 IT SAYS DUKES APPLIES WITH EVEN MORE FORCE IN (B)(3), AND IF 16 YOU WANT TO CERTIFY A CLASS OF 60,000 PEOPLE WITH 2400 -- 17 THE COURT: 18 EVIDENCE. 19 OKAY. BUT DUKES HAD NO DOCUMENTARY DUKES HAD A SOCIOLOGIST TALKING ABOUT WAL-MART CULTURE. 20 MR. VAN NEST: 21 THE COURT: 22 IT HAD 120 ANECDOTES FROM WOMEN EMPLOYEES. 23 MR. VAN NEST: 24 THE COURT: 25 WELL, LOOK AT -- LOOK AT ELLIS. THEY HAD STATISTICS. THEY DID NOT HAVE THE WEALTH OF DOCUMENTARY EVIDENCE THAT EXISTS HERE. UNITED STATES COURT REPORTERS 117 118 1 MR. VAN NEST: 2 THE COURT: 3 MR. VAN NEST: BUT -- BUT AGAIN, YOUR HONOR -- YEAH. I DON'T WANT TO DISPUTE THAT THERE'S 4 DOCUMENTARY EVIDENCE THAT PEOPLE WERE TALKING ABOUT AGREEMENTS. 5 BUT THERE'S NO DOCUMENTARY EVIDENCE OF ANY COMMON IMPACT 6 ACROSS THE CLASS. 7 ANY IMPACT. 8 9 10 11 12 THERE'S NO EVIDENCE IN DOCUMENTS OF REALLY THERE MAY BE EVIDENCE OF INTENT. PEOPLE TALKING TOGETHER, OF COURSE. TIME. THERE MAY BE EVIDENCE OF WE'VE REVIEWED THAT LAST THAT EVIDENCE IS COMMON. THE POINT HERE IS THAT IF YOU HAVE TO SHOW, AS COMCAST REQUIRES AND ELLIS -- 13 THE COURT: ANYWAY, OKAY. 14 MR. VAN NEST: 15 THE COURT: SO -- LET ME GIVE MR. GLACKIN AN OPPORTUNITY TO 16 RESPOND TO THIS ISSUE ABOUT IS IT BETTER TO MEASURE DEVIATION 17 VERSUS THE CORRELATION? 18 MR. GLACKIN: 19 THE COURT: 20 IT'S PARAGRAPH 22. MR. GLACKIN: 22 THE COURT: 23 MR. GLACKIN: 25 IT'S ON PAGE 8 OF DR. MURPHY'S -- 21 24 CAN YOU POINT ME TO EXACTLY -- WELL -- -- JUNE 2013 REPORT. OKAY, YEAH, I UNDERSTAND. I MEAN, THIS IS -- YOU KNOW, SO THIS IS THE HEART OF DR., OF DR. MURPHY'S CRITICISM, SO TO SPEAK, IS HE'S SAYING UNITED STATES COURT REPORTERS 118 119 1 2 DEVIATION REALLY MATTERS. AND WHAT IS HIS EXPLANATION FOR WHY DEVIATION REALLY 3 MATTERS? YOU MIGHT HAVE LOOKED LONG AND HARD FOR IT. 4 I THINK SOMEWHERE IN HIS REPORT HE SAYS BASIC ECONOMICS. 5 AND WHAT HE EXPLAINED AT HIS DEPOSITION IS THAT THE REASON 6 DEVIATION MATTERS IS THAT IT SHOWS THAT IT IS POSSIBLE FOR THE 7 DEFENDANTS TO PAY THEIR EMPLOYEES DIFFERENTLY. 8 SHOWS. 9 THAT IS WHAT IT AND IF IT IS POSSIBLE FOR DEFENDANTS TO PAY THEIR EMPLOYEES 10 DIFFERENTLY, THEN THEY WILL TRY TO PAY THEM AS LITTLE AS 11 POSSIBLE, EVEN IN RESPONSE TO COMPETITION. 12 13 14 THAT IS WHAT I UNDERSTAND TO BE HIS, THE THEORY BEHIND HIS ECONOMICS. AND I -- MY RESPONSE TO THAT IS WE ARE WAY BEYOND BASIC 15 ECONOMICS. 16 SITUATION WHERE EVERY COMPANY FACES OFF AGAINST ITS INDIVIDUAL 17 EMPLOYEES IN ONE-ON-ONE NEGOTIATIONS AND JUST DOES A SIMPLE 18 COST MINIMIZATION FORMULA. 19 WE ARE WAY BEYOND TALKING REASONABLY ABOUT A IT IS UNDISPUTED BY ANY OF THE EXPERTS AT THIS POINT THAT 20 THESE COMPANIES USE PAY STRUCTURES, THAT INFORMATION ECONOMICS 21 AND THE PRINCIPLES OF INTERNAL EQUITY ARE IMPORTANT FACTORS IN 22 HOW THESE COMPANIES PAY THEIR EMPLOYEES. 23 SO WHAT DR. MURPHY IS DOING IS SIMPLY SAYING, "WELL, IF I 24 LIVED IN A WORLD WHERE NONE OF THOSE THINGS MATTERED AND THE 25 WAY GOOGLE PAID ITS EMPLOYEES WAS TO SIT DOWN ACROSS THE TABLE UNITED STATES COURT REPORTERS 119 120 1 FROM THEM AND NEGOTIATE A SALARY AND THERE WAS NOTHING ELSE 2 THAT MATTERED TO THAT CALCULUS, THEN GOOGLE WOULD HAVE AN 3 INCENTIVE TO PAY THAT EMPLOYEE AS LITTLE AS POSSIBLE." 4 JUST AN IRRELEVANT HYPOTHETICAL. 5 MR. VAN NEST: 6 THE COURT: 7 IT'S IF I MAY -- WHAT ABOUT WHAT IS MR. VAN NEST'S TAB 5? I HAD SOME QUESTIONS ABOUT THESE CHARTS. 8 THE FIRST QUESTION IS, IN FOOTNOTE 10, DR. MURPHY SAYS, 9 "I'M INCLUDING PEOPLE WHO GOT PROMOTIONS AND WHO BASICALLY LEFT 10 ONE JOB TITLE AND MOVED TO ANOTHER ONE." 11 BE INCLUDED HERE? 12 VARIATION AS WELL IF YOU'RE TRACKING OVER TIME PEOPLE WHO ARE 13 IN MULTIPLE JOB TITLES. 14 VARIATION. 15 SHOULD THOSE PEOPLE BECAUSE THAT COULD EXPLAIN A LOT OF THE MR. VAN NEST: THAT COULD EXPLAIN SOME OF THE I THINK -- IT COULD. 16 BUT THIS VARIATION IS ENORMOUS, YOUR HONOR, AS YOU CAN SEE. 17 ALL WE'RE DOING HERE IS LOOKING AT EMPLOYEES WITHIN EACH OF 18 THESE JOB TITLES IN A PARTICULAR YEAR. 19 YEAR. 20 21 22 THIS ISN'T OVER TIME. SO THIS IS JUST ONE THIS IS IN 2007. SO YOU CAN SEE -THE COURT: RIGHT. BUT I GUESS I'M -- BUT HE SAYS IN THE FOOTNOTE THAT HE INCLUDED PEOPLE THAT CHANGED JOBS. 23 MR. VAN NEST: 24 THE COURT: 25 MR. VAN NEST: HE DID. SO -SO THERE WOULD BE SOME PEOPLE -- UNITED STATES COURT REPORTERS 120 121 1 THE COURT: SO THERE'S GOING TO BE -- SO THERE'S ONE 2 TITLE LISTED ON TOP OF EACH CHART, BUT THAT'S OBVIOUSLY 3 INCORRECT BECAUSE SOME OF THESE PEOPLE HAD DIFFERENT JOB 4 TITLES. 5 MR. VAN NEST: BUT TAKE A LOOK, THOUGH, YOUR HONOR. 6 IF THIS WERE CLOSE, THEN MAYBE WE WOULD BE -- MAYBE WE WOULD BE 7 LOOKING MORE CAREFULLY AT THAT FOOTNOTE. 8 9 10 BUT TAKE A LOOK. FOR EACH ONE OF THESE COMPANIES, THERE IS NOT ONLY A HUGE RANGE BETWEEN WHETHER YOU GO UP IN PAY OR GO DOWN -- 11 THE COURT: UM-HUM. 12 MR. VAN NEST: -- BUT THERE'S ALSO A HUGE RANGE IN 13 HOW MUCH. 14 A YEAR OR DOWN AS MUCH AS 60 PERCENT, AND THAT'S TRUE FOR 15 APPLE, IT'S TRUE FOR GOOGLE, IT SLIGHTLY LESS TRUE FOR INTUIT. 16 17 SOME OF THESE PEOPLE GO UP AS MUCH AS 75 PERCENT IN THE COURT: BUT THAT COULD BE EXPLAINED BY YOU GETTING A NEW JOB. 18 MR. GLACKIN: 19 THE COURT: 20 MR. GLACKIN: 21 THE QUESTION I HAD ALSO -- THE COURT: 23 MR. GLACKIN: 25 DO YOU STILL WANT ME TO RESPOND TO THIS OR NOT? 22 24 YES. GO AHEAD. I DON'T THINK WE TAKE SERIOUS ISSUE WITH IT ONE WAY OR ANOTHER. I WILL SAY THAT I THINK THE ANSWER TO THE QUESTION DEPENDS UNITED STATES COURT REPORTERS 121 122 1 ON -- THE ANSWER TO THAT QUESTION DEPENDS ON WHAT THE RELEVANT 2 QUESTION IS. 3 TOGETHER JOB TITLES, PROBABLY YOU SHOULD EXCLUDE THE PEOPLE WHO 4 CHANGED JOB TITLES. 5 6 7 8 9 IF THE QUESTION IS, IS THERE A STRUCTURE HOLDING IF THE QUESTION IS, DID THE DEFENDANTS PAY THEIR EMPLOYEES DIFFERENTLY, THEN MAYBE YOU SHOULD INCLUDE THEM. MR. VAN NEST: THE POINT? AND ISN'T THAT THE POINT? ISN'T THAT PROMOTION IS ANOTHER WAY TO RESPOND, YOUR HONOR. MR. GLACKIN: WELL -- 10 MR. VAN NEST: 11 DIFFERENTIATE BETWEEN EMPLOYEES. 12 MR. GLACKIN: 13 PROMOTION IS ANOTHER WAY TO MR. VAN NEST: THAT'S OUR WHOLE POINT -- I RESPECTFULLY -- SORRY. -- IS THAT WHEN YOU MOVE SOMEONE UP, 14 IT'S ANOTHER TOOL TO DIFFERENTIATE BETWEEN INDIVIDUALS, WHICH 15 IS WHAT -- A TOOL IS SALARY, A TOOL IS BONUS, A TOOL IS EQUITY, 16 AND A TOOL IS PROMOTION. 17 THE COURT: THE DOCUMENTARY EVIDENCE DOES SUPPORT 18 THAT PROMOTION WAS ONE WAY THAT MANAGERS DEALT WITH HOW TO 19 COMPENSATE THE TOP PERFORMERS. 20 MR. GLACKIN: 21 MR. VAN NEST: 22 23 INDIVIDUALS. SURE. AND THAT'S INDIVIDUALS. THAT'S OUR POINT. THAT'S THAT'S AN INDIVIDUAL THING. AND OUR WHOLE PITCH HERE, AND THE DATA SUPPORT IT, MURPHY'S 24 DATA AND SHAW'S DATA ALL SUPPORT THIS, IS THAT PEOPLE ARE 25 MAKING WIDE DISTINCTIONS IN VARIATIONS AMONG EMPLOYEES WITHIN UNITED STATES COURT REPORTERS 122 123 1 THE CLASS. 2 THE COURT: 3 MR. VAN NEST: 4 5 UM-HUM. AND THERE ARE WIDE VARIATIONS BETWEEN THE TITLES, WITHIN THE TITLES AND BETWEEN THE TITLES. THERE ISN'T THIS SORT OF RIGID JOB STRUCTURE THAT THEY SAID 6 THEY WOULD PROVE IN ORDER TO SHOW THAT CHANGES TO SOME WOULD 7 PROPAGATE OUT. 8 9 THE COURT: LET ME ASK -- AND I'M GOING TO GIVE YOU A CHANCE TO RESPOND. 10 MR. GLACKIN: 11 THE COURT: OKAY. THANK YOU. LAST TIME I GAVE DR. LEAMER A HARD TIME 12 FOR CHERRY PICKING JOB TITLES OUT OF GOOGLE AND APPLE AND 13 NOBODY ELSE. 14 AND THERE CERTAINLY SEEMS TO BE SOME CHERRY PICKING HERE, 15 BECAUSE FOR LUCASFILM, WE'RE COMPARING ARTIST 2 AND SENIOR 16 ARTIST 1 AND SOFTWARE ENGINEER, BUT THEN YOU GO SOMEWHERE ELSE 17 AND WE'RE COMPARING SOMETHING TOTALLY DIFFERENT. 18 WAS AN ANALYSIS DONE FOR ALL THE DIFFERENT JOB TITLES AND 19 THEN YOU JUST PICKED THE TOP THREE FOR EACH COMPANY THAT HAD 20 THE MOST VARIATION? 21 22 23 24 25 OR WHAT -- IT'S NOT CONSISTENT ACROSS. MR. VAN NEST: I THINK THAT DR. MURPHY WOULD HAVE TO ANSWER THAT. MR. GLACKIN: I CAN TELL YOU WHAT HE SAID AT HIS DEPOSITION IF YOU WANT. THE COURT: WHAT DID HE SAY? UNITED STATES COURT REPORTERS 123 124 1 MR. GLACKIN: WHAT HE SAID IS HE RAN IT BACK AT THE 2 RANCH, SO TO SPEAK, FOR EVERYTHING. 3 WAS IN THE MIDDLE OF THE CLASS PERIOD, AND HE PICKED -- I 4 THINK -- THE PROBLEM IS THAT -- I THINK IF YOU LOOK IN THE 5 REPORT, HIS REPORT, IT MAY SAY THAT THESE WERE THE MOST 6 POPULATED JOB TITLES AT THESE FIRMS. 7 BECAUSE IT'S TAKEN OUT OF THE REPORT, BUT I KNOW THAT WITH 8 RESPECT TO AT LEAST SOME OF THESE CHARTS, THAT WAS HOW HE 9 EXPLAINED HIS SELECTION OF THE JOB TITLES, WHICH IS FINE. 10 THE COURT: ALL RIGHT. HE PICKED 2007 BECAUSE IT I'M NOT -- I CAN'T TELL DO YOU WANT TO RESPOND TO 11 THIS, TO THESE CHARTS? 12 WITHIN A YEAR, WITHIN A SINGLE JOB TITLE. 13 14 MR. VAN NEST: TITLE, EVERY TITLE. THEY CERTAINLY SHOW A LOT OF VARIATION AND APPENDIX B, YOUR HONOR, IS EVERY APPENDIX B TO MURPHY, EVERY TITLE. 15 MR. GLACKIN: 16 THE COURT: 17 MR. GLACKIN: SO THIS IS MY RESPONSE TO THAT. UM-HUM. TO ACCEPT THE DEFENDANTS' POSITION, YOU 18 HAVE TO ACCEPT THAT THE EXISTENCE OF VARIATION IN PAY DISPROVES 19 THE EXISTENCE OF A JOB STRUCTURE THAT HOLDS TOGETHER BASED ON 20 INTERNAL EQUITY. 21 AND DR. MURPHY, AT HIS DEPOSITION, WISELY CONCEDED THAT 22 THERE IS NO INCONSISTENCY BETWEEN THOSE TWO THINGS. 23 PAY YOUR EMPLOYEES DIFFERENTLY IN THAT TOP -- YOU KNOW, AT THAT 24 TOP LEVEL IN TERMS OF THE TOP OF THEIR COMPENSATION, BUT STILL 25 HOLD THEM ALL TOGETHER IN A JOB TITLE STRUCTURE. UNITED STATES COURT REPORTERS YOU CAN 124 125 1 AND THIS WAS -- I MEAN, THIS IS THE QUOTE THAT WE SET OFF 2 FROM HIM. 3 IT'S INCONSISTENT THAT -- ARE YOU SAYING THAT IT'S INCONSISTENT 4 TO HAVE WIDE VARIATION IN PAY AND A STRUCTURE THAT HOLDS 5 TOGETHER ON INTERNAL EQUITY?" HE SAID, "NO, THEY'RE NOT 6 INCONSISTENT." 7 WHEN I ASKED HIM AT HIS DEPOSITION, "ARE YOU SAYING AND WE DRILLED DOWN ON IT AND HE SAID, "YEAH," HE SAID, "I 8 CAN'T TELL YOU THAT THE EXISTENCE OF WIDE VARIATION DISPROVES A 9 JOB STRUCTURE THAT RESPECTS INTERNAL EQUITY. 10 11 12 13 I CAN'T TELL YOU IT DISPROVES IT." AND THIS IS WHEN HE SAID THERE'S NO ABSOLUTES IN STATISTICS AND IF YOU WANT ABSOLUTES, YOU HAVE TO TALK TO GOD. BUT PUTTING ALL THAT ASIDE, THE DEFENDANTS' BRIEF IS SIMPLY 14 NOT CONSISTENT WITH COMMON SENSE. THERE'S NO REASON THAT YOU 15 CAN'T HAVE A STRUCTURE THAT IS HOLDING TOGETHER 90 PERCENT OF 16 THE COMPENSATION WHILE, AT THE SAME TIME, THERE IS VARIATION 17 OVER ON TOP OF THAT TO REFLECT THE FACT THAT PEOPLE ARE OLDER, 18 OR YOUNGER, OR OF DIFFERENT GENDERS, UNFORTUNATELY, OR HAVE 19 PERFORMED BETTER IN A GIVEN YEAR. 20 THERE'S NOTHING INCONSISTENT BETWEEN THOSE TWO THINGS, 21 WHICH IS WHY WE HAVEN'T EVER SAID THERE'S NO VARIATION BETWEEN 22 THE DEFENDANTS' PAYMENT. 23 THE COURT: I GUESS I'M NOT CLEAR. ARE YOU SAYING 24 FOR THE VAST MAJORITY OF PEOPLE, THEIR COMPENSATION WILL MOVE 25 TOGETHER WITHIN JOB TITLE, BUT THEN THERE'S GOING TO BE THE TOP UNITED STATES COURT REPORTERS 125 126 1 AND THE BOTTOM, THE TOP PERFORMERS, FOR EXAMPLE, AND PEOPLE WHO 2 MAY, FOR WHATEVER REASONS, NOT BE VALUED AS HIGHLY, BUT THOSE 3 WILL VARY THE MOST, BUT THE VAST MAJORITY IN THE MIDDLE IS 4 GOING TO MOVE -- 5 MR. GLACKIN: 6 THE COURT: 7 MR. GLACKIN: NO, NO, NO. I'M JUST NOT CLEAR ON WHAT YOU'RE SAYING. WHAT I'M SAYING IS IF YOU LOOK AT ANY 8 INDIVIDUAL EMPLOYEE'S COMPENSATION, HIGH PERFORMER OR LOW 9 PERFORMER, ABOUT 90 PERCENT OF IT IS EXPLAINED BY THEIR JOB 10 TITLE, WHICH MAKES PERFECT SENSE, YOU KNOW, WHEN YOU LOOK AT 11 THE FACT THAT THE DEFENDANTS TRACK ALL THEIR EMPLOYEES IN THE 12 SALARY RANGES THAT ARE NOT INFINITE ON THE TOP OR BOTTOM END. 13 SO WHATEVER EMPLOYEE YOU LOOK AT, HIGH OR LOW, GOOD YEAR, 14 BAD YEAR, MOST OF THEIR COMPENSATION IS EXPLAINED BY THEIR JOB 15 TITLE. 16 I MEAN, AND THAT IS WHY -- THAT IS ONE OF MANY REASONS THAT 17 THE JOB TITLE IS THE RIGHT PLACE TO LOOK FOR A STRUCTURE TO THE 18 DEFENDANTS' COMPENSATION AS A MATTER OF STATISTICS, IN ADDITION 19 TO THE RICH RECORD THAT TELLS US THAT THAT'S THE RIGHT PLACE TO 20 LOOK. 21 22 23 THE COURT: CAN WE GO TO DR. LEAMER'S REPLY REPORT, PARAGRAPH 35? MR. VAN NEST: YOUR HONOR, CAN I JUST RESPOND VERY 24 QUICKLY TO WHAT HE JUST SAID? 25 THE COURT: YES. UNITED STATES COURT REPORTERS 126 127 1 MR. VAN NEST: THE POINT IS WHERE THE JOB TITLE 2 SHOWS -- HAS AN ENORMOUS RANGE OF COMPENSATION WITHIN IT BASED 3 ON SALARY, EQUITY, AND BONUS, WHAT HE SAID MAKES ABSOLUTELY NO 4 DIFFERENCE, AND THAT'S WHY YOU HAVE THE RESULTS THAT YOU HAVE 5 WHEN YOU LOOK AT THE RAW DATA. 6 7 THE EMPLOYEES' PAY IS WIDELY VARIED YEAR TO YEAR, AND THE TITLES VARY WIDELY YEAR TO YEAR. 8 THE COURT: 9 MR. VAN NEST: 10 THE COURT: BUT IT'S -BECAUSE THERE'S SO MUCH DISCUSSION -- BUT IT'S NOT CONSISTENT WITH THE 11 DOCUMENTARY EVIDENCE THAT SAYS HERE ARE THE RANGES, AND IF YOU 12 WANT TO GO ABOVE THIS LEVEL, YOU NEED TO GET ONE ADDITIONAL 13 LEVEL OF APPROVAL, OR THAT -- 14 15 MR. VAN NEST: HONOR. 16 THE COURT: 17 MR. VAN NEST: 18 IT IS CONSISTENT -- EXCUSE ME, YOUR GO AHEAD. I APOLOGIZE. IT'S CONSISTENT WITH THE LEVEL -- YOU CAN LOOK AT 19 DR. HALLOCK'S FIGURE 7. 20 $50,000. 21 JUST SALARY, NOT INCLUDING BONUS AND EQUITY. 22 23 24 25 SOME OF THE RANGES ARE $100,000, THAT'S THE RANGE OF SOME OF THESE JOB TITLES. THAT'S THE REASON THAT YOU HAVE SOMETHING LIKE TABS 4, 5, AND 6 IS THAT THERE IS AN ENORMOUS RANGE WITHIN EACH JOB TITLE. NO ONE IS DENYING THAT THE DEFENDANTS HAVE STRUCTURES AND THAT THEY PAY PEOPLE WITHIN JOB TITLES. UNITED STATES COURT REPORTERS 127 128 1 BUT JOB TITLES, LIKE EVERYTHING ELSE, ARE BASED ON 2 PERFORMANCE, AND WHEN YOU PERFORM OUT OF ONE, YOU MOVE INTO 3 ANOTHER. 4 AND EVEN WITHIN A JOB TITLE, AS YOU CAN SEE IN TAB 4, 5 THERE'S MOVEMENT EVERY YEAR, UP AND DOWN. 6 LOT, THERE'S MOVEMENT A LITTLE, AND THAT'S WHY THERE'S SO MUCH 7 VARIABILITY. 8 CONCLUDE IMPACT TO SOME WOULD TRANSLATE TO IMPACT FOR OTHERS. 9 SOME OF THESE BANDS, JUST BASED ON BASE SALARY, ARE 50 TO 10 11 $100,000. THERE'S MOVEMENT A THAT'S WHY DR. LEAMER CAN'T SAY THAT HE CAN THAT DOESN'T COUNT EQUITY. THE COURT: WELL, THERE'S CERTAINLY A LOT OF 12 DOCUMENTARY EVIDENCE THAT SAYS WHAT THE SPECIFIC BAND IS FOR 13 EACH JOB TITLE FOR ALL OF THE DIFFERENT DEFENDANTS. 14 MR. VAN NEST: 15 THE COURT: 16 17 18 19 20 SO ANYWAY. MR. GLACKIN: THIS IS THE REBUTTAL, SUPPLEMENTAL EXPERT REPORT? THE COURT: I'M SORRY, NO. THIS IS HIS ORIGINAL. LET'S GO TO THE MULTIPLE REGRESSION ANALYSIS. MR. GLACKIN: 22 MR. VAN NEST: 23 THE COURT: 25 LET ME GO TO, PLEASE, PARAGRAPH 35. 21 24 TRUE. SURE. I'VE GOT IT, TINA. THIS IS WHERE HE WAS COMPARING THE INTERNAL VERSUS THE EXTERNAL FACTORS. MR. GLACKIN: RIGHT. UNITED STATES COURT REPORTERS 128 129 1 THE COURT: SO DO WE HAVE TO COMPARE THE MAGNITUDE OF 2 THE COEFFICIENTS FOR THE INTERNAL FACTORS RELATIVE TO THE 3 COEFFICIENTS FOR THE EXTERNAL FACTORS? 4 MR. GLACKIN: WELL, SO I DON'T THINK IT'S NECESSARY. 5 I THINK, YOU KNOW, THE WAY THAT THIS -- THE WAY THAT THIS 6 REGRESSION WORKS IS THAT IF THE DEFENDANTS WERE RIGHT THAT 7 EVERYBODY'S PAY IS COMPLETELY DETERMINED BY EXTERNAL FACTORS, 8 SUCH AS FIRM REVENUE OR PERFORMANCE OF THE FIRM OR THINGS GOING 9 ON IN THE GENERAL TECH JOB MARKET, IF YOU INCLUDE THOSE FACTORS 10 AND THEN YOU ALSO INCLUDE THE SHARING VARIABLES AND YOU RUN THE 11 REGRESSION AND THE SHARING VARIABLES STAY POSITIVE, IF THEY 12 DON'T ALL JUST GO AWAY, THEN YOU'VE STILL DETECTED THE 13 EXISTENCE OF A STRUCTURE. 14 BUT I DO THINK IT IS WORTH NOTING HERE THAT IN MANY CASES, 15 I BELIEVE IN -- I BELIEVE, OVERALL, THAT THE SHARING VARIABLES 16 DID BETTER AND PERFORMED BETTER IN DR. LEAMER'S OPINION THAN 17 THE EXTERNAL FACTOR VARIABLES. 18 19 SO I DON'T THINK THAT, YOU KNOW, STRICTLY SPEAKING YOU HAVE TO COMPARE THE MAGNITUDE. 20 IF THE ONLY THING THAT MATTERED WAS THE EXTERNAL FACTORS, 21 WHEN YOU RAN THE REGRESSION YOU WOULD GET BACK BIG RESULTS ON 22 THE EXTERNAL FACTORS AND YOU WOULD GET BACK ZERO ON THE SHARING 23 VARIABLES BECAUSE THE EXTERNAL FACTORS ARE ACCOUNTING FOR 24 EVERYTHING. 25 THE COURT: DO THE DEFENDANTS AGREE THAT THE UNITED STATES COURT REPORTERS 129 130 1 MAGNITUDE OF THE SHARING EFFECT VARIABLES IS LARGER THAN THE 2 EXTERNAL ONES? 3 MR. VAN NEST: NO, YOUR HONOR. 4 THEY'RE NOT SIGNIFICANT. 5 WE -- OUR POINT -- THEY'RE NOT SIGNIFICANT AT ALL, NUMBER ONE. 6 AND NUMBER TWO, AGAIN, WHAT DR. MURPHY SAYS ABOUT THIS 7 REGRESSION IS YOU WOULD EXPECT THE SAME RESULT WHETHER YOU HAD 8 A RIGID STRUCTURE OR A NON-RIGID STRUCTURE, BECAUSE IF WHAT 9 YOU'RE COMPARING IS A TITLE WITHIN ONE COMPANY TO THE SALARIES 10 AVERAGED OF ALL TECHNICAL EMPLOYEES IN THAT COMPANY, THERE'S 11 ALWAYS GOING TO BE SOME CORRELATION BECAUSE THEY'RE ALL SUBJECT 12 TO THE SAME EXTERNAL FACTORS, COMPANY PERFORMANCE, ECONOMY. 13 SO THEY'RE -- THESE ARE NOT SIGNIFICANT, AND WE SHOW THIS 14 IN FIGURE 8 OF -- YOU CAN SEE IT IN FIGURE 8 OF DR. LEAMER'S 15 REPORT. 16 SIGNIFICANT. 17 HE'S SAYING A LARGE NUMBER, ADOBE, 75 PERCENT, NOT APPLE, 62 PERCENT, NOT SIGNIFICANT. 18 MR. GLACKIN: 19 MR. VAN NEST: I -GOOGLE, 69 PERCENT, NOT SIGNIFICANT. 20 I MEAN, THEY'RE NOT -- AND BOTTOM LINE, WHAT I HAVE AT 21 TAB 8 IS LEAMER'S ADMISSION THAT AFTER ALL OF THE REGRESSIONS 22 HE DID, HE CANNOT TESTIFY THAT THERE'S ANYTHING THAT WOULD SHOW 23 CHANGES IN WAGES BEING TRANSLATED ACROSS THE FIRM. 24 25 THAT'S WHAT -- THAT'S THE POINT. TO SHOW. THAT'S WHAT HE'S TRYING THAT'S WHAT YOU CHALLENGED HIM ON LAST TIME IS CAN UNITED STATES COURT REPORTERS 130 131 1 YOU SHOW, TITLE TO TITLE, THAT ONE TITLE CAUSES ANOTHER TITLE 2 TO MOVE? 3 ANOTHER TITLE TO MOVE? OR THAT A CHANGE IN PAY IN ONE TITLE WOULD CAUSE 4 THE POINT ISN'T, DO WE HAVE A STRUCTURE? 5 IT'S, IS THE STRUCTURE RIGID OR IS IT FLEXIBLE? 6 AND WHAT DR. LEAMER ADMITTED IN HIS DEPOSITION AT PAGES 7 658 TO 660 WAS THAT EVEN THE COEFFICIENTS THAT HE SHOWS DO NOT 8 DEMONSTRATE THAT A CHANGE IN WAGES WOULD BE TRANSLATED ACROSS 9 THE FIRM. 10 SAME THING IN TAB 9. WE ASKED HIM AGAIN, "BASED ON 11 EVERYTHING YOU DID, CAN YOU TELL US THAT WHEN A COMPANY CHANGES 12 THE PAY OF SOME PEOPLE, IT PROPAGATES TO EVERYONE ELSE?" 13 "NO, I CAN'T DO THAT. 14 THE QUESTION ISN'T, DO WE HAVE A STRUCTURE? 15 EVERY COMPANY HAS TO HAVE SOME STRUCTURE FOR PAYING 50 TO 100,000 PEOPLE. 16 17 AND THAT'S NOT MY VIEW." THE QUESTION IS, IS THE STRUCTURE RIGID AND DOES A CHANGE IN ONE TITLE CAUSE A CHANGE IN ANOTHER TITLE? 18 AND ALL THE EVIDENCE IS TO THE SAME EFFECT, NO. 19 THE COURT: HAS DR. MURPHY DONE ANY STUDIES OR ANY 20 QUANTITATIVE ANALYSIS SHOWING WHAT THE RELATIONSHIP MAY BE 21 BETWEEN SAN JOSE EMPLOYMENT RATES AND THE AVERAGE COMPENSATION 22 FOR A TECHNICAL CLASS MEMBER? 23 MR. VAN NEST: 24 NOT. HE'S HERE. 25 I'M NOT SURE WHETHER HE'S DONE THAT OR I'M NOT SURE WHETHER HE'S DONE THAT ANALYSIS OR NOT. UNITED STATES COURT REPORTERS 131 132 1 MR. GLACKIN: 2 THE COURT: 3 MR. GLACKIN: IT'S CERTAINLY NOT IN HIS REPORT. UM-HUM. I MEAN, LIKE, IF DR. MURPHY HAD A 4 BETTER VARIABLE, RIGHT, IF SAN JOSE METRO AREA EMPLOYMENT WAS 5 THE WRONG VARIABLE, HE CERTAINLY HAD THE OPPORTUNITY TO TAKE 6 THE SAME REGRESSION AND PUT A DIFFERENT VARIABLE IN IT. 7 MR. VAN NEST: 8 MR. GLACKIN: 9 MR. VAN NEST: 10 11 12 13 14 15 MR. GLACKIN: HIS POINT ISN'T THAT THERE'S -- EXCUSE ME. I WASN'T FINISHED. I'M SORRY. I WAS ANSWERING THE JUDGE'S, WHAT I UNDERSTOOD THE COURT'S QUESTION TO BE. HE DID NOT DO THAT. HE DID NOT RE-RUN THIS REGRESSION WITH A, QUOTE UNQUOTE, BETTER VARIABLE. INSTEAD HE WENT TO OTHER DATA SETS, LIKE THE WEATHER, AND TRIED TO SHOW THAT HE CAN GET -- 16 THE COURT: 17 MR. GLACKIN: 18 NO. I WAS NOT PERSUADED. -- SIMILAR RESULTS. AND AGAIN, THE ABSENCE OF THAT, THE ABSENCE -- I MEAN, YOU 19 REMEMBER HE TESTIFIED AT HIS DEPOSITION THE FIRST TIME AROUND 20 THAT ADDING THE S&P 500 TOTAL RETURN INDEX IS SOMETHING HE 21 ALWAYS DOES TO TEST THE SENSITIVITY OF A REGRESSION AND WE HAD 22 TO, YOU KNOW, SLOG THROUGH MULTIPLE DIFFERENT REPORTS OF 23 REGRESSION RESULTS USING THINGS LIKE THE S&P 500 TOTAL RETURN 24 INDEX AND GIVING US CRAZY ANSWERS. 25 RESPECT. HE HASN'T DONE THAT IN ANY UNITED STATES COURT REPORTERS 132 133 1 THE BEST HE CAN DO IS SAY THAT IF YOU HYPOTHESIZE THAT WE 2 HAVE FAILED TO ACCOUNT FOR HALF OF THE RELEVANT FACTORS, THEN 3 THE ANSWER WOULD BE DIFFERENT. 4 WELL, I AGREE. 5 BE A DIFFERENT ANSWER. 6 7 BUT HE HAS NOT DONE THE STANDARD THING THAT, FRANKLY, I THINK IT SPEAKS VOLUMES THAT HE DID NOT DO. 8 9 IF YOU HYPOTHESIZE THAT, THEN THERE MIGHT MR. VAN NEST: YOUR HONOR, THE REASON YOU WOULDN'T DO IT IS THAT OBVIOUSLY IF WHAT YOU'RE TRYING TO COMPARE IS PAY 10 WITHIN ONE TITLE ON AN AVERAGE TO PAY WITHIN ALL TECHNICAL 11 EMPLOYEES IN A COMPANY, A REGRESSION DOESN'T ANSWER THE 12 QUESTION BECAUSE THEY WILL ALWAYS BE RELATED. 13 BE RELATED BECAUSE THEY'RE ALL SUBJECT TO THE SAME EXTERNAL SET 14 OF FACTORS. 15 THEY WILL ALWAYS WHAT THEY FAILED TO SHOW WAS THAT A CHANGE IN ONE TITLE 16 WOULD CAUSE A CHANGE IN ANOTHER. 17 IN FACT, HE SAYS, "I DON'T THINK IT'S TRUE." 18 DR. LEAMER DOESN'T SAY THAT. AND THAT IS GAME OVER BECAUSE THE WHOLE POINT IS NOT THAT 19 YOU HAVE A STRUCTURE, NOT THAT YOU PAY PEOPLE ACCORDING TO 20 TITLE. 21 22 23 WE DO THAT. BUT IS IT RIGID SO THAT EITHER WITHIN A TITLE OR ACROSS TITLES, A CHANGE IN ONE WOULD PROPAGATE OUT? THERE'S NO DATA TO SUPPORT THAT. 24 THE COURT: SO WHAT -- I'M SORRY TO INTERRUPT YOU. 25 MR. VAN NEST: I'M SORRY. UNITED STATES COURT REPORTERS 133 134 1 THE COURT: 2 IT THE DOCUMENTARY EVIDENCE? 3 WHAT IS YOUR EVIDENCE OF CAUSATION? MR. GLACKIN: IS WHAT DO YOU HAVE ON CAUSATION? INSOFAR AS THAT IS DIFFERENT FROM 4 IMPACT? I GUESS -- I MEAN, I THINK OF -- I THINK ANTITRUST 5 IMPACT AND CAUSATION ARE -- PEOPLE FREQUENTLY COMPARE ANTITRUST 6 IMPACT TO THE CONCEPT OF PROXIMATE CAUSATION IN GENERAL TORT, 7 SO I THINK THAT IT IS THE SAME EVIDENCE. 8 9 THE COURT: THE CAUSATION? AND WHAT IS IT? LET'S SAY I ACCEPT THAT THERE'S A CORRELATION. 10 MR. GLACKIN: 11 THE COURT: 12 MR. GLACKIN: 13 WHAT IS IT THAT SHOWS OKAY. WHAT'S THE CAUSATION? WELL, THE EVIDENCE -- AGAIN, IT HELPS TO BACK UP A LITTLE BIT TO WHERE, TO WHERE WE STARTED. 14 THE COURT: UM-HUM. 15 MR. GLACKIN: WHAT I UNDERSTOOD THE INQUIRY TO BE IS, 16 YOU KNOW, WE HAD DONE THE WORK TO SHOW THAT PEOPLE'S PAY AT 17 THESE COMPANIES, CLASS MEMBERS' PAY IS MAINLY DRIVEN BY JOB 18 TITLE. 19 AND WE HAD DONE THE WORK TO SHOW THAT THE -- TO AT LEAST 20 OFFER PROOF THAT THE AGREEMENTS HAD A BROAD AND GENERALIZED 21 EFFECT, WHICH WAS THE ADMISSIONS OF THE CEOS, THE DOCUMENTS, 22 THE NATURE OF THE AGREEMENTS THEMSELVES, AND THE REGRESSION 23 ANALYSIS. 24 25 THEY ALL SHOWED THAT THE INTENT AND THE ACTUAL EFFECT OF THESE AGREEMENTS -- I MEAN, THIS IS PROOF -- I UNDERSTAND THAT UNITED STATES COURT REPORTERS 134 135 1 THE DEFENDANTS WILL DISPUTE IT AT TRIAL -- BUT IT IS PROOF THAT 2 THESE AGREEMENTS HAD AN EFFECT BEYOND ONE WORKER. 3 THE THING THAT I UNDERSTOOD TO BE MISSING FROM THE COURT'S 4 PERSPECTIVE WAS SOME OF THE INFERENTIAL LINKS ALONG THE WAY, 5 AND SO WHAT WE HAVE DONE IS TO SHOW -- AND MAINLY ABOUT WHETHER 6 OR NOT THERE IS ACTUALLY A TITLE STRUCTURE THAT IS RESPECT -- 7 THAT RESPECTS INTERNAL EQUITY AND THAT APPLIES THROUGHOUT THE 8 FIRM. 9 10 THAT'S THE QUESTION THAT WE UNDERSTOOD TO BE POSED. AND WE HAVE, I THINK, ANSWERED IT. SO I WOULD SAY THAT IT IS -- IT IS ALL THAT EVIDENCE. WHAT 11 IS THE EVIDENCE OF CAUSATION? IT IS THE EVIDENCE THAT THEY PAY 12 ACCORDING TO TITLE? 13 EFFECT, INCLUDING THE EVIDENCE -- ADMISSIONS BY THE CEOS THAT 14 THEY HAVE A PAY STRUCTURE AND THAT THE GOAL OF THE AGREEMENTS 15 WAS TO PROTECT THE PAY STRUCTURE? IT IS THE EVIDENCE OF BROAD AND GENERAL 16 AND THEN IT IS ALL THE INFERENTIAL LINKS IN BETWEEN THAT 17 SHOW THAT HAD PREEMPTIVE MEASURES BEEN TAKEN BY THESE COMPANIES 18 TO RESPOND TO INCREASED COMPETITION, THAT THESE PREEMPTIVE 19 MEASURES WOULD HAVE APPLIED ACROSS THE FIRM. 20 AND TO RESPOND TO ONE THING THAT MR. VAN NEST SAID, I 21 BELIEVE, IF HE'S STILL REFERRING TO TAB 8 OF DR. LEAMER'S 22 TESTIMONY, HE'S OVERSTATING IT. 23 I DON'T THINK DR. LEAMER WAS EVER ASKED, NOR DID HE EVER 24 TESTIFY, ABOUT WHETHER MOVING A TITLE'S COMPENSATION WOULD 25 AFFECT THE REST OF THE FIRM. UNITED STATES COURT REPORTERS 135 136 1 THE DOCUMENTARY EVIDENCE, I THINK, SHOWS THAT AT SOME OF 2 THESE FIRMS IT WOULD HAVE, BECAUSE THEY -- BECAUSE THEY SET ALL 3 THEIR TITLES AS A PERCENTILE OFF OF RADFORD, AND SO THE WAY 4 THAT THEY WOULD MOVE THE TITLES IS TO CHANGE THE PERCENTILE 5 THAT THEY WERE PEGGING OFF OF RADFORD. 6 WHAT DR. LEAMER WAS ASKED OVER AND OVER AGAIN IS, "ARE YOU 7 SAYING THAT IF ONLY A FEW PEOPLE'S PAY CHANGED, THAT IT WOULD 8 AFFECT THE WHOLE FIRM?" 9 AND THAT IS NOT OUR THEORY OF THE CASE AND THAT IS NOT HIS 10 11 12 13 AND HE'S NEVER OFFERED THAT OPINION OPINION. THE COURT: BUT WHAT'S YOUR EVIDENCE OF CAUSATION ACROSS JOB TITLES? MR. GLACKIN: WELL, AGAIN, THE EVIDENCE OF CAUSATION 14 IS THE EVIDENCE THAT THESE, THAT THESE FIRMS RESPECT THE 15 PRINCIPLE OF INTERNAL EQUITY AND THAT THE TITLES ARE HELD 16 TOGETHER IN A STRUCTURE, IN PART TO PRESERVE INTERNAL EQUITY. 17 18 19 THE COURT: BUT ISN'T INTERNAL EQUITY ALL WITHIN THE JOB TITLE? MR. GLACKIN: NO, IT'S NOT. INTERNAL EQUITY OPERATES 20 AT DIFFERENT -- AT EVERY LEVEL OF THE COMPANY. 21 MAINTAINING A RELATIVE DISTANCE BETWEEN THE JOB TITLES IS JUST 22 AS IMPORTANT AS MAINTAINING THE RIGHT DISTANCE BETWEEN THE 23 EMPLOYEES WITHIN THE JOB TITLE. 24 25 I MEAN, THE -- SO INTERNAL EQUITY IS A CONCEPT THAT APPLIES UP AND DOWN THE FIRM AT EVERY LEVEL OF AGGREGATION. UNITED STATES COURT REPORTERS 136 137 1 THE COURT: OKAY. BUT WHAT IS YOUR EVIDENCE OF 2 CAUSATION ACROSS THE JOB TITLES? 3 IS A CORRELATION. 4 EVIDENCE BE? 5 LET'S SAY I ASSUME THAT THERE WHAT WOULD -- WHAT WOULD YOUR CAUSATION MR. GLACKIN: WELL, THE CAUSATION EVIDENCE, IN 6 ADDITION TO THE CORRELATION, IS THE CONDUCT REGRESSION WHICH IS 7 EVIDENCE OF BROAD AND GENERALIZED -- IN ADDITION TO BEING AN 8 ESTIMATE OF DAMAGES, IT IS EVIDENCE OF BROAD AND GENERALIZED 9 HARM. 10 AND SO THE COMBINATIONS -- AGAIN, I DON'T WANT TO JUST KEEP 11 SAYING THE DOCUMENTS AND THE CEOS OVER AND OVER AGAIN. 12 KNOW ABOUT THAT STUFF. 13 CAUSATION. 14 YOU I WOULD SAY THAT'S ALSO EVIDENCE OF BUT WHEN YOU TAKE THE CONDUCT -- STATISTICALLY WHEN YOU 15 TAKE THE CONDUCT REGRESSION AND YOU ADD IT THE CORRELATION 16 ANALYSIS, YOU CONCLUDE THAT THE BROAD AND GENERAL HARM WOULD 17 HAVE BEEN FELT THROUGHOUT THE COMPANY AND NOT CONCENTRATED AT 18 HALF THE TITLES, FOR EXAMPLE. 19 UNDERSTOOD. 20 THE COURT: THAT WAS THE INQUIRY THAT WE DO YOU THINK THAT THE CORRELATION 21 ANALYSIS AND THE REGRESSION ANALYSIS PROVES THE CAUSATION, OR 22 NOT? 23 MR. GLACKIN: SO I THINK THAT THE CONDUCT REGRESSION, 24 WHICH IS ALSO THE ESTIMATE OF DAMAGES, WHEN ADDED TO THE OTHER 25 STATISTICAL EVIDENCE PROVES CAUSATION, WHICH I UNDERSTAND TO BE UNITED STATES COURT REPORTERS 137 138 1 THE SAME THING AS ANTITRUST IMPACT. 2 3 THE COURT: THE CONDUCT REGRESSION AND WITH WHAT OTHER STATISTICAL EVIDENCE? 4 MR. GLACKIN: WITH THE EVIDENCE THAT ALL THE TITLES 5 AT THESE FIRMS HAVE A POSITIVE SHARING RELATIONSHIP WITH ONE 6 ANOTHER, BOTH CONTEMPORANEOUSLY AND OVER TIME. 7 EVIDENCE THAT THE EFFECT OF THESE AGREEMENTS WOULD HAVE BEEN 8 CLASS-WIDE. 9 10 THE COURT: THAT IS EVIDENCE THAT ALL TITLES HAVE POSITIVE SHARING RELATIONSHIPS OVER TIME? 11 MR. GLACKIN: AND I WANT TO BE -- I SHOULD BE 12 CAREFUL. 13 THAT HAVE NEGATIVE RELATIONSHIPS, BUT HE ALSO -- HE EXPLORED 14 THOSE TITLES, EXPLAINED WHY IT'S NOT SURPRISING TO FIND SOME 15 THAT HAVE NEGATIVE RELATIONSHIPS, AND EXPLAINED THAT HIS 16 OVERALL OPINION IS THAT THOSE TITLES ARE HELD TOGETHER THAT 17 WAY, AS IS DR. HALLOCK'S OPINION BASED ON THE EVIDENTIARY 18 RECORD. 19 I MEAN, DR. LEAMER NOTED THAT THERE ARE A FEW TITLES THE COURT: SO WHAT IS THE -- SO FOR THE COEFFICIENT, 20 YOUR CASE IS PROVEN IF THE NUMBER IS CLOSEST TO 1? 21 RIGHT? 22 STATISTICALLY SIGNIFICANT? 23 IS THAT AND FOR THE T-STAT, WHAT NUMBER IS IT TO BE MR. GLACKIN: SO FOR -- OKAY. SO LET ME TAKE THE 24 SECOND THING FIRST BECAUSE IT RELATES TO SOMETHING THAT 25 MR. VAN NEST WAS TALKING ABOUT BEFORE. UNITED STATES COURT REPORTERS 138 139 1 HE CALLED THE COURT'S ATTENTION TO NOT SIGNIFICANT, TO THE 2 NOT SIGNIFICANT COLUMN IN THE REGRESSION ANALYSIS, SO THAT 3 MEANS THAT THOSE RESULTS DON'T MEET STATISTICAL SIGNIFICANCE AT 4 CONVENTIONAL LEVELS. 5 6 A T-STAT OF 2 OR MORE IS STATISTICAL SIGNIFICANCE AT CONVENTIONAL LEVELS. 7 HOWEVER, THE FACT THAT WE DON'T -- THE POINT ISN'T THAT -- 8 IT'S NOT NECESSARY TO DR. LEAMER'S OPINION THAT ALL THE 9 COEFFICIENTS BE POSITIVE, ALTHOUGH THE VAST MAJORITY ARE; NOR 10 IS IT NECESSARY TO HIS OPINION THAT THEY ALL BE STATISTICALLY 11 SIGNIFICANT. 12 WHAT THE TOTAL PICTURE OF VAST, VASTLY POSITIVE 13 COEFFICIENTS AND VASTLY STATISTICALLY SIGNIFICANT COEFFICIENTS 14 WHERE YOU HAVE 11 YEARS OF DATA TELLS HIM THAT THIS STRUCTURE 15 DOES EXIST. 16 AND I'LL JUST POINT OUT THAT IT'S, AGAIN, IT'S SORT OF -- 17 IT'S SORT OF ESTABLISHED AGREEMENT IN THIS CASE AT THIS POINT 18 THAT STATISTICAL SIGNIFICANCE IS NOT NECESSARY TO THE 19 RELIABILITY OF AN ECONOMETRIC OPINION. 20 DR. MURPHY THE FIRST TIME AROUND. 21 OF BEHIND US ON THE ISSUE. 22 ZONE IN ON THAT COLUMN. 23 THE COURT: 24 MR. GLACKIN: 25 THAT WAS AGREED TO BY I THINK, AGAIN, THAT'S SORT SO I DON'T THINK IT'S HELPFUL TO WHAT'S THE CHANGE CORRELATION? COULD YOU TELL ME WHAT YOU'RE LOOKING AT? UNITED STATES COURT REPORTERS 139 140 1 THE COURT: I'M LOOKING AT EXHIBIT 2 -- 2 MR. GLACKIN: 3 THE COURT: 4 MR. GLACKIN: SURE. -- OF THE OPENING REPORT. OKAY. SO, YOU KNOW, IF IT WOULD BE 5 HELPFUL, I WOULD BE HAPPY TO JUST GO ACROSS THE COLUMNS, OR I 6 CAN JUST FOCUS ON -- 7 THE COURT: 8 MR. GLACKIN: 9 THAT'S FINE. -- CHANGE CORRELATION. SO LEVEL CORRELATION IS THE DEGREE TO WHICH THE 10 COMPENSATION LEVELS ARE CORRELATED, SO IF THE AVERAGE 11 COMPENSATION IS A HUNDRED GRAND FOR ONE TITLE, THE QUESTION IS, 12 HOW IS THAT LEVEL CORRELATED TO THE AVERAGES AT ANY GIVEN POINT 13 IN TIME? 14 15 16 CHANGE COMPENSATION IS THE RATE OF -- TO WHAT DEGREE ARE THE RATES OF CHANGE CORRELATED? SO WHEN THE -- WHEN THE OTHER COMPENSATION AT THE COMPANY 17 GOES UP BY X PERCENT, 5 PERCENT, WHAT HAPPENS -- HOW MUCH DOES 18 THE COMPENSATION FOR THAT TITLE CHANGE? 19 CHANGE? 20 WHAT PERCENT DOES IT AND THEN THE REGRESSION COEFFICIENTS ARE -- THE 21 CONTEMPORANEOUS COEFFICIENT IS -- BASICALLY IT SAYS HOW MUCH 22 EXPLANATORY POWER IS IN THE -- IS WHAT'S HAPPENING AT THE SAME 23 TIME WITH COMPENSATION TO THE REST OF THE CLASS? 24 FACTOR IS THAT IN THE PAY OF THE TITLE? 25 HOW MUCH OF A THE LAGGED COEFFICIENT, OR VARIABLE, ASKS HOW -- UNITED STATES COURT REPORTERS 140 141 1 THE COURT: 2 ADOBE'S JOB TITLES? 3 WHY DON'T YOU HAVE DATA FOR MOST OF WHY IS IT BLANK? MR. GLACKIN: BECAUSE -- SO YOU'RE TALKING -- SO THE 4 DATA FOR ADOBE TITLES IS BROKEN DOWN BY -- ALL THE DATA IN 5 THESE EXHIBITS IS BROKEN DOWN BY THE NUMBER OF YEARS FOR WHICH 6 WE HAVE DATA FOR A TITLE. 7 FOR EXAMPLE, WE HAVE 11 YEARS OF DATA. 8 TITLES ARE IN EXISTENCE FOR ALL 11 YEARS. 9 SOME OF THESE TO WORK WITH. 10 11 12 13 14 THAT'S A LOT OF DATA SOME OF THESE TITLES ARE IN EXISTENCE FOR TWO OR THREE YEARS. THAT'S NOT ENOUGH DATA TO WORK WITH. SOME OF THESE TITLES ARE IN EXISTENCE FOR SIX, SEVEN, OR EIGHT YEARS. THE REASON THAT YOU SEE BLANKS ON -- I THINK THE PAGE 15 YOU'RE LOOKING AT FOR ADOBE IS YOU'LL SEE THOSE ARE ALL TITLES 16 FOR WHICH WE ONLY HAVE SIX YEARS OF DATA. 17 TO DO THE CORRELATION ANALYSIS, BUT IT IS NOT ENOUGH DATA TO DO 18 THE REGRESSION ANALYSIS, BECAUSE THE REGRESSION ANALYSIS HAS 19 FOUR VARIABLES, AND WITH SIX -- AND ONE OF THOSE VARIABLES IS A 20 RATE OF CHANGE, AND WITH SIX -- I'M GOING TO TRY TO GET THIS 21 RIGHT -- WITH ONLY SIX YEARS OF DATA AND ONE OF YOUR VARIABLES 22 BEING A CHANGE VARIABLE, YOU ONLY HAVE 5 DEGREES OF FREEDOM, 23 WHICH IS NOT ENOUGH DATA. 24 KIND OF SENSIBLE ANSWER ABOUT FOUR EXPLANATORY VARIABLES AND 25 ONE DEPENDENT VARIABLE, WHICH IS FIVE VARIABLES TOTAL. THAT IS ENOUGH DATA IT'S NOT ENOUGH FREEDOM TO GET ANY UNITED STATES COURT REPORTERS 141 142 1 2 THE COURT: WHY DON'T YOU CONTINUE WITH THE CONTEMPORARY AND THE LAGGED VARIABLE? 3 MR. GLACKIN: SURE. SO THE CONTEMPORARY VARIABLE 4 REFLECTS HOW MUCH, HOW MUCH THE JOB TITLE'S COMPENSATION IS 5 EXPLAINED BY WHAT'S HAPPENING AT THE REST OF THE COMPANY. 6 THE LAGGED VARIABLE ASKS HOW MUCH OF THE JOB TITLE'S 7 COMPENSATION, IN THE REGRESSION, IS EXPLAINED BY THE DIFFERENCE 8 BETWEEN THE JOB TITLE AND THE REST OF THE CLASS, THE REST OF 9 THE COMPANY IN THE PRIOR YEAR. 10 SO IN OTHER WORDS, IF THERE WAS A BIG DIFFERENCE, DO WE 11 SEE A CONVERGENCE IN THE SECOND YEAR, OR VICE-VERSA? 12 IT TO BE EITHER ONE. 13 IT ALLOWS AND SO THAT IS TO ACCOUNT FOR THE POSSIBILITY THAT 14 SOMETIMES THE EFFECT OF THE INTERNAL EQUITY ON THE STRUCTURE 15 WILL BE FELT IN A SUBSEQUENT YEAR. 16 AND THEN THE OTHER TWO VARIABLES ARE THE EXTERNAL FACTOR 17 VARIABLES. 18 FIRM PERFORMANCE, YOU KNOW, THE COMPANY HAS A GOOD YEAR, SO 19 EVERYONE GETS PAID MORE; AND -- OR THAT TITLE GETS PAID MORE; 20 AND THE SJ EMP IS SAN JOSE EMPLOYMENT, SO THAT ACCOUNTS FOR THE 21 TECH SECTOR IS HOT, JOBS ARE SCARCE, PAY GOES UP. 22 REVENUE IS THE FIRM'S REVENUE, WHICH ACCOUNTS FOR AND WHAT YOU SEE WHEN YOU LOOK AT THESE IS A LOT OF MOSTLY 23 GOOD SIZED AND POSITIVE COEFFICIENTS ON THE INTERNAL SHARING 24 VARIABLES. 25 THEY'RE NOT ALWAYS POSITIVE AND THEY'RE NOT ALWAYS LARGE. UNITED STATES COURT REPORTERS 142 143 1 BUT THEY CERTAINLY DON'T GO AWAY WHEN YOU ACCOUNT FOR THE 2 EXTERNAL FACTORS, WHICH IS WHAT WOULD HAPPEN IF THE DEFENDANTS' 3 THEORY OF THE CASE WERE CORRECT. 4 THE COURT: WHAT ABOUT THE NET EFFECT? 5 MR. GLACKIN: 6 THE COURT: 7 MR. GLACKIN: OH, SO -- UM-HUM. -- ALL THE NET -- SO T STATUS IS 8 T-STAT, AND THE NET EFFECT IS IF YOU ADD THE CONTEMPORANEOUS 9 AND THE LAGGED VARIABLES TOGETHER, THAT'S THE ANSWER. 10 SO FOR -- IF YOU'RE LOOKING AT EXHIBIT 2, APPLE, YOU SEE 11 THAT FOR THE FIRST ONE, INFORMATION SYSTEMS MANAGER 2, THE 12 CONTEMP IS .8, THE LAGGED IS .04, IF YOU ADD THEM TOGETHER, YOU 13 GET .84. 14 THE COURT: AND WHAT IS THE OBS IN SECTION 6? 15 MR. GLACKIN: THAT IS THE R SQUARED. SO THAT IS 16 THE -- THAT IS JUST A -- THAT IS A STANDARD ECONOMIC, OR 17 STATISTICAL MEASURE OF WHAT'S CALLED GOODNESS OF FIT TO THE 18 DATA. 19 VARIABLE IS BEING EXPLAINED BY THE EXPLANATORY VARIABLES. 20 IT TELLS YOU SOMETHING ABOUT HOW MUCH OF THE DEPENDENT I'M SURE SOMEONE COULD PROBABLY EXPLAIN IT TECHNICALLY 21 BETTER THAN THAT, BUT I THINK EVERYONE AGREES THAT THAT'S 22 GENERALLY WHAT IT IS. 23 THE COURT: LET ME ASK BOTH SIDES, HOW DO YOU EXPLAIN 24 WHY THE TWO EXPERTS CAME OUT WITH CONFLICTING ANALYSIS OF THE 25 ACS DATA? DID THEY DO IT IN DIFFERENT WAYS? UNITED STATES COURT REPORTERS DID THEY LOOK AT 143 144 1 2 SOMETHING DIFFERENTLY? MR. GLACKIN: WELL, I DON'T THINK THAT THEIR 3 ANALYSIS -- HOW DID THEY COME OUT WITH CONFLICTING ANALYSIS OF 4 THE ACS DATA? 5 THIS IS THE STATE OF PLAY WITH THE ACS DATA. WHAT 6 DR. MURPHY DID IS HE TOOK ALL OF THE SURVEY DATA FROM ALL OF 7 THESE DIFFERENT JOBS ACROSS THE UNITED STATES AND HE PLUGGED IT 8 INTO A REGRESSION ANALYSIS AND HE SAID, "SEE, I CAN GET 9 POSITIVE RESULTS ON THE SHARING VARIABLES, SO THAT MEANS THAT 10 11 WHAT DR. LEAMER DID IS INVALID." WHAT DR. LEAMER HAS POINTED OUT IN HIS REBUTTAL REPORT, HIS 12 REPLY OR REBUTTAL REPORT, IS THAT THAT DATA SET IS COMPLETELY 13 UNSUITED TO THIS PURPOSE BECAUSE OF THIS HUGE METHODOLOGICAL 14 FLAW WITH THE WAY THE DATA IS GATHERED. 15 WHAT THE -- WHEN THE SURVEY IS ADMINISTERED TO THE OCCUPANT 16 OF THE HOUSE, A SINGLE PERSON FROM THE HOUSE ANSWERS ON BEHALF 17 OF EVERYBODY IN THE HOUSE AND SAYS THE LOT -- "IN THE LAST 365 18 DAYS, WE HAVE EARNED X AMOUNT OF MONEY," AND THAT SURVEY IS 19 ADMINISTERED EVERY MONTH. 20 SO IN EVERY MONTH, OTHER THAN DECEMBER, YOU'RE GETTING 21 ANSWERS FOR BOTH THE PRIOR YEAR AND -- YOU'RE GETTING AN AMOUNT 22 OF MONEY THAT INCLUDES MONEY FROM THE PRIOR YEAR AND MONEY FROM 23 THE CURRENT YEAR. 24 SO IF THE SURVEY IS ADMINISTERED IN JUNE, HE TELLS YOU, "I 25 EARNED 80 GRAND THIS YEAR," BUT YOU DON'T KNOW WHAT OF THAT 80 UNITED STATES COURT REPORTERS 144 145 1 GRAND WAS EARNED IN 2013 VERSUS WHAT OF THAT 80 GRAND WAS 2 EARNED IN 2012. 3 4 YOU HAVE NO IDEA. SO THEN DR. MURPHY TAKES THIS DATA SET AND HE USES -- HE APPLIES TO IT CALENDAR YEAR VARIABLES AND GETS THESE RESULTS. 5 AND, YOU KNOW, I DON'T KNOW WHAT, WHAT OTHER ANALYSIS HE 6 DID, BUT THIS ONE IS COMPLETELY INAPPROPRIATE AND IT IS SUBJECT 7 TO A HUGE METHODOLOGICAL FLAW AND THAT'S WHY IT'S NOT RELIABLE. 8 AND THEN AS DR. LEAMER POINTS OUT, THERE -- IF YOU -- IF 9 YOU ASK YOURSELF HOW WELL THESE TITLES ARE CORRELATED WITH ONE 10 ANOTHER IN THE ACS DATA SET, WHAT YOU SEE IS -- AND THIS IS IN 11 HIS REBUTTAL REPORT -- THAT IN THE ACS DATA -- SO THERE ARE -- 12 THERE IS ACTUALLY THE KIND OF CORRELATIONS YOU MIGHT EXPECT TO 13 SEE. 14 NEGATIVE CORRELATIONS, AND THEY FALL ROUGHLY EVENLY AROUND 0. 15 THERE ARE SOME POSITIVE CORRELATIONS, THERE ARE SOME IN THE DEFENDANTS' DATA, THE CORRELATIONS ARE ALMOST ALL 16 POSITIVE, AND MOST OF THEM ARE UP AROUND .8 OR .9, AND THAT 17 JUST SHOWS THAT THE ACS DATA IS COMPLETELY UNCOMPARABLE TO THE 18 DEFENDANTS' DATA AND ANALYZING IT IS A POINTLESS EXERCISE UNDER 19 THESE CIRCUMSTANCES. 20 21 THE COURT: ACS DATA. 22 23 LET ME LET MR. VAN NEST RESPOND TO THE MR. VAN NEST: AND I WANT TO GO BEYOND THAT A LITTLE BIT. 24 BUT THE ACS DATA JUST PROVES THE BASIC POINT THAT 25 DR. MURPHY IS MAKING, THAT THESE REGRESSIONS DON'T MEAN A UNITED STATES COURT REPORTERS 145 146 1 THING, AND EVEN LEAMER SAYS THESE ARE LIMITED EXERCISES. 2 LEAMER SAYS THESE DON'T SHOW CAUSATION. 3 OF HIS DEPO AND, REPEATEDLY, THESE DO NOT SHOW CAUSATION. 4 THEY ARE IS CORRELATION. 5 THE COURT: 6 MR. VAN NEST: HE SAYS IT AT PAGE 525 ALL UM-HUM. AND THE ACS DATA SHOWS THAT IF WHAT 7 YOU'RE COMPARING IS A TITLE WITHIN A COMPANY TO EVERYBODY IN 8 THE COMPANY, GETTING A POSITIVE CORRELATION DOESN'T TELL YOU 9 WHETHER YOU HAVE A RIGID OR A NON-RIGID STRUCTURE BECAUSE THOSE 10 THINGS WILL TEND TO BE CORRELATED NO MATTER WHAT -- 11 THE COURT: 12 MR. VAN NEST: 13 SAME EXTERNAL FACTORS. 14 15 UM-HUM. -- BECAUSE THEY ARE ALL SUBJECT TO THE LET ME MAKE ANOTHER POINT ABOUT THIS, YOUR HONOR. THE COURT: WHY DO YOU THINK THAT DR. MURPHY GOT THE 16 HIGH, THESE HIGH COEFFICIENTS AND DR. LEAMER GOT THE LOW ONES 17 WITH THE SAME DATA? 18 MR. VAN NEST: 19 DID WITH THE ACS DATA. 20 I DON'T KNOW EXACTLY WHAT DR. LEAMER ALL I KNOW IS THAT DR. MURPHY TRIED TO REPLICATE EXACTLY 21 WHAT LEAMER HAD DONE WITH THE COMPANY DATA. 22 LIKE LEAMER DID, SO HE WENT ABOUT IT THE SAME WAY LEAMER DID, 23 GOT THE SAME HIGH CORRELATIONS. 24 25 HE USED AVERAGES AND JUST AN EXAMPLE OF THIS, YOUR HONOR -THE COURT: EVEN HIGHER. UNITED STATES COURT REPORTERS 146 147 1 2 MR. VAN NEST: CORRELATIONS HE JUST TOLD YOU ABOUT FROM ADOBE -- 3 THE COURT: 4 MR. VAN NEST: 5 IF YOU LOOK -- IF YOU LOOK AT THE UM-HUM. -- YOU WILL SEE THE THIRD TITLE DOWN IS A PRINCIPAL SCIENTIST 6. 6 THE COURT: UM-HUM. 7 MR. VAN NEST: THE CORRELATIONS ARE HIGH, AND YET, IF 8 YOU LOOK AT THE RAW DATA FOR THAT ADOBE PRINCIPAL SCIENTIST 6, 9 BEHIND TAB 4 YOU'LL SEE THERE IS ENORMOUS VARIATION, ENORMOUS 10 VARIATION WITHIN THAT TITLE WITHIN THE PEOPLE EMPLOYED THERE. 11 AND SO THAT'S WHY MURPHY SAYS THIS REGRESSION AND 12 CORRELATION MEAN NOTHING. 13 YOU'VE TAKEN THE VARIATION OUT. 14 WHEN YOU AVERAGE TO START WITH, BUT IF YOU COMPARE WHAT HE'S SHOWING AS CORRELATION, HE'S 15 GOT A .86, HE'S GOT A .89 AND .79 ON HIS LEVEL AND CHANGE 16 CORRELATIONS FOR THIS PRINCIPAL SCIENTIST 6. 17 IF YOU LOOK AT THE RAW DATA BEHIND TAB 4, THERE IS AN 18 ENORMOUS AMOUNT OF VARIATION, PROVING OUR POINT THAT THESE 19 REGRESSIONS TELL YOU NOTHING. 20 AND THEY ARE SET UP TO SHOW SOMETHING THAT DOESN'T ANSWER THE 21 RIGHT QUESTION. 22 23 24 25 THEY ARE SET UP USING AVERAGES THE RIGHT QUESTION IS, DOES A CHANGE IN ONE TITLE CAUSE A CHANGE IN OTHER TITLES? HE HASN'T POINTED YOU TO ANY STATISTICAL EVIDENCE TO PROVE THAT. THERE IS NO DOCUMENTARY EVIDENCE TO PROVE THAT. UNITED STATES COURT REPORTERS 147 148 1 THE FACT THAT WE HAVE A STRUCTURE MEANS NOTHING WHEN THOSE 2 STRUCTURES HAVE 50 TO $100,000 OF RANGE WITHIN A BAND. 3 AND IF YOU LOOK AT MURPHY 7 AND MURPHY 8, THERE IS 4 ABSOLUTELY NO WAY TO CONCLUDE, OTHER THAN WITH RESPECT TO THESE 5 TITLES -- 6 7 THE COURT: WHAT EXHIBIT NUMBER HAS THE $100,000 RANGE? 8 MR. VAN NEST: 9 THE COURT: 10 EXCUSE ME? WHAT EXHIBIT NUMBER? MR. VAN NEST: IT'S EXHIBIT 7 IN HALLOCK. IT'S 11 EXHIBIT 7 IN HALLOCK, AND HE'S SHOWING AN EXAMPLE THERE OF 12 SALARY RANGES AT GOOGLE. 13 COMPANIES. 14 GOT -- IT'S FROM HIS MAY 10TH REPORT. 15 AT GOOGLE AND YOU CAN SEE THAT -- AND THAT'S JUST, YOU KNOW, ONE OF THE BUT IT'S FIGURE 7 FROM HALLOCK'S REPORT. 16 THE COURT: 17 MR. VAN NEST: HE'S HE'S SHOWING A JOB GRADE UM-HUM. -- AT THE HIGH END, IT'S MORE THAN 18 100, AND THEN YOU'VE GOT ANOTHER ONE THAT'S ALMOST A HUNDRED, 19 IT'S 90, ANOTHER ONE THAT'S 70. 20 21 I MEAN -- AND THIS IS JUST SALARY, YOUR HONOR, BASE. THIS DOESN'T INCLUDE EQUITY. 22 THE COURT: UM-HUM. 23 MR. VAN NEST: 24 THE COURT: 25 MR. VAN NEST: IT DOESN'T INCLUDE BONUS. UM-HUM. AND SO YOU WOULD EXPECT TO SEE THESE UNITED STATES COURT REPORTERS 148 149 1 WIDE VARIATIONS WITHIN A TITLE -- 2 THE COURT: 3 MR. VAN NEST: 4 UM-HUM. -- AND WIDE VARIATIONS BETWEEN AND AMONG TITLES. 5 THE COURT: UM-HUM. 6 MR. VAN NEST: AND I GUESS -- WHEN YOU HAVE LEAMER 7 ADMITTING THAT HE CAN'T SHOW CAUSATION AND YOU HAVE HIM 8 CONCEDING THAT HE CAN'T SAY THE STRUCTURE IS SO RIGID THAT 9 THERE WOULD BE PROPAGATION, ADD THAT TO APPENDIX E, WHICH IS 10 TAB 11 IN WHAT I HANDED UP, YOUR HONOR. 11 OF 2400 JOB TITLES THAT THEY'RE TRYING TO STAND HERE AND TELL 12 YOU ARE ALL MOVING TOGETHER AND ALL CAUSE ONE TO THE OTHER. 13 14 IT'S LUDICROUS. APPENDIX E IS THE LIST YOU CAN GO TO ANY PAGE OF THIS AND SEE AN ENORMOUS AMOUNT OF VARIATION ON ALL THESE COMPANIES. 15 INTEL, 800 TITLES. 16 APPLE, 350 TITLES. 17 GOOGLE, 300 TITLES. 18 AND JUST LOOK AT THE RANGE. PICK UP THE FIRST PAGE OF 19 INTEL: 20 ENGINEERING MANAGER; YOU'VE GOT A CHEMICAL ENGINEER; A CIRCUIT 21 DESIGN ENGINEER; CONSTRUCTION PROJECT MANAGER; CONSULTING 22 ENGINEERING MANAGER; FAILURE ANALYSIS ENGINEER. 23 ON AND ON AND ON. 24 25 ASSEMBLY TD PROCESSOR AND INTEGRATOR; YOU'VE GOT A CAD IT GOES ON AND AND WITH 2400 OF THESE, THE IDEA THAT THEY -- THAT THERE'S SOME, QUOTE, LINKAGE WITHIN COMPANIES IS ABSOLUTELY CRAZY. UNITED STATES COURT REPORTERS 149 150 1 AND THAT'S WHY THERE ISN'T ANY STATISTICAL EVIDENCE. 2 IS NONE. THE STATISTICAL EVIDENCE POINTS THE OTHER WAY. 3 THERE VARIATION, WIDE DISCRETION, BIG DIFFERENCES YEAR TO YEAR. 4 MR. GLACKIN: 5 MR. VAN NEST: HUGE I -AND SO WHAT THEY'RE ASKING YOU TO 6 DO -- THIS IS A SWING FOR THE FENCES TYPE PLAY. 7 A FACTOR OF THREE THAN ANY SIMILAR CASE THAT'S -- WHERE IT'S 8 EVEN BEEN REQUESTED. 9 IT'S BIGGER BY AND IN REED AND THE OTHER CASES THAT WE CITED, YOUR HONOR, 10 WEISFELDT AND FLEISHMAN, MUCH SMALLER CLASSES WITH SINGLE JOB 11 TITLES WERE NOT CERTIFIED. 12 THE COURT: 13 MR. VAN NEST: UM-HUM. AND THAT'S BEFORE COMCAST SAID YOU 14 HAVE TO MAKE A RIGOROUS ANALYSIS OF THE DATA AND SEE HOW 15 RELIABLE AND PERSUASIVE IT IS IF WHAT THEY WANT IS SOMETHING 16 THIS BIG WHERE THEY'RE GOING TO PROVE IN ONE TRIAL ALL OF THIS, 17 ALL THIS STUFF. 18 NOW, YOU OFFERED THEM SOMETHING LESS AND THEY DON'T WANT 19 IT, AND THAT SOMETHING LESS WAS, LET'S TRY THE CONSPIRACY ISSUE 20 FIRST. 21 THEY'VE GOT TO PROVE IMPACT ACROSS THE CLASS AND THEY 22 HAVEN'T DONE IT. 23 DOCUMENTS THAT REFLECT THAT. 24 25 THE DATA DON'T REFLECT IT. THERE ARE NO AND SO WE NEED TO THINK ABOUT ANOTHER WAY TO RESOLVE THIS CASE, AND I THINK COMING BACK TO THE IDEA OF LETTING PEOPLE, IN UNITED STATES COURT REPORTERS 150 151 1 EFFECT, OPT INTO A MASS ACTION WHERE WE CAN ACTUALLY MANAGE HOW 2 IT GETS TRIED AND WHAT PORTIONS OF IT GET TRIED AND HOW WE CAN 3 SET OURSELVES UP TO RESOLVE THIS IS A LOT BETTER THAN THIS HAIL 4 MARY WHERE THEY WANT 60,000 PEOPLE IN A CLASS WITH 2400 TITLES. 5 IT'S JUST GOING TO BE A MESS AND WE'RE BETTER OFF SAYING NO 6 NOW. 7 SAY NO AND FIGURE OUT ANOTHER BETTER WAY TO DO THIS, WHICH, AS 8 I SAY, IS HOW WE'RE TRYING THESE TORT CASES AROUND CALIFORNIA 9 AND THE UNITED STATES NOW MORE AND MORE. 10 BECAUSE THEY DIDN'T TAKE YOUR MORE LIMITED OFFER, LET'S WITH THESE STANDARDS BEING IMPOSED FROM COMCAST AND ELLIS 11 AND AMGEN AND ALL THIS, WHAT COURTS ARE DOING IS REFUSING TO 12 CERTIFY AND FINDING A BETTER WAY, USUALLY A MASS APPROACH WHERE 13 PEOPLE MAKE THEIR CLAIMS AND WE TRY, IN A BELLWETHER TRIAL, A 14 SERIES OF THOSE. 15 THAT'S THE WAY THIS CASE SHOULD BE RESOLVED. 16 FAIRER TO THE DEFENDANTS. 17 THAT'S A LOT WE'LL GET A BETTER RESULT. 18 THIS CLASS CAN'T STAND UP. 19 20 IT'S A LOT BETTER ACROSS THE BOARD. THE COURT: ALL RIGHT. LET ME INTERRUPT YOU ONE SECOND. 21 MR. VAN NEST: 22 THE COURT: YEAH. LET ME ASK MR. GLACKIN, LAST TIME YOU HAD 23 MENTIONED THAT YOU MIGHT BE INTRODUCING THE STATISTICAL 24 EVIDENCE FOR FALSIFICATION PURPOSES. 25 ARE YOU DOING THAT NOW, OR THAT'S NOT REALLY AN ISSUE UNITED STATES COURT REPORTERS 151 152 1 ANYMORE? 2 3 MR. GLACKIN: I DON'T THINK THAT THAT'S A VERY IMPORTANT ISSUE. 4 THE COURT: OKAY. 5 MR. GLACKIN: 6 THE COURT: CAN I RESPOND TO SOME OF THAT? WELL, I'M GOING TO -- I'D LIKE TO WRAP 7 UP, AND I ALSO WANT TO HAVE A LITTLE BIT OF A CMC, BUT I WANT 8 TO FINISH IN THE NEXT TEN, NO LATER THAN THE NEXT TEN MINUTES. 9 SO -- 10 MR. VAN NEST: 11 THE COURT: 12 YES, I KNOW. YOU HAVE A FLIGHT TO CATCH, RIGHT? 13 MR. VAN NEST: 14 THE COURT: 15 MR. VAN NEST: 16 THE COURT: 17 MR. GLACKIN: 18 ME, TOO, YOUR HONOR. I DO. OKAY. IS IT OKAY IF WE GO TO 5:30? SURE. OKAY. THERE'S JUST A COUPLE OF POINTS IN THAT THAT I THINK I CAN RESPOND TO RATHER BRIEFLY IF IT'S ALL RIGHT. 19 THE COURT: OKAY. 20 MR. GLACKIN: VERY QUICK. SO FIRST OF ALL, THE RIGOROUS ANALYSIS 21 STANDARD IS NOT NEARLY -- IT'S BEEN AROUND FOR 30 YEARS. 22 DUKES, COMCAST, AMGEN, NONE OF THOSE CASES CHANGE IT. 23 BEEN AROUND FOREVER. IT'S IT'S BEEN AROUND SINCE EISEN. 24 SECOND OF ALL, THIS IS NOT A BIG CLASS. 25 PARTICULARLY LARGE OR COMPLICATED CLASS ACTION. UNITED STATES COURT REPORTERS THIS IS NOT A I MEAN, WE 152 153 1 REGULARLY CERTIFY, IN ANTITRUST CASES, CLASS ACTIONS WITH 2 THOUSANDS OF PRODUCTS, THOUSANDS OF PURCHASERS. 3 IT IS THE REASON -- THE FACT THAT CLASS RELIEF -- 4 THE COURT: IT IS THE -- CAN I -- LET ME INTERRUPT YOU AND ASK A 5 QUESTION. 6 THE SMALLER 150,000 MEMBER WAL-MART CLASS, AND ONE OF HIS 7 COMMENTS IN HIS CONCLUSION WAS, "LOOK, IT'S KIND OF ARBITRARY 8 HOW YOU CHOSE TO NARROW THIS. 9 REGIONS YOU CHOSE ARE REALLY NOT ANY DIFFERENT THAN ANY OTHER 10 11 YOU KNOW, JUDGE BREYER RECENTLY DENIED CLASS CERT TO YOU KNOW, THE GEOGRAPHICAL REGIONS WHERE WAL-MART OPERATES." WHAT -- HOW WOULD YOU RESPOND TO -- YOU KNOW, WHAT 12 JUSTIFIES THIS TECHNICAL CLASS? 13 BLAME FOR THIS, BUT WHAT JUSTIFIES THIS VERSUS THE ALL EMPLOYEE 14 CLASS? 15 16 OR WHAT -- YOU KNOW, WHAT -MR. GLACKIN: THE COURT: 18 MR. GLACKIN: 20 21 22 SO THE -- THE SUBSEQUENT DISCOVERY THAT WE'VE TAKEN SINCE THE HEARING -- 17 19 AND MAYBE I'M PARTIALLY TO UH-HUH. -- HAS CONFIRMED THAT THESE AGREEMENTS WERE PARTICULARLY TARGETED AT HIGH TECH WORKERS. THE -- SO THERE'S A LITTLE BIT MORE EVIDENCE ABOUT THAT IN THE RECORD NOW THAT WE ALSO CITED. BUT THE SELECTION OF THIS GROUP OF PEOPLE WAS NOT AT ALL 23 ARBITRARY. I MEAN, THE DEFENDANTS THEMSELVES, SEVERAL OF 24 THEM -- AND THIS IS ALL IN APPENDIX B TO DR. LEAMER'S FIRST 25 REPORT -- SEVERAL OF THESE DEFENDANTS SEGMENT THEIR EMPLOYEES UNITED STATES COURT REPORTERS 153 154 1 INTO TECH AND NON-TECH. 2 EMPLOYEE AND EVERY JOB TITLE THAT IT CONSIDERS TO BE TECHNICAL, 3 SO WE INCLUDED THOSE. 4 5 6 GOOGLE PUTS A "T" NEXT TO EVERY WE EXCLUDED THE OTHER ONES. YOU KNOW, THIS IS A DIFFERENTIATION THAT'S BEING DRIVEN BY THE DEFENDANTS' OWN APPROACH TO THEIR EMPLOYEES. AND THEN IN ADDITION TO THAT, WE'VE ASKED DR. HALLOCK, WHO 7 IS A LEADING EXPERT ON COMPANY PAY SYSTEMS AND HOW COMPANIES 8 ORGANIZE AND COMPENSATE THEIR EMPLOYEES, HE'S REVIEWED THE 9 TECHNICAL CLASS AND HE'S OFFERED THE OPINION THAT, FIRST OF 10 ALL, IT'S A SENSIBLE COLLECTION THAT IS CONSISTENT WITH THE WAY 11 THAT COMPANIES ORGANIZE THEIR JOB FAMILIES TO REFLECT 12 PARTICULAR FUNCTIONS WITHIN THE FIRM, AND HE'S ALSO OFFERED THE 13 OPINION THAT HARM LIKELY WOULD HAVE BEEN CONCENTRATED ON THE 14 TECHNICAL CLASS GIVEN THE NATURE OF THE AGREEMENTS. 15 SO IT WAS NOT AN ARBITRARY DECISION AT ALL. 16 THE COURT: ALL RIGHT. LET ME DO A LITTLE 17 HOUSEKEEPING AND THEN I'M GOING TO GIVE YOU THE LAST COUPLE 18 MINUTES TO WRAP UP TO SAY WHATEVER, HOWEVER YOU WISH TO CLOSE. 19 LET'S HAVE THE FURTHER CMC ON OCTOBER 3RD, WHICH IS WHEN 20 WE'RE GETTING TOGETHER ANYWAY FOR THE PRELIMINARY APPROVAL. 21 DOES THAT SOUND OKAY? 22 MR. VAN NEST: 23 THE COURT: THAT'S FINE, YOUR HONOR. ALL RIGHT. I WOULD -- IN LIGHT OF THE 24 THREE DEFENDANTS SETTLING, I'D LIKE TO REDUCE SOME OF THE PAGE 25 LIMITS THAT I HAD PREVIOUSLY SET FOR PRETRIAL DOCUMENTS. UNITED STATES COURT REPORTERS 154 155 1 2 MR. VAN NEST: COULD I JUST BRIEFLY MAKE A PLEA THAT YOU NOT DO THAT, YOUR HONOR? 3 WE'RE HAVING -- WE HAVE -- IT'S STILL FOUR DEFENDANTS. 4 EACH HAVE ISSUES THAT WE NEED TO PRESS. 5 WE SAME. 6 WE'RE NOT ALL THE AND HONESTLY, IF THEIR POSITION IS THAT ALL THE SAME 7 EVIDENCE AND STUFF IS RELEVANT, IT SHOULDN'T CHANGE THE PAGE 8 LIMITS. 9 10 11 I WOULD JUST LEAVE IT AT THAT, YOUR HONOR, AND ASK YOU PLEASE NOT TO DO THAT. THE COURT: IT'S ALREADY REALLY TIGHT. WELL, THIS IS WHAT I'LL DO. LET'S TALK 12 ABOUT THIS -- SINCE IT'S A LATE HOUR NOW, LET'S TALK ABOUT THIS 13 ON OCTOBER 3RD SINCE WE HAVE TIME. 14 GOING TO RUN UNTIL, I THINK, FEBRUARY. 15 MR. VAN NEST: 16 THE COURT: NONE OF THOSE DEADLINES ARE GOOD TO GO. OR JANUARY. BUT IF YOU WOULD AT LEAST 17 TALK ABOUT MAYBE YOU COULD SHAVE SOME OFF HERE AND THERE. I 18 MEAN, THESE LIMITS WERE SET ASSUMING ALL SEVEN DEFENDANTS WOULD 19 BE PARTICIPATING. 20 SOME LIMITS AND THEN PUT YOUR PROPOSAL IN THE JOINT CASE 21 MANAGEMENT STATEMENT. SO IF YOU WOULD PLEASE AT LEAST CONSIDER 22 MR. VAN NEST: 23 THE COURT: CERTAINLY WE WILL. ALL RIGHT. SO -- WELL, I WAS GOING TO 24 MAKE SOME PAGE REDUCTIONS, BUT IF YOU WANT ME TO HOLD OFF ON 25 THAT, THEN I DON'T THINK THAT -- UNITED STATES COURT REPORTERS 155 156 1 MR. VAN NEST: 2 THE COURT: 3 -- THERE'S ANYTHING MORE WE NEED TO DO ON THE CMC. 4 MR. VAN NEST: 5 MR. SAVERI: 6 PLEASE. THANK YOU. I THINK THAT'S FINE. WE'LL WORK IT OUT -- 7 MR. VAN NEST: 8 MR. SAVERI: 9 THE COURT: WE'LL WORK IT OUT. -- AFTER MR. VAN NEST'S SOJOURN. I WOULD APPRECIATE ANY SHAVING. 10 MR. SAVERI: YOU GOT IT. 11 MR. VAN NEST: 12 THE COURT: WE KNOW THAT, YOUR HONOR. OKAY. AND ALSO IF YOU WOULD GIVE ME A 13 NEW TRIAL ESTIMATE AS WELL, YOU KNOW, DEPENDING ON WHO IS LEFT 14 TO TRY THE CASE, WHETHER THAT WOULD ACTUALLY CHANGE THE LENGTH 15 OF THE TRIAL. 16 17 18 19 MR. SAVERI: SO WE HAVE 17 DAYS. YOU WANT TO SEE IF WE CAN TRIM THAT BACK? THE COURT: YEAH. I JUST WANT TO KNOW, IS THERE A NEW ESTIMATE NOW THAT THERE ARE THREE FEWER DEFENDANTS? 20 MR. SAVERI: 21 THE COURT: OH, OKAY. OKAY. WHY DON'T -- WE'LL KEEP EVERYTHING 22 AS IS, BUT IF YOU WOULD PLEASE MEET AND CONFER AND MAKE SOME 23 PROPOSALS. 24 MR. VAN NEST: 25 THE COURT: WE'LL DO THAT. OKAY. LET ME GIVE THE LAST, REALLY, TWO UNITED STATES COURT REPORTERS 156 157 1 MINUTES, BECAUSE POOR MS. SHORTRIDGE IS PROBABLY GOING TO LOSE 2 HER ARMS IN A MINUTE, JUST THE LAST TWO MINUTES OF YOUR 3 STRONGEST WHATEVER YOU WANT TO SAY ON IMPACT OR WHY THIS SHOULD 4 BE CERTIFIED OR -- 5 6 7 MR. GLACKIN: WELL, THERE'S ONE, ONE POINT I WANTED TO MAKE. MR. VAN NEST SAID THAT DR. LEAMER ADMITTED NOTHING HE DOES 8 CAN SHOW CAUSALITY AND HE CITED TO 525 OF THE DEPOSITION OF 9 DR. LEAMER. 10 I WENT IMMEDIATELY TO THE EXCERPTS THAT WE HAVE THAT WERE 11 SUBMITTED BY THE DEFENDANTS. 12 CAN'T CONFIRM THAT HE DID SAY THAT. 13 BUT I WAS AT HIS DEPOSITION. 14 15 I DIDN'T SEE THAT PAGE, SO I I DON'T REMEMBER HIM EVER SAYING THAT. AND HE EXPRESSLY SAYS IN HIS FINAL REPORT THAT THE KIND OF 16 REGRESSION ANALYSIS HE'S DONE, WHICH INCLUDES TEMPORAL ORDERING 17 AND ALSO INCLUDES ACCOUNTING FOR THE EXTERNAL FACTORS THAT THE 18 DEFENDANTS HAVE CLAIMED ARE IMPORTANT, CAN SUPPORT AN INFERENCE 19 OF CAUSALITY. 20 SO, YOU KNOW, WE HAVE -- I'M ONLY GOING TO -- YOU'VE HEARD 21 A LOT OF ARGUMENT TODAY. 22 I'M NOT GOING TO WALK THROUGH IT ALL AGAIN. 23 ALL I WILL SAY IS THAT, YOU KNOW, WE SORT OF UNDERSTOOD 24 THERE TO BE A SPECIFIC ISSUE, A DEFICIENCY THAT HAD BEEN RAISED 25 WITH RESPECT TO THE EVIDENCE THAT WE HAD SUBMITTED. UNITED STATES COURT REPORTERS WE HADN'T 157 158 1 SHOWN MOVEMENT OVER TIME, WE HADN'T EXPANDED THE ANALYSIS TO 2 THE ENTIRE STRUCTURE, AND WE HADN'T ACCOUNTED FOR EXTERNAL 3 FACTORS. 4 WE'VE NOW DONE ALL THREE OF THOSE THINGS. WE HAVE 5 COMPLETED ALL THE INFERENTIAL LINKS THAT THE DEFENDANTS 6 COMPLAINED ABOUT LAST TIME, AND THAT'S WHY, INSTEAD OF SAYING 7 WE HAVEN'T, THEY'RE JUST FOCUSSING BACK ON THIS QUESTION OF 8 INDIVIDUAL VARIATION AND SAYING THAT IT MATTERS. 9 BUT IN THE TEXT OF HIS DEPOSITION THAT WE BLOCK QUOTED IN 10 OUR REPLY BRIEF, DR. MURPHY ADMITS THAT IT DOESN'T MATTER, THAT 11 WIDE VARIATION IN INDIVIDUAL PAY IS NOT INCONSISTENT WITH A JOB 12 TITLE STRUCTURE HELD TOGETHER BY INTERNAL EQUITY. 13 AND SO WHAT THAT TELLS YOU IS WE HAVE -- WE HAVE NOT JUST 14 GIVEN THE COURT A PLAUSIBLE METHODOLOGY. 15 GIVEN THE COURT, I THINK, SIGNIFICANT PROOF OF ANTITRUST 16 IMPACT, FAR MORE SIGNIFICANT PROOF THAN I HAVE SEEN IN AN 17 ANTITRUST CLASS CASE. 18 19 AT THIS POINT WE HAVE SO I RESPECTFULLY SUBMIT WE'VE MORE THAN CLEARED THE HURDLE ON THAT ONE. 20 MR. VAN NEST: SO, YOUR HONOR, I'LL STICK WITH THE 21 KEY POINTS IN THE TABS I HANDED UP. 22 STORY. 23 I THINK THEY TELL THE AND LET ME TELL IT JUST FROM THE VERY HIGHEST POINT. THERE 24 ARE THREE REASONS WHY THEY FAIL THE TEST THAT COMCAST SETS OUT. 25 COMCAST SAYS RIGOROUS ANALYSIS, YOU'VE GOT TO PROVE CLASS-WIDE UNITED STATES COURT REPORTERS 158 159 1 INJURY, WHICH YOU'VE INTERPRETED, I THINK CORRECTLY SO, AS ALL 2 OR NEARLY ALL PEOPLE. 3 ONE. LEAMER AVERAGED AND THE CASE LAW UNIFORMLY REJECTS 4 THAT. 5 UNIFORMLY REJECTED THAT AVERAGING CAN ALLOW YOU TO SHOW 6 CLASS-WIDE IMPACT. 7 GPU REJECTED IT, REED REJECTED IT, AND IT'S BEEN IT CAN'T, BECAUSE THE WAY THE AVERAGE MOVES DOESN'T TELL 8 YOU ANYTHING ABOUT HOW MANY PEOPLE WERE IMPACTED. 9 ONE. 10 POINT TWO. THAT'S POINT THE RAW DATA THAT WE LOOKED AT IN TABS 4, 5, 6, 11 AND 7 SHOWS TWO THINGS CLEARLY AS A BELL. 12 ENORMOUS VARIATION WITHIN EACH JOB TITLE BECAUSE THE BANDS ARE 13 BROAD, BECAUSE THERE IS SALARY, BONUS AND EQUITY ALL IN PLAY, 14 AND FOR ALL THESE TITLES, AND MURPHY LOOKED AT EVERY ONE, THERE 15 IS A WIDE RANGE OF VARIATION WITHIN THE TITLE. 16 ONE, THERE IS AND POINT TWO, THERE IS NO SHOWING THAT MOVING ONE TITLE 17 CAUSES ANY OTHER TITLE TO MOVE. 18 AND MURPHY 8. 19 TITLES. 20 THAT'S THE POINT OF MURPHY 7 THERE IS ENORMOUS VARIATION BETWEEN AND AMONG AND THE THIRD POINT IS THEY SIMPLY HAVEN'T SHOWN THIS 21 RIPPLE EFFECT OR HOW THE HECK IT WOULD WORK. 22 WHAT DO YOU HAVE TO SHOW CAUSATION? 23 IS YOUR THEORY OF PROPAGATION? 24 25 WE KEEP ASKING, WHAT DO YOU HAVE -- WHAT THEY DON'T REALLY HAVE A THEORY OF PROPAGATION BECAUSE THERE'S NO EVIDENCE OF IT, THERE'S NO ANECDOTES OF IT EITHER UNITED STATES COURT REPORTERS 159 160 1 BEFORE, DURING, OR AFTER THE CLASS PERIOD. 2 THIS RIPPLE THEORY IS A MADE UP THEORY THAT THE EVIDENCE 3 WILL NOT SUPPORT, AND WITHOUT THAT, WITHOUT THAT, THEY CAN'T 4 SHOW CLASS-WIDE INJURY. 5 MY FINAL POINT, YOUR HONOR, IS JUST APPENDIX B. 6 TITLES, 60,000 CLASS MEMBERS. 7 AMONG ALL THE CLASSES IN THE UNITED STATES. 8 2400 AN ENORMOUS CLASS FOR ANY WAGE SUPPRESSION CASE. 9 IT'S NOT THAT THAT'S A BIG CLASS IT'S THAT THAT'S REED SAID 19,000, TOO MANY. 10 FLEISHMAN, EVEN LESS THAN THAT, TOO MANY. 11 WEISFELDT, LESS THAN THAT, TOO MANY. 12 AND THE REASON IS THAT WHEN YOU HAVE THIS MUCH DISPARITY 13 AND DIFFERENCE BETWEEN AND AMONG THESE TYPES OF JOBS, THERE IS 14 NO WAY TO SHOW THAT IMPACT ON SOME OF THEM WOULD HAVE IMPACTED 15 ALL OR NEARLY EVERYONE, ESPECIALLY WHEN THEY'RE SWINGING FOR 16 THE FENCE WITH A 2400 TITLE PROPOSED CLASS. 17 IT IS UNWORKABLE. IT IS UNPRECEDENTED. THEY CAN'T POINT 18 TO A SINGLE CASE WHERE ANYTHING EVEN APPROACHING THIS WAS 19 CERTIFIED, NOT ONE. 20 21 22 THEY HAVEN'T CITED ONE. THERE ISN'T ONE BECAUSE THE CASES THAT ARE ANYWHERE NEAR THIS ARE ALL CASES DENYING CLASS CERT. AND THAT'S WHY WE EMPHASIZE REED, WEISFELDT, FLEISHMAN AND 23 THE LIKE. 24 DOESN'T TELL YOU ANYTHING, AND YOU CAN'T RUN A CLASS ACTION IN 25 THIS WAY. THEY ALL RECOGNIZE WHAT WE RECOGNIZE, THAT AVERAGING UNITED STATES COURT REPORTERS 160 161 1 2 3 LET'S SAY NO AND GET ON TO A MORE REASONABLE WAY OF DOING THIS AND FIGURE OUT A BETTER WAY TO RESOLVE THESE CLAIMS. THANKS FOR YOUR ATTENTION, YOUR HONOR. 4 5 THE COURT: MUCH. ALL RIGHT. I REALLY APPRECIATE IT. 6 MR. GLACKIN: 7 MR. VAN NEST: 8 WELL, THANK YOU ALL VERY THANKS FOR YOUR PATIENCE TODAY. THANK YOU, YOUR HONOR. THANK YOU, YOUR HONOR. (THE PROCEEDINGS IN THIS MATTER WERE CONCLUDED.) 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 UNITED STATES COURT REPORTERS 161 1 2 CERTIFICATE OF REPORTER 3 4 5 6 7 I, THE UNDERSIGNED OFFICIAL COURT REPORTER OF THE UNITED 8 STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA, 9 280 SOUTH FIRST STREET, SAN JOSE, CALIFORNIA, DO HEREBY 10 11 CERTIFY: THAT THE FOREGOING TRANSCRIPT, CERTIFICATE INCLUSIVE, IS 12 A CORRECT TRANSCRIPT FROM THE RECORD OF PROCEEDINGS IN THE 13 ABOVE-ENTITLED MATTER. 14 15 17 _______________________________ LEE-ANNE SHORTRIDGE, CSR, CRR CERTIFICATE NUMBER 9595 18 DATED: 16 AUGUST 19, 2013 19 20 21 22 23 24 25 UNITED STATES COURT REPORTERS 162 1 1 UNITED STATES DISTRICT COURT 2 NORTHERN DISTRICT OF CALIFORNIA 3 SAN JOSE DIVISION 4 5 6 IN RE: HIGH-TECH EMPLOYEE ANTITRUST LITIGATION, 7 8 _________________________ 9 THIS DOCUMENT RELATES TO: ALL ACTIONS _________________________ 10 ) ) ) ) ) ) ) ) ) ) C-11-02509 LHK SAN JOSE, CALIFORNIA JANUARY 17, 2013 PAGES 1-153 11 12 13 TRANSCRIPT OF PROCEEDINGS BEFORE THE HONORABLE LUCY H. KOH UNITED STATES DISTRICT JUDGE 14 15 A P P E A R A N C E S: 16 FOR THE PLAINTIFFS: 17 18 JOSEPH SAVERI LAW FIRM BY: JOSEPH SAVERI LISA J. LEEBOVE JAMES G. DALLAL 255 CALIFORNIA STREET, SUITE 450 SAN FRANCISCO, CALIFORNIA 94111 19 20 21 22 23 24 25 LIEFF, CABRASER, HEIMANN & BERNSTEIN BY: KELLY M. DERMODY BRENDAN P. GLACKIN DEAN M. HARVEY ANNE B. SHAVER 275 BATTERY STREET, 30TH FLOOR SAN FRANCISCO, CALIFORNIA 94111 APPEARANCES CONTINUED ON NEXT PAGE OFFICIAL COURT REPORTER: LEE-ANNE SHORTRIDGE, CSR, CRR CERTIFICATE NUMBER 9595 UNITED STATES COURT REPORTERS 163 2 1 2 APPEARANCES (CONTINUED) 3 4 FOR DEFENDANT APPLE: 5 6 7 8 FOR DEFENDANT LUCASFILM: 9 O'MELVENY & MYERS BY: GEORGE A. RILEY MICHAEL F. TUBACH CHRISTINA J. BROWN TWO EMBARCADERO CENTER 28TH FLOOR SAN FRANCISCO, CALIFORNIA 94111 KEKER & VAN NEST BY: DANIEL PURCELL 633 BATTERY STREET SAN FRANCISCO, CALIFORNIA 94111 10 11 FOR DEFENDANT GOOGLE: MAYER BROWN BY: LEE H. RUBIN DONALD M. FALK ANNE SELIN TWO PALO ALTO SQUARE, SUITE 300 PALO ALTO, CALIFORNIA 94306 FOR DEFENDANTS ADOBE AND INTUIT: JONES DAY BY: ROBERT A. MITTELSTAEDT CRAIG E. STEWART DAVID C. KIERNAN LYNN WONG 555 CALIFORNIA STREET 26TH FLOOR SAN FRANCISCO, CALIFORNIA 94104 FOR DEFENDANT INTEL: BINGHAM MCCUTCHEN BY: FRANK M. HINMAN DONN P. PICKETT SUJAL SAHW 1117 S. CALIFORNIA AVENUE PALO ALTO, CALIFORNIA 94304 FOR DEFENDANT PIXAR: COVINGTON & BURLING BY: EMILY J. HENN DEBORAH A. GARZA 333 TWIN DOLPHIN DRIVE, SUITE 700 REDWOOD SHORES, CALIFORNIA 94065 12 13 14 15 16 17 18 19 20 21 22 23 24 25 UNITED STATES COURT REPORTERS 164 3 1 SAN JOSE, CALIFORNIA 2 3 JANUARY 17, 2013 P R O C E E D I N G S (COURT CONVENED AND THE FOLLOWING PROCEEDINGS WERE HELD:) 4 THE COURT: GOOD AFTERNOON AND WELCOME. 5 THE CLERK: YOU MAY BE SEATED. 6 CALLING CASE NUMBER C-11-02509 LHK, IN RE: HIGH-TECH 7 EMPLOYEE ANTITRUST LITIGATION. 8 THE COURT: 9 10 WOULD YOU LIKE TO STATE YOUR APPEARANCES? MR. GLACKIN: BRENDAN GLACKIN, LEIFF, CABRASER, 11 HEIMANN & BERNSTEIN. 12 MR. HARVEY, AND MS. SHAVER. 13 14 15 I'M WITH MY COLLEAGUES MS. DERMODY, ALSO JOINING US IN THE COURTROOM IS PLAINTIFF MICHAEL DIVINE SEATED IN THE FRONT ROW. MR. SAVERI: GOOD AFTERNOON, JUDGE KOH. 16 JOSEPH SAVERI, JOSEPH SAVERI LAW FIRM IN SAN FRANCISCO, AND 17 JAMES DALLAL AND LISA LEELOVE. 18 THE COURT: 19 MR. MITTELSTAEDT: OKAY. GOOD AFTERNOON. AND YOUR HONOR, FOR DEFENDANTS, 20 BOB MITTELSTAEDT OF JONES DAY FOR ADOBE AND INTUIT, AND WITH ME 21 ARE LYNN WONG, DAVID KIERNAN, AND CRAIG STEWART. 22 THE COURT: SO NOT EVERYONE IS ON THIS LIST. 23 THE CLERK: I WAS TOLD THEY WERE. 24 THE COURT: YOU SAID LYNN WONG AND GREG STEWART? 25 OKAY. OR CRAIG STEWART? UNITED STATES COURT REPORTERS 165 4 1 MR. MITTELSTAEDT: 2 THE COURT: 3 MR. PURCELL: 4 CRAIG STEWART. CRAIG STEWART. OKAY, THANK YOU. GOOD AFTERNOON, YOUR HONOR. DAN PURCELL OF KEKER & VAN NEST FOR LUCASFILM. 5 THE COURT: OKAY. GOOD AFTERNOON. 6 MR. PICKETT: 7 DONN PICKETT OF BINGHAM MCCUTCHEN. 8 INTEL, ALONG WITH FRANK HINMAN AND SUJAL SHAW. GOOD AFTERNOON, YOUR HONOR. I'M I'M HERE ON BEHALF OF 9 THE COURT: OKAY. GOOD AFTERNOON. 10 MR. RUBIN: GOOD AFTERNOON, YOUR HONOR. LEE RUBIN 11 FROM MAYER BROWN. WITH ME TODAY IS MY PARTNER, DON FALK FROM 12 MAYER BROWN, AND ANNE SELIN, AND ANNE SELIN IS PROBABLY NOT ON 13 THE LIST. 14 THE COURT: OKAY. AND THE LAST NAME IS SPELLED? 15 MR. RUBIN: SELIN, S-E-L-I-N. 16 THE COURT: S-E-L-I-N. 17 MR. RUBIN: THANK YOU. 18 MS. HENN: OKAY, THANK YOU. GOOD AFTERNOON, YOUR HONOR. EMILY HENN, 19 AND MY COLLEAGUE DEBORAH GARZA, OF COVINGTON & BURLING ON 20 BEHALF OF PIXAR. 21 THE COURT: OKAY. GOOD AFTERNOON. 22 MR. RILEY: GOOD AFTERNOON, YOUR HONOR. 23 GEORGE RILEY OF O'MELVENY & MYERS. 24 MICHAEL TUBACH, AND MY OTHER COLLEAGUE, CHRISTINA BROWN. 25 THE COURT: OKAY. I'M JOINED BY MY COLLEAGUE, GOOD AFTERNOON. UNITED STATES COURT REPORTERS SO HAS EVERYONE 166 5 1 STATED THEIR APPEARANCES? 2 OKAY. 3 THE CMC SECOND. 4 5 6 OKAY. ALL RIGHT. THANK YOU. LET'S HANDLE THE CLASS CERT MOTION FIRST AND THEN AND WHY DON'T WE START WITH THE PLAINTIFFS? WELL, ACTUALLY, I'M SORRY, LET MET START WITH THE DEFENDANTS FIRST. I JUST WANT TO NARROW THE SCOPE OF WHAT'S AT ISSUE TODAY. 7 I DIDN'T SEE IN YOUR OPPOSITION REALLY ANYTHING CHALLENGING 8 OTHER THAN -- ANY CLASS CERTIFICATION REQUIREMENT OTHER THAN 9 PREDOMINANCE. IS THAT CORRECT? 10 MR. MITTELSTAEDT: PREDOMINANCE AND SUPERIORITY. 11 THE COURT: SO ARE YOU CONCEDING NUMEROSITY OKAY. 12 AND ALL THE OTHER RULE 23 REQUIREMENTS? 13 MR. MITTELSTAEDT: FOR PURPOSES OF THIS MOTION, YES. 14 THE COURT: SO IT'S ONLY PREDOMINANCE AND 15 SUPERIORITY. 16 HAVE TO COVER. 17 OKAY. 18 OKAY. OKAY. THANK YOU. THAT HELPS US NARROW WHAT WE LET ME GO, PLEASE, TO THE PLAINTIFFS, AND I FIRST JUST WANT TO MAKE SURE THAT I UNDERSTAND WHAT YOUR THEORY IS. 19 MR. GLACKIN: 20 THE COURT: OKAY. SO IF YOU COULD, PLEASE, THERE ARE 21 CERTAIN FIGURES THAT I'D LIKE YOU TO PLEASE EXPLAIN OR 22 ELABORATE IN DR. LEAMER'S REPORT IN SUPPORT OF THE MOTION. 23 MR. GLACKIN: 24 THE COURT: 25 SURE. SO LET ME SEE IF I UNDERSTAND THE INTERNAL EQUITY THEORY THAT YOU ARE ALLEGING. UNITED STATES COURT REPORTERS 167 6 1 IS IT YOUR ASSERTION THAT ALL OF THE COMPENSATIONS FOR ALL 2 OF THE WORKERS ARE SOMEHOW LINKED, SO IF THERE'S ANY CHANGE IN 3 ONE, IT SHOULD HAVE SOME TYPE OF TRICKLE DOWN OR SOME SHADOWING 4 EFFECT ON THE OTHER EMPLOYEES OF THE SAME COMPANY? 5 RIGHT? 6 7 8 MR. GLACKIN: IS THAT YEAH, I WOULD SAY THAT'S BASICALLY CORRECT, YOUR HONOR. WE -- DR. LEAMER, TO BEGIN SPEAKING ABOUT THEORY, HE 9 PROPOSES THAT IF THE -- THAT GIVEN THE RECOGNIZED THEORY OF 10 INTERNAL EQUITY, THAT GAINS TO PART OF A WORK FORCE WILL BE 11 SHARED WITH OTHER MEMBERS OF THE SAME WORK FORCE. 12 WOULD PUT IT. 13 THAT'S HOW I IT'S A SHARING OF GAINS. SO IT'S NOT -- YOU KNOW, ANOTHER KIND OF SHARING, OR OF 14 LINKING THAT YOU COULD TALK ABOUT IN AN ECONOMICS MATTER WOULD 15 BE, FOR EXAMPLE, A SUPPLY AND DEMAND SIDE SUBSTITUTION. 16 COULD SAY, FOR EXAMPLE, THE PRICE OF A AND THE PRICE OF B ARE 17 LINKED BECAUSE IF YOU MODIFY THE PRICE OF A, OR THE SUPPLY OF 18 A, SUPPLY AND DEMAND SIDE SUBSTITUTION FORCES ARE GOING TO DO 19 SOMETHING TO THE PRICE OF B AS A MATTER OF SUPPLY AND DEMAND. 20 THE COURT: 21 MR. GLACKIN: YOU SO LET ME ASK YOU -THAT'S ONE KIND OF LINK. 22 DIFFERENT KIND OF LINKING. 23 THAT'S A LINKING. 24 25 THE COURT: THAT'S WHAT I THINK OF MORE AS AND I'M SORRY TO INTERRUPT YOU. I CAN UNDERSTAND THE SHARING OF GAINS IN TERMS OF EXAMPLES THAT ARE UNITED STATES COURT REPORTERS 168 7 1 BRIEFED, LIKE A PIXAR MOVIE DOES VERY WELL SO EVERYONE GETS, 2 ACROSS THE BOARD, RECEPTION TO PRESIDENTS GET A SORT OF BONUS 3 IN THAT YEAR. 4 BUT THIS IS A SHARING OF PAIN AND NOT A SHARING OF GAIN. 5 SO WHAT SAYS THAT IF THERE'S A SUPPRESSION OF GAIN IN ONE SORT 6 OF JOB FIELD THAT THAT WOULD NECESSARILY RESULT -- AND I GUESS 7 I'M HAVING A DIFFICULTY VISUALIZING WHY THE CATEGORY OF SOU 8 CHEFS' SALARIES WOULD NECESSARILY IMPACT THE CATEGORY OF 9 ADMINISTRATIVE ASSISTANTS THAT WOULD NECESSARILY IMPACT THE 10 11 CATEGORY OF AN ANIMATOR VERSUS A SOFTWARE ENGINEER. DO YOU SEE WHAT I'M SAYING? WHY CAN'T THOSE BE ON 12 SEPARATE TRACKS? 13 ALREADY ORGANIZED BY FAMILIES ANYWAY. 14 TO ACTUALLY BE INTERLINKED? 15 GROUND? 16 I KNOW THAT YOU HAVE SOME DATA THAT THEY'RE MR. GLACKIN: WHY DO THE FAMILIES HAVE CAN'T THEY ALL JUST BE ON SEPARATE WELL, SO THE -- THE ANSWER I WOULD 17 GIVE TO THAT IS THAT, FIRST OF ALL, WE ARE NOT TALKING ABOUT A 18 SHARING -- WE'RE TALKING ABOUT A SHARING OF PAIN IN THE SENSE 19 OF A SHARING OF TALKING ABOUT DAMAGES, BUT WE ACTUALLY ARE 20 REALLY TALKING ABOUT A SHARING OF GAIN BECAUSE WE'RE TALKING 21 ABOUT WHAT WOULD HAVE HAPPENED IN THE WORLD THAT DOESN'T EXIST, 22 WHICH IS THE WORLD WHERE THESE AGREEMENTS WERE NEVER REACHED. 23 AND WE'RE SAYING THAT IN THAT WORLD, THERE WOULD HAVE BEEN 24 COMPETITIVE GAINS THAT WOULD HAVE, IN SOME RESPECTS, BEEN 25 FOCUSSED ON INDIVIDUALS OR GROUPS OF EMPLOYEES, BUT THAT THE UNITED STATES COURT REPORTERS 169 8 1 EFFECT OF THOSE GAINS WOULD HAVE BEEN WIDELY FELT ACROSS THE 2 WORK FORCES. 3 AND THERE'S -- YOU KNOW, I HEAR WHAT YOU'RE SAYING ABOUT, 4 OH, IT SORT OF DOESN'T -- IT'S SURPRISING THAT THE -- THAT WE 5 WOULD INCLUDE THE SOU CHEF, FOR EXAMPLE. 6 EXPLANATION FOR THAT? WHAT'S THE 7 AND I WOULD -- I GUESS I WOULD SAY THAT THE INTERNAL 8 EQUITY FRAMEWORK POSTULATES THAT THIS FEELING OF FAIRNESS WHICH 9 DRIVES A COMPANY'S NEED TO SHARE GAINS LIKE THIS CAN APPLY 10 COMPANY-WIDE. 11 APPLY WITH DIFFERENT STRENGTHS, CERTAINLY IN DIFFERENT 12 CONTEXTS. 13 14 IT CAN APPLY IN MANY DIFFERENT WAYS AND IT CAN BUT THERE IS A COMPANY-WIDE SENSE OF FAIRNESS THAT SAYS THAT, UNDER CERTAIN CIRCUMSTANCES, THE GAINS SHOULD BE SHARED. 15 AND PRACTICALLY SPEAKING, AND THIS IS ACTUALLY DISCUSSED, 16 I BELIEVE, IN THE AKER -- I BELIEVE WE CITED GEORGE AKERLOF'S 17 ARTICLE, THE FAIR WAGE HYPOTHESIS. 18 THE THINGS THAT HE STUDIES THERE, OR DISCUSSES, IS RESEARCH ON 19 SHARING OF GAINS BETWEEN EMPLOYEES WITH VASTLY DIFFERENT SKILL 20 SETS. HE SAYS -- I MEAN, ONE OF SO THAT'S THE -- THAT'S THE THEORY. 21 AND THEN THE FACT OF HOW COMPENSATION WAS SET AT THESE 22 COMPANIES ALSO IS CONSISTENT AND IN LINE WITH THE PREDICTION 23 THAT AT LEAST SOME LEVEL OF THESE GAINS WOULD BE SHARED 24 COMPANY-WIDE, AND THAT FACT IS THAT THEY ALL USE ADMINISTRATIVE 25 PAY SYSTEMS, THEY SET COMPANY-WIDE COMPENSATION BUDGETS, THEY UNITED STATES COURT REPORTERS 170 9 1 SET COMPANY-WIDE RAISE BUDGETS. 2 THAT THEY MAKE IN THEIR DECLARATIONS AND IN THEIR PAPERS. 3 THIS IS ACTUALLY AN ARGUMENT AND THERE'S -- IT'S -- IF THE COMPANY COMPENSATION BUDGET 4 GOES UP BECAUSE MANAGERS ARE COMPLAINING THAT THEY NEED MORE 5 MONEY TO SATISFY THEIR EMPLOYEES OR BECAUSE THE CEO IS 6 CONCERNED ABOUT COMPETITION HE'S FACING FROM ONE OF THESE OTHER 7 COMPANIES WITH WHICH, IN THE REAL WORLD, HE HAD AN AGREEMENT SO 8 HE WASN'T CONCERNED ABOUT THAT, THAT COULD MOVE THE WHOLE PAY 9 STRUCTURE. IT COULD MOVE SALARY BANDS. IT COULD INFLUENCE 10 COMPANIES' DECISIONS ABOUT WHERE TO SET MINIMUM AND MAXIMUM 11 SALARIES FOR JOB TITLES. 12 DECISIONS ABOUT -- 13 THE COURT: IT WOULD INFLUENCE COMPANIES' AND I'M SORRY TO INTERRUPT YOU. I CAN 14 UNDERSTAND HOW WITHIN THE SAME JOB FAMILY CO-WORKERS MIGHT TALK 15 AND FIND OUT, "WHAT ARE YOU MAKING? 16 WHAT OFFER DID YOU GET?" BUT WHAT IS THE EVIDENCE THAT THE SOU CHEF IS TALKING TO 17 THE ANIMATOR IS TALKING TO SOME OTHER, YOU KNOW, CO-WORKER FROM 18 A COMPLETELY DIFFERENT JOB FAMILY AND THAT THERE'S SORT OF THIS 19 EQUITY CONCERN -- 20 MR. GLACKIN: 21 THE COURT: 22 MR. GLACKIN: UM-HUM. -- ACROSS JOB FAMILIES? SO I DON'T THINK THERE'S EVIDENCE -- I 23 MEAN, TO ANSWER YOUR QUESTION DIRECTLY, I DON'T THINK THERE'S 24 EVIDENCE THAT THE SOU CHEF IS TALKING TO THE CEO'S A.A., FOR 25 EXAMPLE. UNITED STATES COURT REPORTERS 171 10 1 THE COURT: UM-HUM. 2 MR. GLACKIN: I THINK THAT WHAT WE'VE -- WHAT WE'VE 3 POSTULATED AND WE WOULD SAY WHAT WE'VE DEMONSTRATED IS THAT 4 THIS INFORMATION -- THERE'S AN INFORMATION NETWORK THAT 5 CONNECTS THESE EMPLOYEES. 6 RECEIVES THE INFORMATION TO TALK TO PEOPLE IN OTHER JOB 7 FAMILIES. 8 9 IT DOESN'T REQUIRE THE EMPLOYEE WHO THE INFORMATION COMES INTO THE NETWORK AND IT IS -- IT IS SPREAD AND THE FORCE OF -- AND THE FORCE OF INTERNAL EQUITY 10 CAUSES THE COMPETITIVE EFFECT TO BE SHARED TO SOME LEVEL ACROSS 11 THE ENTIRE WORK FORCE, OR IT CAN. 12 AND A CONCRETE EXAMPLE OF THIS IS THE GOOGLE PAY RAISE IN 13 RESPONSE TO AGGRESSIVE RECRUITING BY FACEBOOK. 14 WAS A -- THAT WAS -- THAT'S AN EXAMPLE OF AGGRESSIVE RECRUITING 15 BY A SINGLE COMPANY THAT MOVED AN ENTIRE PAY STRUCTURE BY 10 16 PERCENT FROM SOU CHEFS TO SECRETARIES. 17 I MEAN, THAT SO THIS IS NOT -- I MEAN, WE BELIEVE THAT -- I MEAN, THIS 18 IS SOUND ECONOMIC THEORY AND I DON'T THINK THERE'S A DISPUTE 19 ABOUT THAT AT THIS POINT. 20 THERE'S ALSO NOT REALLY A DISPUTE THAT THESE DEFENDANTS 21 USE ADMINISTRATIVE PAY STRUCTURES AND THAT THEY SET THEIR 22 COMPENSATION THE WAY EVERY OTHER MAJOR COMPANY IN THE WORLD 23 SETS IT. 24 25 AND THEN WE ALSO HAVE DOCUMENTARY EVIDENCE THAT DIRECTLY -- AND THERE'S A FEW INSTANCES OF THIS THAT WE CITED UNITED STATES COURT REPORTERS 172 11 1 IN THE BRIEF -- THAT DIRECTLY LINKS COMPETITION, AGGRESSIVE 2 COMPETITION BY A SINGLE FIRM TO EITHER CONCERN ABOUT THE PAY 3 STRUCTURE MOVING IN THE CASE OF SOME OF THE PIXAR E-MAILS WE'VE 4 CITED, OR TO AN ACTUAL ENORMOUS, $500 MILLION MOVEMENT OF THE 5 PAY STRUCTURE, WHICH IS WHAT GOOGLE DID. 6 THE COURT: LET ME ASK YOU, SINCE WE'RE 7 UNFORTUNATELY LIMITED IN TERMS OF DOCUMENTARY EVIDENCE, WHAT 8 EVIDENCE IS THERE ABOUT WHAT TYPE OF EMPLOYEES OR WHAT TYPE OF 9 JOB FAMILIES RECEIVE COLD CALLS GENERALLY? 10 MR. GLACKIN: WELL, THAT IS AN EXCELLENT QUESTION, 11 AND AS -- I MEAN, DR. LEAMER SAID, I WOULD COUNT NO FEWER THAN 12 20 TIMES IN HIS DEPOSITION, THAT HE WOULD HAVE LOVED TO HAVE 13 HAD RELIABLE DATA ABOUT THE COLD CALLING, AND THE PROBLEM IS IT 14 JUST DIDN'T EXIST. 15 HAVE. 16 17 18 I MEAN, WE CAN ONLY WORK WITH THE DATA WE I'M ALMOST TEMPTED TO QUOTE DEFENSE SECRETARY ROSENFELD, YOU GO TO WAR WITH THE DATA THAT YOU HAVE. AND THE DEFENDANTS DON'T DISPUTE THAT. THERE'S NO 19 ANALYSIS OF THE COLD CALLING DATA BY DR. MURPHY EITHER. 20 WHY HE'S, WE WOULD SAY WRONGLY, BUT HE'S USING THIS PROXY 21 APPROACH BASED ON INTER-DEFENDANT HIRING, WHICH IS EVIDENCE 22 THAT WE DEVELOPED USING UNIQUE EMPLOYEE IDENTIFIERS. 23 THAT'S BUT THERE'S NO -- THERE IS NO EVIDENCE IN THIS CASE ABOUT 24 HOW THAT COLD CALLING -- THERE'S NO RELIABLE EVIDENCE, I SHOULD 25 SAY, NO RELIABLE STATISTICAL EVIDENCE ABOUT HOW THAT COLD UNITED STATES COURT REPORTERS 173 12 1 2 CALLING WAS CONCENTRATED, IF AT ALL, TO DIFFERENT EMPLOYEES. I MEAN, I WILL SAY, YOU MENTIONED SOU CHEF. THERE IS A 3 DOCUMENT IN THIS CASE THAT, YOU KNOW, DISCUSSES BEING CONCERNED 4 ABOUT LOSING A SOU CHEF. 5 THE COURT: YEAH. 6 MR. GLACKIN: SO DEFINITELY THERE'S NO DOUBT THAT 7 SOU CHEFS WERE WITHIN THE SCOPE OF THESE AGREEMENTS, SO I JUST 8 WANTED TO MENTION THAT IN CASE IT HAD SLIPPED YOUR MIND. 9 10 11 THE COURT: NO. THAT'S WHAT PROMPTED THE QUESTION ACTUALLY. SO LET ME ASK, I COMPLETELY AGREE WITH YOU THAT THE 12 AGREEMENTS ARE EXPLICITLY NOT RESTRICTED BY JOB FAMILY, 13 GEOGRAPHY, THEY'RE NOT LIMITED BY ANYTHING. 14 EMPLOYEE CANNOT BE COLD CALLED, COUNTER-OFFERED, OR HIRED 15 WITHOUT GETTING CONSENT OF THE CURRENT EMPLOYER. 16 THEY APPLY TO ANY BUT DOESN'T IT SEEM THAT, OVERALL, THE PRIMARY CONCERN OF 17 THESE CEO'S WAS THE TOP TALENT, AND SPECIFICALLY THE TOP 18 TECHNICAL TALENT? 19 LIKE THEY WERE OKAY ABOUT THE ADMINISTRATIVE ASSISTANT 20 FROM PIXAR. 21 REALLY DON'T WANT THE TOP TECHNICAL TALENT LEAVING. 22 THEY'RE OKAY REALLY ABOUT THE SOU CHEF. MR. GLACKIN: BUT THEY I MEAN, I WOULD -- SO FIRST OF ALL, I 23 WOULD HASTEN TO ADD THAT WE HAVEN'T ACTUALLY DEPOSED ANY OF THE 24 CEO'S YET, SO THE DISCOVERY RECORD IS STILL OPEN ON WHAT THEY 25 THINK. UNITED STATES COURT REPORTERS 174 13 1 I WOULD SAY THAT THERE IS CERTAINLY SOME EVIDENCE IN THE 2 RECORD, AND WE CITED IT I BELIEVE ON THE LAST PAGE, OR LAST TWO 3 PAGES OF OUR OPENING BRIEF, WHICH IS WHERE WE ALSO DISCUSSED -- 4 WE EXPLAINED WHY WE PROPOSED A POSSIBLE ALTERNATIVE CLASS. 5 THERE IS SOME EVIDENCE OF THEM BEING CONCERNED ABOUT THAT; 6 THERE'S ALSO EVIDENCE OF THEM BEING CONCERNED ABOUT THE ENTIRE 7 PAY STRUCTURE; AND THEN THERE IS ALSO EVIDENCE OF THEM BEING 8 CONCERNED ABOUT THE SOU CHEF, I MEAN, FIGURATIVELY SPEAKING. 9 10 11 12 13 14 15 SO I WOULD AGREE THAT THERE IS SOME EVIDENCE OF THE KIND THAT YOU DESCRIBE. BUT I WOULD ALSO AGREE -- SAY THAT THERE'S EVIDENCE THAT THEY WERE CONCERNED ABOUT OTHER THINGS. THE COURT: OKAY. THANK YOU. LET ME GO TO THE DEFENDANTS. WHY DIDN'T YOUR CLIENTS RESTRICT THESE AGREEMENTS TO 16 SPECIFIC TYPES OF EMPLOYEES? AND THERE'S CERTAINLY DOCUMENTARY 17 EVIDENCE WHERE -- I CAN'T RECALL WHO THE COMPANY WAS -- BUT I 18 KNOW STEVE JOBS WAS INVOLVED WHERE THEY TRIED TO NARROW THE 19 CLASS OF EMPLOYEES WHO COULDN'T BE SOLICITED, OR I SHOULD SAY 20 CLASS EMPLOYEES, AND THE AGREEMENT WAS, NO, JUST ANY EMPLOYEE. 21 DON'T CONTACT THEM. 22 SO YOU TELL ME, WHY SHOULD THERE BE ANY FURTHER 23 RESTRICTION WHEN THE AGREEMENT IS PRETTY EXPLICIT THAT IT 24 APPLIES TO ANY EMPLOYEE, AND THERE'S CERTAINLY E-MAILS WITH 25 STEVE JOBS AND OTHER CEO'S NOT LIMITING IT TO ANY PARTICULAR UNITED STATES COURT REPORTERS 175 14 1 TYPE OF EMPLOYEE. 2 MR. MITTELSTAEDT: I THINK, YOUR HONOR, THE ISSUE IS 3 WHO WAS IMPACTED. 4 IMPACTED, WHO WOULD HAVE RECEIVED A RAISE, WHO WOULD HAVE GONE 5 TO ANOTHER JOB IF THEY HAD RECEIVED A CALL. 6 NOT JUST WHO DIDN'T GET A CALL, BUT WHO WAS IN THE CASES THAT WE'VE CITED, REED, WEISFELD, MPT, AND 7 JOHNSON, THE AGREEMENTS THERE WERE BROAD RANGING. SOME OF 8 THOSE CASES INVOLVED JUST NURSES, AND IN REED, FOR EXAMPLE, THE 9 COURT SAID THE QUESTION IS, IS THERE IMPACT ON THE NURSES 10 ACROSS THE BOARD AND DOES THE PLAINTIFF HAVE A METHOD OF 11 PROVING IMPACT ACROSS THE BOARD? 12 AND WHAT THE COURT FOUND IN REED, LIKE THE OTHER CASES, IS 13 THAT IF THE PLAINTIFFS HAVE TO GO PERSON BY PERSON, DEPARTMENT 14 BY DEPARTMENT, COMPANY BY COMPANY, TO DETERMINE WHO WAS 15 IMPACTED, NOT JUST WHO WAS WITHIN THE SCOPE OF WHETHER IT'S A 16 NO HIRING -- 17 THE COURT: SO YOU CONCEDE THAT ALL EMPLOYEES WERE 18 IN THE SCOPE. 19 DEFINE THE CATEGORY OF EMPLOYEES THAT WERE ACTUALLY DAMAGED? 20 YOUR POSITION IS JUST THAT ONLY WHAT -- CAN YOU MR. MITTELSTAEDT: 21 CERTAINLY. 22 IT'S NOT WHAT CATEGORIES. 23 I'M MAKING THE LATTER POINT, AND IT'S, IN MY VIEW -- AND I'LL GET INTO THIS -IT'S INDIVIDUAL BY INDIVIDUAL. BUT ON THE FIRST POINT, THESE AGREEMENTS, TO THE EXTENT 24 THEY WERE ACTUAL AGREEMENTS, DIFFERED FROM COMPANY TO COMPANY 25 TO COMPANY, BOTH AS TO THE TERMS AND WHO THEY COVERED, SO I UNITED STATES COURT REPORTERS 176 15 1 CAN'T MAKE ANY BROAD GENERALIZATION ABOUT ALL OF THEM COVERED 2 EVERYBODY OR NONE OF THEM COVERED EVERYBODY. 3 TO BE TAKEN ONE BY ONE. 4 THEY REALLY NEED BUT -- 5 THE COURT: SO TELL ME, WHAT ARE THE CHARACTERISTICS 6 OF THE INDIVIDUALS THAT THE DEFENDANTS WOULD CONCEDE WERE 7 DAMAGED? 8 9 10 11 MR. MITTELSTAEDT: WELL, NONE OF THE NAMED PLAINTIFFS FIT THIS CATEGORY. BUT YOUR HONOR SAID, IN APRIL, AFTER READING THE COMPLAINT, AFTER SEEING THE PLAINTIFFS' THEORY -- 12 THE COURT: I DON'T WANT TO HEAR WHAT I SAID. I 13 WANT TO HEAR YOUR POSITION. 14 THE CHARACTERISTICS OF INDIVIDUALS THAT THE DEFENDANTS CONCEDE 15 WERE DAMAGED? 16 WHAT ARE -- HOW WOULD YOU DESCRIBE I DON'T WANT TO HEAR WHAT I SAID. MR. MITTELSTAEDT: OKAY. IT WOULD BE SOMEBODY WHO 17 WOULD HAVE RECEIVED A COLD CALL BUT FOR THE AGREEMENTS; WOULD 18 HAVE TAKEN THAT COLD CALL, TAKEN IT FAR ENOUGH DOWN THE ROAD TO 19 GET SOME SALARY INFORMATION; AND THEN WENT INTO HIS OR HER BOSS 20 AND SAID, "I'VE GOT AN OFFER FROM ANOTHER COMPANY AT A HIGHER 21 WAGE. WILL YOU NEGOTIATE AND GIVE ME A RAISE?" 22 AND THEN IF THAT -- IF THE MANAGER SAYS, "NO, ACTUALLY, I 23 DON'T WANT TO GIVE YOU A RAISE," THEN THAT PERSON HAS TO DECIDE 24 WHETHER THEY WOULD TAKE THE JOB AT THE COMPETING COMPANY. 25 IF THAT PERSON COULD SHOW THAT THEY WOULD HAVE RECEIVED A UNITED STATES COURT REPORTERS 177 16 1 CALL, IT WOULD HAVE LED TO A RAISE, THEN THEY COULD SAY THAT 2 THEY WERE DAMAGED BY AN AGREEMENT THAT KEPT THEM FROM GETTING 3 THE CALL. 4 5 6 THE COURT: AND THE DEFENDANTS CONCEDE THAT THERE ARE INDIVIDUALS LIKE THAT AT ALL OF YOUR CLIENTS' COMPANIES? MR. MITTELSTAEDT: 7 BEEN IDENTIFIED. 8 WELL, I DON'T THINK ANYBODY HAS THAT CATEGORY. 9 10 11 I KNOW THE NAMED PLAINTIFFS DON'T FIT INTO MR. DIVINE, FOR EXAMPLE, HE HELD SOME -THE COURT: AND I'VE READ ABOUT THE NAMED PLAINTIFFS, SO LET'S NOT GO THERE. 12 MR. MITTELSTAEDT: 13 THE COURT: OKAY. LET ME ASK -- THERE IS NINTH CIRCUIT 14 CASE LAW THAT SAYS DAMAGE CALCULATIONS SHOULD NOT DEFEAT CLASS 15 CERTIFICATION, BUT IT SEEMS LIKE THAT'S THE CRUX OF YOUR 16 OPPOSITION IS THAT YOU'RE SAYING THAT THE PLAINTIFFS NEED TO 17 SHOW INDIVIDUALIZED INJURY AND THEY CAN'T DO THAT, AND THEY 18 CAN'T DO A DAMAGES CALCULATION, THEREFORE, THEY CAN'T GET A 19 CLASS CERTIFIED. 20 21 22 DO YOU WANT TO RESPOND TO THAT? I'M THINKING OF YOKOYAMA. GO AHEAD, PLEASE. MR. MITTELSTAEDT: TO STATE AN ANTITRUST TRUST CAUSE 23 OF ACTION, THE PLAINTIFF NEEDS TO SHOW THAT THERE WAS A 24 VIOLATION, AND THAT'S WHAT THEY USE THEIR AGREEMENT -- THE 25 AGREEMENTS FOR. UNITED STATES COURT REPORTERS 178 17 1 THE COURT: AND LET ME ASK YOU, DO YOU FIGHT -- DO 2 YOU CONTEST THAT PRONG OF THE ANALYSIS? 3 MR. MITTELSTAEDT: 4 NOT FOR PURPOSES OF THIS MOTION -- 5 THE COURT: OKAY. 6 MR. MITTELSTAEDT: -- EXCEPT TO SAY THIS, YOUR 7 HONOR: 8 THAT THE D.O.J. DID NOT ALLEGE, YOU KNOW, THAT LOOKS LIKE IT'S 9 A COMMON ISSUE. 10 WHEN THEY ALLEGE AN OVERARCHING AGREEMENT, SOMETHING WHEN THEY GET INTO, YOU KNOW, AN AGREEMENT BY ADOBE WITH 11 APPLE, THAT IS A DIFFERENT ANALYSIS, A DIFFERENT INQUIRY AT 12 TRIAL, IF YOU WILL, THAN WHETHER THERE WAS AN AGREEMENT BETWEEN 13 PIXAR AND LUCASFILM. 14 15 AND SO, YOU KNOW, WHEN YOU LOOK AT JUST AN INDIVIDUAL -THE COURT: BUT I DIDN'T SEE THAT IN YOUR 16 OPPOSITION. I DIDN'T SEE YOU MAKING THAT ARGUMENT. 17 POINT ME TO -- I DIDN'T SEE YOU CHALLENGING THAT THERE WAS AN 18 ANTITRUST TRUST VIOLATION IN YOUR OPPOSITION. 19 MR. MITTELSTAEDT: 20 THE COURT: 21 22 CAN YOU AND THAT -- IF YOU DID, CAN YOU POINT ME TO IT? THAT'LL JUST HELP US WITH GETTING THE ORDER DRAFTED. MR. MITTELSTAEDT: NO. AND, YOUR HONOR, THAT -- 23 THAT'S BECAUSE THEY ARE ALLEGING THE OVERARCHING CONSPIRACY AND 24 YOUR HONOR LET THAT GO ON THE MOTION TO DISMISS. 25 THE COURT: UM-HUM. UNITED STATES COURT REPORTERS 179 18 1 MR. MITTELSTAEDT: 2 THE COURT: BUT AFTER -- SO THAT'S NOT BEING CHALLENGED? THE 3 FACT OF THE ANTITRUST VIOLATION IS NOT BEING CHALLENGED FOR 4 PURPOSES OF THIS CLASS CERT MOTION? 5 MR. MITTELSTAEDT: WELL, THE -- THE WAY I WOULD 6 PHRASE IT IS, ARE WE CONTESTING THAT THAT'S AN INDIVIDUAL ISSUE 7 OR A COMMON ISSUE? AND I'M -- I THINK THAT'S A COMMON ISSUE. 8 THE COURT: OKAY. 9 MR. MITTELSTAEDT: BUT THE SECOND ELEMENT OF AN 10 ANTITRUST LIABILITY CLAIM IS THAT THE PLAINTIFF SHOWS IMPACT ON 11 HIM OR HER OF THE VIOLATION, AND SO THAT'S BEFORE YOU GET TO 12 DAMAGES, THE AMOUNT OF DAMAGES. 13 THEY HAVE TO SHOW AN IMPACT. AND IN REED, AGAIN -- AND REED -- YOU KNOW, IF THERE'S A 14 SINGLE CASE THAT'S THE MOST IMPORTANT HERE, YOUR HONOR, I THINK 15 IT IS THE REED CASE. 16 AND IN THE REED CASE, THE COURT IS QUOTING FROM THE THIRD 17 CIRCUIT IN HYDROGEN PEROXIDE, AND IT SAYS, "IN ANTITRUST CASES, 18 IMPACT OFTEN IS CRITICALLY IMPORTANT FOR PURPOSES OF EVALUATING 19 THE PREDOMINANCE REQUIREMENT BECAUSE IT'S AN ELEMENT OF THE 20 CLAIM THAT MAY CALL FOR INDIVIDUAL AS OPPOSED TO COMMON PROOF." 21 AND SO WHAT WE'RE SAYING IS THAT THE ONLY WAY FOR THE 22 PLAINTIFFS TO SHOW IMPACT, NAMELY, THAT SOMEBODY WAS INJURED IN 23 HIS OR HER PROPERTY OR BUSINESS -- AND THAT'S, THAT'S WHAT THEY 24 NEED TO SHOW UNDER AN ANTITRUST VIOLATION -- IN ORDER TO SHOW 25 THAT, THEY HAVE TO GO INDIVIDUAL BY INDIVIDUAL. UNITED STATES COURT REPORTERS 180 19 1 THEY HAVE TO SHOW, YOU KNOW, WHO WOULD HAVE RECEIVED THE 2 COLD CALL, WHAT IT WOULD HAVE LED TO. 3 WOULD HAVE LED TO A PAY RAISE, EITHER AT THAT COMPANY OR AT 4 ANOTHER COMPANY. 5 AND THAT IS WHERE ALL THESE CASES HAVE SAID THAT'S AN 6 INDIVIDUAL QUESTION. 7 THE COURT: 8 9 10 THEY HAVE TO SHOW IT WOULD THERE HAVE BEEN AN IMPACT? I'M SORRY TO INTERRUPT YOU. WHAT IS THE DEFENDANTS' POSITION AS TO WHAT TYPES OF EMPLOYEES OR MAYBE JOB FAMILIES WOULD BE SUBJECT TO A COLD CALL? OR DO YOU HAVE A POSITION? 11 MR. MITTELSTAEDT: WELL, NOT REALLY. THAT'S WHAT I 12 SAID BEFORE, THAT ALL OF THE -- EACH OF THESE AGREEMENTS WAS 13 DIFFERENT. 14 THE COURT: UM-HUM. 15 MR. MITTELSTAEDT: EACH COMPANY WAS IN A DIFFERENT 16 POSITION. 17 EMPLOYEES. 18 SO I DON'T THINK IT CAN BE GENERALIZED. 19 20 21 SOME COMPANIES WERE LOOKING FOR A CERTAIN TYPE OF OTHERS WERE LOOKING FOR OTHER TYPES OF EMPLOYEES. BUT TO ME, YOUR HONOR, THE IMPORTANT POINT ISN'T THE SCOPE OF THE AGREEMENTS. IT'S WHO THEY CAN SHOW WAS IMPACTED. AND, YOU KNOW, THEY HAVE -- AND WE DON'T THINK THEY HAVE 22 COME UP WITH A METHOD TO SHOW, BY COMMON EVIDENCE ACROSS THE 23 BOARD, WHO WAS INJURED. 24 25 AND SO IF I CAN BE PERMITTED TO JUST SAY ONE THING THAT YOUR HONOR HAD SAID, BECAUSE IT'S -- I THINK IT GOES TO THE UNITED STATES COURT REPORTERS 181 20 1 HEART OF THIS. 2 AT THE START OF THIS CASE, YOUR HONOR TURNED TO THE 3 PLAINTIFFS AND SAID, YOU KNOW, THE CLASS OF EVERYBODY IS JUST 4 INTUITIVELY TOO BROAD. 5 AND YOUR HONOR SAID, "YOU NEED TO FIGURE OUT WHO WAS 6 IMPACTED, NOT WHO WAS IN THE SCOPE OF THE AGREEMENTS, BUT WHO 7 WAS IMPACTED." 8 AND THE PLAINTIFF SAID, IN APRIL, THAT THAT'S WHY THEY 9 NEEDED THE DATA, AND THEY SAY, "IT'S ONE OF THE QUESTIONS WE'RE 10 ASKING OUR ECONOMIST. 11 EMBEDDED IN OUR REQUEST FOR DATA." 12 IT'S ONE OF THE QUESTIONS THAT IS AND THEN IN JUNE WHEN THEY CAME BACK AND ASKED FOR MORE 13 TIME TO ANALYZE THE DATA, THEY SAID -- AND THIS IS AT PAGE 21 14 OF THE JUNE TRANSCRIPT -- "ONE OF THE THINGS WE NEED TO DO WITH 15 THE DATA IS TO LOOK AT IT AND SEE WHAT IMPACT. 16 THE DATA TO HELP ADDRESS THE VERY SPECIFIC QUESTION YOU'RE 17 ASKING, WHICH IS, WHAT'S THE CLASS IN THIS CASE?" 18 WE NEED TO GET THEY SAID, "WE DIDN'T HAVE ACCESS TO DATA AT THE START, 19 THEY DIDN'T HAVE ACCESS AT THE START, WE NEED THAT DATA TO HELP 20 ANSWER THAT QUESTION. 21 CERTIFICATION THAT'S GOING TO BE AS SPECIFIC AS WE CAN BASED ON 22 WHAT THE DATA SHOWS." WE'RE GOING TO MAKE A MOTION FOR CLASS 23 AND SO WE'VE GIVEN THEM 12 YEARS OF COMPENSATION DATA AND 24 IF THERE WERE ANYTHING TO THE CLAIM THAT WHEN -- AND FOUR OF IT 25 WAS BEFORE THE -- OR, YEAH, FOUR YEARS WAS BEFORE THE ALLEGED UNITED STATES COURT REPORTERS 182 21 1 VIOLATION PERIOD. 2 IF THERE WERE ANYTHING TO THEIR CLAIM THAT PEOPLE WOULD 3 GET COLD CALLS, THAT THE COLD CALLS WOULD LEAD TO A RAISE FOR 4 THAT PERSON AND THEN IT WOULD LEAD TO A RAISE FOR SOMEBODY 5 ELSE, EVEN WITHIN THE SAME DEPARTMENT, THERE WOULD BE AMPLE 6 EVIDENCE OF THAT IN THE DATA. 7 IT WOULD -- YOU KNOW, IF ALL THESE COMPANIES HAD THIS 8 INTERNAL EQUITY SYSTEM WHICH MEANT THAT A RAISE FOR ONE IS A 9 RAISE FOR EVERYBODY -- 10 THE COURT: OKAY. I'M SORRY. I'M GOING TO 11 INTERRUPT YOU, BECAUSE UNFORTUNATELY I HAVE A LONG LIST OF 12 TOPICS THAT I WANT TO COVER WITH YOU ALL. 13 MR. MITTELSTAEDT: SURE. 14 THE COURT: THANK YOU. 15 16 17 OKAY. OKAY. LET ME GO BACK TO THE PLAINTIFFS, AND WE'RE KIND OF STUCK ON COLD CALLING FOR A LITTLE WHILE. I GUESS I'M STILL BACK TO THE SAME ISSUE OF WHETHER THERE 18 SHOULD BE REFINEMENT OF THE CLASS, AND I GUESS THE QUESTION IS, 19 FIRST, WHETHER THERE SHOULD BE SOME NARROWING OF THE MARKET BY 20 EITHER GEOGRAPHY OR BY TYPE OF WORK. 21 QUESTION FIRST? 22 MR. GLACKIN: SURE. WOULD YOU ADDRESS THAT THAT'S TWO QUESTIONS. 23 IN TERMS OF GEOGRAPHY, THAT'S AN ISSUE THAT WE HAVE NOT 24 STUDIED AND THAT HAS NOT BEEN SUGGESTED BY THE DEFENDANTS AS 25 PROPER, SO AS I'M STANDING HERE, I DON'T HAVE AN OPINION AS TO UNITED STATES COURT REPORTERS 183 22 1 2 WHETHER OR NOT THAT WOULD BE SENSIBLE. I'M NOT AWARE OF ANY EVIDENCE THAT HOW THE DEFENDANTS' PAY 3 STRUCTURE OPERATED WAS SORT OF EXISTENTIALLY DIFFERENT 4 DEPENDING ON WHERE A WORKER WAS LOCATED. 5 HAVE PAID PEOPLE DIFFERENTLY BASED ON WHERE THEY WORK, I MEAN, 6 DIFFERENT ACTUAL AMOUNTS OF MONEY. 7 CERTAINLY THEY MAY BUT ALL OF THAT WOULD BE ACCOUNTED FOR IN THE DATA 8 ANALYSIS THAT WE'VE DONE. 9 SAY IT'S INCLUDED IN THAT INDIVIDUAL EMPLOYEE COMPENSATION 10 11 OR IT WOULD BE INCLUDED -- I SHOULD NUMBER. IN TERMS OF TYPE OF WORK, WE TOOK THE -- WE TOOK THE ISSUE 12 SERIOUSLY, YOUR HONOR, AND THAT'S WHY WE OFFERED THIS, WHAT 13 WE -- THE REASON WE OFFERED AN ALTERNATIVE CLASS THAT WE CALL 14 THE TECHNICAL CLASS IS BECAUSE WE WANTED TO DEMONSTRATE THAT IF 15 THERE WAS A CONCERN ABOUT COHESIVENESS, IF YOU WILL, FOR WANT 16 OF A BETTER TERM, THAT WE COULD MEET THAT CONCERN BY SIMPLY 17 LOOKING AT THE JOB TITLES OF -- USED BY THE DEFENDANTS AND 18 CALLING OUT PEOPLE WHO ARE WORKING IN SOFTWARE, TECHNICAL, AND 19 CREATIVE POSITIONS BASED ON A REVIEW OF THE JOB TITLES. 20 21 22 WE THINK THAT, AS I SAID, THAT THE IMPACT WAS BROADER THAN THAT. BUT IF YOUR HONOR HAD WHAT I WOULD CHARACTERIZE AS SORT OF 23 A COHESION CONCERN, THAT WE WOULD -- THAT'S -- THAT WE WOULD 24 PROPOSE IS THE BEST WAY TO ADDRESS IT. 25 OTHER IDEAS, BUT THAT WAS OUR IDEA. I'M OPEN TO HEARING UNITED STATES COURT REPORTERS 184 23 1 AND THEN IN TERMS OF -- JUST IN TERMS OF THE DATA AND ALL 2 THE THINGS THAT WERE SAID, WE REALLY WANTED THE COLD CALLING 3 DATA. 4 AND IT JUST DOESN'T EXIST AND THAT IS -- THAT IS SOMETHING WE 5 WERE AFTER AND WE DON'T HAVE IT. 6 ANSWER THE QUESTION OF HOW COLD CALLING WOULD HAVE BEEN 7 FOCUSSED. 8 9 WE REALLY WANTED RELIABLE DATA ABOUT THE COLD CALLING SO THAT IS WHY WE CAN'T BUT JUST TO GET BACK TO THE -THE COURT: IS THERE DEFINITE -- LET'S TALK ABOUT 10 YOUR TECHNICAL ALTERNATIVE CLASS. 11 INTERCHANGEABILITY THERE, LIKE WOULD INTUIT NEED AN ANIMATOR? 12 LIKE HOW -- 13 MR. GLACKIN: NO. IS THERE DEFINITE THERE'S -- I MEAN, I THINK -- AND 14 DR. LEAMER TESTIFIED TO THIS AT HIS DEPOSITION. 15 THESE -- THERE ARE MULTIPLE DIFFERENT -- IF YOU WERE GOING TO 16 DO A MARKET-WIDE ANALYSIS, THERE ARE MULTIPLE DIFFERENT MARKETS 17 AT ISSUE HERE. 18 THE COURT: 19 MR. GLACKIN: I MEAN, UM-HUM. AND, NO, I WOULD NEVER SAY THAT 20 EVERYONE IN THE TECHNICAL CLASS IS INTERCHANGEABLE, JUST AS I 21 WOULD NEVER SAY THAT EVERYBODY IN THE LARGER CLASS IS 22 INTERCHANGEABLE FROM A MARKET ANALYSIS STANDPOINT. 23 BUT, AGAIN, OUR WHOLE -- OUR WHOLE -- THE WHOLE THRUST OF 24 DR. LEAMER'S ANALYSIS HERE, AND ACROSS 130 PAGES, IS THAT A 25 TRADITIONAL MARKET ANALYSIS OF THIS CONDUCT IS THE WRONG WAY TO UNITED STATES COURT REPORTERS 185 24 1 LOOK AT A LABOR MARKET. 2 MARKET AND A RESTRICTION ON COMPETITIVE INFORMATION IN A LABOR 3 MARKET. 4 IT JUST DOESN'T APPLY TO A LABOR AND THERE'S -- I MEAN, I'M NOT GOING TO RECAPITULATE 5 EVERYTHING HE SAID, BUT THAT'S THE WHOLE POINT IS THAT THAT 6 INTERCHANGEABILITY QUESTION REALLY GOES TO A TROPE THAT IS NOT 7 APPLICABLE HERE. 8 9 THE COURT: CONSPIRACY THEN? SO DOES THAT UNDERMINE THE OVERARCHING DOES THAT RE-ENFORCE THAT THE BILATERAL 10 AGREEMENTS WERE REALLY REFLECTING THE RELEVANT MARKET FOR 11 EMPLOYEES, LIKE THE TWO COMPANIES THAT WOULD ACTUALLY COMPETE 12 FOR THE SAME WORKERS ENTERED INTO A BILATERAL AGREEMENT AND 13 THERE WOULDN'T KIND OF BE THE SORT OF OVERARCHING, YOU KNOW, 14 INTUIT NEEDS A PIXAR PERSON AND SORT OF ALL THAT, THE CROSS 15 DEMAND THAT WE HAD TALKED ABOUT -- 16 MR. GLACKIN: 17 THE COURT: 18 MR. GLACKIN: 19 YEAH. -- ON THE MOTION TO DISMISS? I MEAN, I THINK THAT THERE'S -- I MEAN, THERE'S A FEW THINGS TO UNPACK THERE. 20 I MEAN, TO THE EXTENT THAT WE'RE TALKING ABOUT, AS A 21 QUESTION OF LAW, WHETHER -- OR AS A QUESTION, I SHOULD SAY, OF 22 ANTITRUST VIOLATION AND WHETHER THERE WAS A SINGLE CONSPIRACY 23 OR MORE THAN ONE CONSPIRACY, AS TO THAT QUESTION I WOULD SAY 24 THAT, AGAIN, WE HAVE YET TO DEPOSE ANY OF THE PEOPLE WHO WERE 25 THE ARCHITECTS OF THIS CONSPIRACY. UNITED STATES COURT REPORTERS 186 25 1 2 THE COURT: WHEN ARE THOSE DEPOSITIONS GOING FORWARD? 3 MR. GLACKIN: THEY'RE SET ACTUALLY TO START NEXT 4 WEEK, AND WE ARE GOING TO HAVE TO GET DONE BEFORE THE END OF 5 DISCOVERY, WHICH IS, I BELIEVE, TOWARDS THE END OF MARCH. 6 THEY'RE HAPPENING. 7 8 9 I DON'T KNOW WHAT THEY'RE GOING TO SAY. SO I DON'T KNOW THAT THEY'RE GOING TO ADMIT THAT THERE WAS A SINGLE CONSPIRACY. BUT THAT'S -- THAT'S AN ISSUE THAT THEY'RE NOT CONTESTING 10 AND I SUSPECT THAT -- FOR THE PURPOSES OF THIS MOTION, AND I 11 SUSPECT THAT PART OF THAT MAY BE THAT WE CAN VERY EASILY SAY 12 THAT DISCOVERY IS COMPLETELY OPEN ON THIS POINT. 13 THE COURT: WHY WEREN'T THOSE SCHEDULED -- I THINK 14 IT'S VERY CONVENIENT THAT THEY WERE NOT SCHEDULED UNTIL AFTER 15 THE HEARING ON CLASS CERT. 16 MR. GLACKIN: WELL, WE'VE BEEN -- I DON'T KNOW WHAT 17 TO SAY EXCEPT TO SAY WE'VE BEEN PRESSING FOR THEM AND WE WOULD 18 HAVE LIKED TO HAVE TAKEN SOME OF THEM FASTER AND WE REQUESTED 19 SOME OF THEM BEFORE THE HEARING. 20 THE COURT: BUT THAT IS WHERE WE ARE. WELL, WHEN WE GO THROUGH THE CMC, I WANT 21 YOU TO GIVE ME ALL OF THE DATES AND THOSE DATES ARE GOING TO 22 STICK. 23 MR. GLACKIN: 24 THE COURT: 25 ALL RIGHT. OKAY. OKAY? LET ME ASK WITH REGARD TO YOUR ALTERNATIVE UNITED STATES COURT REPORTERS 187 26 1 CLASS, DO WE KNOW -- AND WE PROBABLY DON'T BECAUSE THERE'S NO 2 COLD CALLING DATA -- WHETHER THE INDIVIDUALS IN THAT CATEGORY, 3 OR THAT CLASS, WOULD HAVE RECEIVED COLD CALLS OR WOULD HAVE 4 BEEN LIKELY SUBJECT TO COLD CALLS? 5 MR. GLACKIN: WELL, I THINK THAT -- I MEAN, HOW CAN 6 I PUT THIS? 7 LARGE, AND SO THEIR TECHNOLOGY TALENT IS A BIG PART OF THEIR 8 WORK FORCE UNLIKE, SAY, BURGER KING. 9 THEM. 10 11 SO THE DEFENDANTS ARE TECHNOLOGY COMPANIES, BY AND COLD CALLING MATTERED TO THEY HAD LARGE STAFFS OF PEOPLE WHO MADE A LOT OF COLD CALLS TO TRY TO FILL OPEN POSITIONS. SO I FEEL -- IT WAS -- I WOULD SAY IT WAS A SIGNIFICANT 12 RECRUITING CHANNEL FOR THEM, FOR EACH OF THEM, OR AT LEAST NOT 13 A NEGLIGIBLE ONE. 14 BUT BEYOND THAT, WE'RE NOT IN A POSITION TO SAY THAT 15 MEMBERS OF ONE -- MEMBERS OF ONE EMPLOYEE GROUP OR ONE, YOU 16 KNOW, OF THE SMALLER CLASS ARE MORE LIKELY TO HAVE RECEIVED 17 COLD CALLS THAN MEMBERS OF THE -- THAN CLASS MEMBERS NOT IN 18 THAT SMALLER CLASS. 19 WAY OR THE OTHER, NOT BASED ON EVIDENCE. 20 SPECULATE, BUT NOT BASED ON EVIDENCE. 21 THE COURT: WE'RE NOT IN A POSITION TO SAY THAT ONE I MEAN, WE COULD LET ME ASK ABOUT YOUR NAMED PLAINTIFFS. 22 THEY'RE ALL SOFTWARE ENGINEERS, OR THEY WERE. 23 THEM ARE DOING DIFFERENT OCCUPATIONS RIGHT NOW. 24 MR. GLACKIN: 25 THE COURT: I KNOW SOME OF CORRECT. HOW WERE THEY TYPICAL? UNITED STATES COURT REPORTERS AND I'M 188 27 1 UNDERSTANDING THAT THE DEFENDANTS ARE NOT CHALLENGING 2 TYPICALITY HERE, BUT HOW ARE THEY TYPICAL OF THE SOU CHEFS AND 3 ADMINISTRATIVE ASSISTANTS AND THE OTHER TYPES OF EMPLOYEES? 4 MR. GLACKIN: WELL, IN AN ANTITRUST CASE, TYPICALITY 5 IS -- YOU KNOW, ORDINARILY THE MOST TYPICAL THING ABOUT THE 6 CLASS REPRESENTATIVE IS THAT THEY HAVE THE ISSUE THAT'S COMMON 7 TO THE WHOLE CLASS, WHICH IS THE VIOLATION. 8 AND USUALLY WHEN YOU LOOK AT -- WHEN YOU ASK ABOUT 9 TYPICALITY IN AN ANTITRUST CASE, YOU MIGHT BE ASKING YOURSELF 10 IF IT'S POSSIBLE TO -- IF THERE'S SOME SORT OF FUNDAMENTAL 11 CONFLICT BETWEEN THIS PERSON AND OTHER MEMBERS OF THE CLASS 12 THAT MAKES THEIR CLAIM SO UNUSUAL THAT THEY'RE GOING TO BE A 13 BAD CLASS REPRESENTATIVE. 14 ADEQUACY. I MEAN, IT'S A RELATED CONCEPT TO 15 AND I DON'T THINK THERE'S ANYTHING ABOUT OUR PROPOSED 16 CLASS REPRESENTATIVES, ABOUT THE PLAINTIFFS HERE, THAT SUGGESTS 17 THAT THERE -- THAT SUCH A CONFLICT EXISTS, THAT THE CLASS WOULD 18 BE DISADVANTAGED BECAUSE THEIR CLAIM IS A LOT DIFFERENT THAN 19 THE CLASS -- THAN THE CLAIM OF SOMEBODY ELSE IN THE CLASS. 20 THINK THEY'RE COMPLETELY, FOR PURPOSES OF THIS MOTION, 21 COMPLETELY TYPICAL. 22 THE COURT: I AND YOU'RE SAYING THAT BECAUSE YOU 23 BELIEVE THEIR INJURY IS THE SAME BASED ON THE VIOLATION OF 24 SUPPRESSED COMPENSATION? 25 MR. GLACKIN: CORRECT. THEY HAVE THE SAME -- THEY UNITED STATES COURT REPORTERS 189 28 1 SHARE IN COMMON THE TWO THINGS THAT REALLY MATTER. 2 EMPLOYED BY THE DEFENDANTS, BY DEFENDANTS; AND THE DEFENDANT 3 THAT EMPLOYED THEM WAS A PARTY TO AN UNLAWFUL AGREEMENT OR 4 AGREEMENTS. 5 THE COURT: THEY WERE THE PLAINTIFFS RELY, IT APPEARS, HEAVILY 6 ON JUDGE ILLSTON'S DECISION ABOUT THE CLASS CERT ANALYSIS 7 REALLY JUST BEING ON THE METHOD FOR FIGURING OUT WHETHER 8 THERE'S CLASS-WIDE IMPACT VERSUS ACTUALLY LOOKING AT THE MERITS 9 OF WHETHER THERE HAS, IN FACT, BEEN CLASS-WIDE IMPACT. 10 MR. GLACKIN: 11 THE COURT: CORRECT. TELL ME WHY, AFTER DUKES V. WAL-MART, I 12 SHOULD FOLLOW JUDGE ILLSTON, WHO I ADMIRE A LOT AND RESPECT A 13 LOT, BUT WHY, AFTER DUKES, SHOULD I DO THAT? 14 15 16 MR. GLACKIN: OH, SURE. SO -- EXCUSE ME -- I DON'T THINK THAT DUKES HAS HAD ANY EFFECT ON THIS ANALYSIS AT ALL. DUKES IS A CASE THAT'S ABOUT 23(A) -- THIS IS A 23(B)(2) 17 CLASS, NOT A (B)(3) DAMAGES CLASS -- AND IT WAS A CASE ABOUT 18 COMMONALITY. 19 AND THE CASE -- THE ISSUE BEFORE THE SUPREME COURT IN 20 DUKES WAS IF THE ONLY COMMON ISSUE THE PLAINTIFFS HAVE IS THE 21 LACK OF A POLICY AND THE DISCRIMINATORY EFFECT THAT THEY SAY 22 THAT LACK OF A POLICY HAD, THAT THEY CAN PROVE THROUGH 23 STATISTICAL EVIDENCE, IF THAT IS THE ONLY COMMON ISSUE, THE 24 ONLY THING HOLDING THIS CLASS TOGETHER, THEN WE -- YOU BETTER 25 BE REALLY CONVINCING IS HOW I WOULD FRAME IT, AND THE COURT IS UNITED STATES COURT REPORTERS 190 29 1 REQUIRED TO MAKE -- I BELIEVE THE SUPREME COURT -- THE 2 DEFENDANTS USED THE PHRASE "CONVINCING PROOF" IN THEIR PAPERS. 3 I SEEM TO RECALL THE PHRASE AS "SIGNIFICANT PROOF." 4 PHRASES ARE USED IN THE OPINION. 5 MAYBE BOTH BUT IF YOU'RE IN THAT SITUATION WHERE THE ONLY EVIDENCE OF 6 A COMMON ISSUE IS THE STATISTICAL ANALYSIS SHOWING DISPARATE 7 IMPACT, THEN YOU ARE REQUIRED TO HAVE -- TO MAKE A SHOWING THE 8 SUPREME COURT CALLS CONVINCING PROOF. 9 IN AN ANTITRUST CASE, A SECTION 1 ANTITRUST CASE IS 10 FUNDAMENTALLY DIFFERENT. 11 SAYS THAT THE VIOLATION IS THE GLUE, THAT THAT IS THE COMMON 12 ISSUE. 13 I MEAN, THE LAW GOING BACK 50 YEARS THAT'S WHY, IN ANTITRUST CASES, YOU SPEND ABOUT 30 SECONDS 14 IN THE BRIEFING TALKING ABOUT 23(A) IF IT'S A SECTION 1 15 AGREEMENTS CASE BECAUSE THERE'S JUST NO DOUBT THAT THE 16 VIOLATION IS COMMON, THAT YOU'VE MET THAT REQUIREMENT OF 23(A). 17 YOU HAVE A PRETTY IMPORTANT COMMON ISSUE THAT IS THE GLUE THAT 18 MAKES THE CLASS COHESIVE. 19 20 21 IT IS COMMON TO EVERY CLASS MEMBER. SO THEN YOU GO TO THE 23 (B)(3) ANALYSIS, WHICH IS NOT THE SUBJECT OF DUKES. THERE WAS NO 23 (B)(3) CLASS IN DUKES. AND THERE, AGAIN, THE LAW GOING BACK TIME IMMEMORIAL IS 22 PRETTY CLEAR THAT THE VIOLATION ITSELF, PUTTING ALL ELSE ASIDE, 23 CAN BE A REASON TO CERTIFY A CLASS. 24 JUST BASED ON THE VIOLATION AND HAVE -- EVEN IF THERE ARE 25 INDIVIDUALIZED ISSUES, IF YOU MEET THE OTHER REQUIREMENTS THAT YOU CAN CERTIFY A CLASS UNITED STATES COURT REPORTERS 191 30 1 2 CLASS RELIEF IS STILL SUPERIOR. SO I WOULD SAY THAT WHEN YOU GET TO -- IN AN ANTITRUST 3 CASE, BY THE TIME YOU GET TO THE CONVERSATION WE'RE HAVING NOW 4 ABOUT IMPACT, THERE'S A PRETTY BIG THUMB ON THE SCALE IN FAVOR 5 OF CLASS CERTIFICATION, AND THAT IS A LOGICAL RESULT OF THE 6 NATURE OF THE CASE UNDER RULE 23. 7 SO BACK TO JUDGE ILLSTON. I MEAN, THE REASON THAT WE 8 CITED THAT CASE SO MUCH, BESIDES FAMILIARITY WITH IT, IS 9 THAT -- I MEAN, THERE ARE MANY GOOD CLASS CERTIFICATION 10 DECISIONS IN THE NORTHERN DISTRICT THAT WE'VE CITED AND I WOULD 11 SAY THAT ALL OF THOSE JUDGES DID A FINE JOB. 12 BUT I FELT -- WE BELIEVE THAT JUDGE ILLSTON'S OPINION 13 THERE IS PARTICULARLY COMPREHENSIVE AND THAT THE ISSUES THAT 14 ONE -- THAT -- THE ANALYSIS THAT THE COURT SHOULD GO THROUGH 15 AND THE ISSUES THAT ARE COMMONLY RAISED IN THESE CASES ARE -- 16 WERE VERY WELL VENTILATED THERE AND CONSIDERED BY HER. 17 AND SO WE THINK IT'S AN EXCELLENT, AN EXCELLENT ROAD MAP, 18 IF YOU WILL, OF WHAT THE COURT IS SUPPOSED TO DO HERE, WHICH IS 19 LOOK AT EVERY ISSUE AND SAY, IS IT INDIVIDUAL OR IS IT COMMON? 20 PUT THE COMMON ISSUES ON ONE SIDE OF THE LEDGER, PUT THE 21 INDIVIDUAL ISSUES ON THE OTHER SIDE OF THE LEDGER, IF ANY, AND 22 THEN MAKE A JUDGMENT AS TO WHETHER OR NOT THE INDIVIDUAL ISSUES 23 PREDOMINATE. 24 25 THE COURT: CAN YOU WALK ME THROUGH -- THIS IS IN DR. LEAMER'S EXPERT REPORT IN SUPPORT OF THE MOTION -- WALK ME UNITED STATES COURT REPORTERS 192 31 1 THROUGH FIGURES 13 THROUGH 22 AND WHAT EXACTLY THEY SHOW AND 2 WHAT THEY REPRESENT. THAT WOULD JUST BE HELPFUL -- 3 MR. GLACKIN: 4 THE COURT: CERTAINLY, YOUR HONOR. -- TO KNOW WHETHER THESE ARE JUST 5 HYPOTHETICALS, ARE THESE ACTUAL DATA THAT'S BEEN AGGREGATED AND 6 THEN AVERAGED? 7 8 OR WHAT -- WHAT THESE ARE. MR. GLACKIN: YOU COULD GUIDE ME ALONG IF YOU TOLD ME WHAT PAGE FIGURE 13 IS ON. 9 THE COURT: SURE. 10 MR. GLACKIN: 11 THE COURT: PAGE 57. PAGE 57. OR IF YOU WANT TO START WITH 15, WHICH 12 IS ON PAGE 59, OR 20, WHICH IS ON PAGE 66. 13 HOWEVER YOU FIND IT EASIER TO EXPLAIN WHAT THEY REPRESENT. 14 15 MR. GLACKIN: I MEAN, IT -- SURE, AND I THINK THIS IS AN EXCELLENT THING TO DO. 16 THE COURT: OKAY. 17 MR. GLACKIN: SO LET'S ACTUALLY GO BACK TO 12 AND 18 13, BECAUSE THE SIGNIFICANCE OF WHAT COMES OUT OF 15 AND 16 19 DEPENDS ON UNDERSTANDING 12, 13, AND 14. 20 THE COURT: OKAY. 21 MR. GLACKIN: SO 12, 13, AND 14 ARE -- EXCUSE ME, 22 AND ACTUALLY GOING BACK TO 11 I WOULD SAY -- ARE -- REPRESENT 23 THE RESULTS OF THE CORRELATION ANALYSIS. 24 25 AND THIS, JUST TO BE COMPLETELY CLEAR, IS NOT AN AVERAGED EXERCISE. THIS IS AN EXERCISE THAT'S PERFORMED ON THE ENTIRE UNITED STATES COURT REPORTERS 193 32 1 DATA SET, AND THE QUESTION THAT DR. LEAMER IS ASKING IS, TO 2 WHAT EXTENT DO A SET OF COMMON OBJECTIVE FACTORS THAT WE CAN 3 IDENTIFY IN THE DATA EXPLAIN THE COMPENSATION OF CLASS MEMBERS? 4 AND THE REASON WE ASKED THE QUESTION IS, IF THE 5 COMPENSATION OF CLASS MEMBERS IS NOT WELL EXPLAINED BY COMMON 6 OBJECTIVE FACTORS, THEN WE WOULD HAVE A REASON TO BELIEVE THAT 7 OUR HYPOTHESIS OF A PAY STRUCTURE IS FALSE. 8 9 SO HE ASKED THE QUESTION, AND YOU SEE ON 11 YOU HAVE, I WOULD SAY, THE SORT OF HIGH LEVEL RESULTS. AND THE R SQUARE 10 NUMBER, AND I'M -- I BELIEVE -- I HOPE I'M GOING TO GET THIS 11 RIGHT -- IT SAYS THIS IS THE PERCENTAGE OF -- THIS IS AN 12 AVERAGE. 13 IS EXPLAINED FOR THAT YEAR AT THESE DEFENDANT FIRMS BY THESE 14 COMMON OBJECTIVE FACTORS. 15 THIS IS THE AVERAGE PERCENTAGE OF COMPENSATION THAT THE COURT: SO DR. LEAMER TOOK ALL OF THE DATA FOR 16 ALL EMPLOYEES OF ALL DEFENDANTS AND THEN DID AN ANALYSIS TO 17 DETERMINE HOW MUCH OF THE PAY DIFFERENTIAL IS DETERMINED BY 18 AGE, FOR EXAMPLE, OR BY TENURE AT THE COMPANY. 19 MR. GLACKIN: IS THAT RIGHT? EXACTLY, HOW MUCH OF IT IS DETERMINED 20 BY THESE SIX FACTORS TOGETHER, AND ALSO HOW MUCH OF IT IS 21 DETERMINED BY THEM INDIVIDUALLY, CORRECT. 22 AND WHAT WE FIND IS, UNSURPRISINGLY -- AND DR. MURPHY, I 23 THINK, FOUND THIS, TOO -- IS THAT JOB TITLE IS FAR AND AWAY THE 24 MOST IMPORTANT FACTOR, WHICH IS TOTALLY UNSURPRISING AT 25 COMPANIES THAT PAY PEOPLE WITHIN SALARY RANGES ACCORDING TO JOB UNITED STATES COURT REPORTERS 194 33 1 2 3 4 TITLES, WHICH IS WHAT WE HAVE REASON TO BELIEVE HAPPENED HERE. SO THAT'S -- THAT'S WHAT 12 -- THAT'S WHAT 11, 12, 13, AND 14 ARE ABOUT. AND THEN IF YOU LOOK AT 14 -- 5 THE COURT: NOW, TITLE INDICATORS, IT JUST SAYS YES. 6 IT DOESN'T SAY HOW MUCH OF A DIFFERENTIAL IT MADE IN TERMS OF 7 COMPENSATION. 8 9 10 11 MR. GLACKIN: YES. I THINK WHAT THAT -- EXCUSE ME. I MIGHT ACTUALLY BE -- IT'S POSSIBLE THAT I'M MISINTERPRETING THAT COLUMN ESTIMATE. BUT WHAT TITLE -- WHAT I READ TITLE INDICATORS THERE TO 12 MEAN IS THAT TITLE INDICATORS ARE INCLUDED IN THE ANALYSIS, 13 WHICH IS TRUE. 14 THE COURT: OKAY. SO THEN THIS IS JUST LOOKING AT 15 THE DIFFERENCE THAT AGE, TENURE AT THE COMPANY, AND GENDER 16 MAKE? IT'S ONLY LOOKING AT THOSE THREE VARIABLES? 17 MR. MITTELSTAEDT: 18 MR. GLACKIN: 19 JOB TITLE, AND WHAT COMPANY IT IS. 20 THE COURT: 21 MR. GLACKIN: 22 THE COURT: YEAH. RIGHT. AGE, TENURE, GENDER, LOCATION, THAT'S WHAT EMPLOYER INDICATORS MEANS? I BELIEVE SO. WHAT COMPANY IT IS? I GUESS I'M JUST 23 NOT CLEAR ON WHY IT DOESN'T SHOW WHAT DIFFERENCE THE TITLE 24 INDICATOR MAKES. 25 GO ON. IT JUST SAYS YES. BUT THAT'S FINE. UNITED STATES COURT REPORTERS WE CAN 195 34 1 MR. GLACKIN: SO -- AND THEN IF YOU LOOK -- AND THEN 2 ON 12, THIS INFORMATION IN FIGURE 12 IS DISAGGREGATED BY 3 DEFENDANT, RIGHT? 4 THE PERCENTAGE OF EMPLOYEE COMPENSATION THAT IS EXPLAINED BY 5 THESE COMMON OBJECTIVE FACTORS IN ANY GIVEN YEAR FOR ANY GIVEN 6 DEFENDANT. 7 SO YOU CAN SEE THE -- THIS FIGURE 12 SHOWS SO WE -- IN ADDITION TO GIVING THE COURT THE RANGE -- OR 8 EXCUSE ME -- THE AVERAGE, WHICH IS WEIGHTED BY DEFINITION 9 TOWARDS CERTAIN DEFENDANTS THAT ARE LARGER, WE ALSO WANTED TO 10 11 SHOW THE RANGE SO YOUR HONOR COULD SEE THE RANGE. AND, I MEAN, THIS MIGHT BE A GOOD PLACE TO POINT OUT THAT 12 IN THE REED CASE ON WHICH MR. MITTELSTAEDT HAS RELIED 13 EXTENSIVELY, THERE WAS -- THERE WAS ALSO A CORRELATION ANALYSIS 14 DONE IN THAT CASE, AND THE EXPLANATORY VALUE OF THE CORRELATION 15 ANALYSIS IN THAT CASE WAS I THINK 48 TO 63 PERCENT. 16 IN OTHER WORDS, THE PLAINTIFFS IN THAT CASE, WHEN THEY 17 WERE TRYING TO EXPLAIN HOW NURSES ARE PAID, WHICH IS A VERY 18 DIFFERENT EXERCISE THAN WHAT WE'RE DOING HERE, COULD ONLY 19 EXPLAIN 48 TO 63 PERCENT, I THINK, OF THE SALARY, OR OF THE PAY 20 EARNED BY NURSES. 21 THE MANY FACTORS THAT THE COURT CONSIDERED IN THAT LENGTHY 22 OPINION. 23 AND THAT WAS A FACTOR THAT THE COURT, ONE OF HERE YOU CAN SEE THAT OUR RANGE IS MUCH HIGHER THAN THAT. 24 I MEAN, I'M NOT SEEING THE LOWEST FIGURE HERE. 25 THE LOWEST FIGURE IS PROBABLY THE .77 FOR GOOGLE AT THE END IN UNITED STATES COURT REPORTERS I WANT TO SAY 196 35 1 2 2010. OH, THERE'S A .75 ABOVE THAT, EXCUSE ME. BUT IT'S QUITE CLEAR HERE, THE REASON THAT THE AVERAGE IS 3 AROUND 90 TO 95 IN EVERY YEAR IS BECAUSE FOR EVERY EMPLOYER FOR 4 EVERY YEAR WE ARE MORE OR LESS EXPLAINING IN THE BALL PARK OF 5 THAT AMOUNT OF THEIR COMPENSATION. 6 NOW, TO CORRECT ONE OTHER POSSIBLE MISCONCEPTION, THE -- 7 JUST BECAUSE WE'VE ONLY EXPLAINED -- BECAUSE THE ANALYSIS ONLY 8 EXPLAINS THIS MUCH OF THE COMPENSATION, IT DOESN'T MEAN THE 9 REST OF IT IS RANDOM OR THAT IT IS ALL DISCRETIONARY. 10 11 IT SIMPLY MEANS WE HAVEN'T EXPLAINED IT. THERE ARE OTHER COMMON OBJECTIVE FACTORS THAT, IF WE KNEW 12 THEM, WE MIGHT BE ABLE TO EXPLAIN YET MORE OF THE COMPENSATION. 13 AND ONE THAT CAME UP IN, SPECIFICALLY IN DR. LEAMER'S 14 DEPOSITION IS EDUCATION. 15 WE HAVE. 16 BECAUSE THEY DON'T ALL KEEP IT, AND SO WE COULD NOT RUN A 17 CORRELATION ANALYSIS THAT WOULD INCLUDE THAT VARIABLE. 18 AND, AGAIN, WE SIMPLY HAVE THE DATA WE DON'T HAVE EDUCATION DATA FOR ALL DEFENDANTS BUT DR. LEAMER EXPRESSED AT HIS DEPOSITION HE FELT PRETTY 19 CONFIDENT THAT IF YOU PUT EDUCATION IN THERE, YOU WOULD BE 20 EXPLAINING SOME MORE OF THE SALARIES, OR OF THE COMPENSATION. 21 SO THEN 13 AND 14 ARE THE SAME EXERCISE, BUT FOR THE 22 TECHNICAL CLASS. 23 THE COURT: WAIT. 24 MR. GLACKIN: 25 THE COURT: LET ME ASK YOU -- SURE. -- SO, FOR EXAMPLE, ONE COMP IN 2001, UNITED STATES COURT REPORTERS 197 36 1 .91, DOES THAT MEAN THAT 91 PERCENT OF THE COMPENSATION IS 2 DETERMINED BY THE EMPLOYEE'S AGE, THEIR TENURE AT THE COMPANY, 3 THEIR GENDER, THE LOCATION WHERE THEY WORK, AND THEIR TITLE? 4 5 MR. GLACKIN: CORRECT. ON AVERAGE, YES, THAT'S WHAT IT MEANS. 6 THE COURT: OKAY. 7 MR. GLACKIN: AND THAT -- AND 9 PERCENT OF IT WE 8 JUST DON'T KNOW. IT COULD BE DETERMINED BY EDUCATION. 9 COULD BE DETERMINED BY MANAGER DISCRETION. IT IT COULD BE 10 DETERMINED BY -- ONE COULD IMAGINE OTHER FACTORS, BUT WE JUST 11 DON'T KNOW. 12 THE COURT: OKAY. 13 MR. GLACKIN: AND THEN 13 AND 14 ARE THE SAME THING 14 FOR THE TECH CLASS AND THEY SHOW -- I MEAN, AGAIN, WE WERE SORT 15 OF TAKEN TO TASK ABOUT NOT ASKING THESE QUESTIONS. 16 BUT WE DID ASK THESE QUESTIONS, AND IF THE CORRELATION 17 ANALYSIS HAD SHOWED THAT IT WAS PERFORMING VERY BADLY FOR THE 18 LARGER CLASS AND PERFORMING VERY WELL FOR THE TECHNICAL CLASS, 19 THEN WE MIGHT HAVE NOT PROPOSED THE LARGER CLASS. 20 BUT IT TURNS OUT THAT THE CORRELATION ANALYSIS PERFORMS 21 PRETTY MUCH THE SAME FOR BOTH, WHICH IS NOT -- I MEAN, I DON'T 22 KNOW IF IT'S SURPRISING OR NOT, BUT IT IS WHAT IT IS. 23 TRUE. 24 25 IT'S SO WHAT YOU SEE FROM THIS IS THAT FOR BOTH THAT SMALLER CLASS AND FOR THE CLASS OF EMPLOYEES ALL TOGETHER, THERE IS A UNITED STATES COURT REPORTERS 198 37 1 PAY STRUCTURE. 2 I THINK DR. MURPHY AND DR. LEAMER BOTH AGREE, FROM LOOKING AT 3 THE DATA, THAT IT'S VERY DRIVEN BY JOB TITLE. 4 THERE IS SOME KIND OF A PAY STRUCTURE HERE, AND THE COURT: WELL, YOU CAN'T TELL THAT BY -- YOU 5 CAN'T TELL THAT BY THESE FIGURES BECAUSE THEY DON'T GIVE YOU 6 ANY NUMERICAL ESTIMATE FOR TITLE. 7 MR. GLACKIN: 8 THE COURT: 9 10 YOU CAN'T DISAGGREGATE AGE OF THE BECAUSE THIS IS A -MR. GLACKIN: THAT'S CORRECT. WE DON'T REPORT -- WE DON'T REPORT THE PERCENTAGE. 13 14 THAT'S TRUE. EMPLOYEE, TENURE AT THE COMPANY, GENDER, LOCATION, AND TITLE, 11 12 IT JUST SAYS YES. THE COURT: SO WHAT DO THEY BASE THAT ON, THAT IT'S BASED ON THE TITLE? 15 MR. GLACKIN: WHAT I AM RECALLING IS THAT DR. LEAMER 16 WAS ASKED AT HIS DEPOSITION, BY MR. PICKETT, SOMETHING ALONG 17 THE LINES OF, "WOULD IT SURPRISE YOU THAT MOST OF THIS 18 CORRELATION IS DRIVEN BY THE JOB TITLE?" 19 20 21 22 23 AND DR. LEAMER SAID, "NO, NOT AT ALL. I BELIEVE THAT'S TRUE." AND I THINK THAT DR. MURPHY REFERRED TO THIS IN HIS REPORT AS WELL, BUT I WOULD HAVE TO CHECK. THE COURT: WHY ARE THE, THE NUMBERS FOR HOW MUCH A 24 COMPENSATION IS DETERMINED BY EMPLOYEE AGE, COMPANY TENURE, 25 GENDER, LOCATION, AND TITLE PRETTY CONSISTENTLY LOWER FOR THE UNITED STATES COURT REPORTERS 199 38 1 TECHNICAL ALTERNATIVE CLASS VERSUS THE ALL EMPLOYEE CLASS? 2 3 MR. GLACKIN: THAT. I DON'T KNOW THAT WE COULD. 4 THE COURT: 5 MR. GLACKIN: 6 I DON'T BELIEVE WE TRIED TO EXPLAIN OKAY. ALL RIGHT. SO THAT'S THOSE FIGURES. THEN YOU GO TO FIGURES 15 AND 16 AND 17 -- AND JUST FOR 7 CONTEXT'S SAKE, THESE ARE THE FIGURES THAT I THINK ARE THE 8 SUBJECT OF ALL THE SUPPLEMENTAL MATERIAL THE DEFENDANTS MOVED 9 TO ADMIT I BELIEVE LATE LAST WEEK. 10 AND WHAT THESE FIGURES SHOW IS -- SO IT SAYS CONSTANT 11 CONTRIBUTE -- EXCUSE ME -- CONSTANT ATTRIBUTE COMPENSATION OF 12 MAJOR JOB TITLES. 13 AND WHAT DR. LEAMER HERE IS DOING IS HE'S LOOKING AT THE 14 PREDICTED VALUE OF THESE JOB TITLES, PREDICTED BY THE 15 CORRELATION, WITHIN A PERSON'S COMPENSATION. 16 AND I'M PROBABLY NOT SAYING -- I'M PROBABLY NOT SAYING 17 THAT VERY WELL, BUT THE IDEA HERE IS TO ASK YOURSELF, IS THE 18 VALUE OF THE JOB TITLE CHANGING ON A YEAR TO YEAR BASIS WITHIN 19 THESE COMPANIES? 20 AND THE REASON YOU ASK THAT QUESTION -- IT ALWAYS GOES 21 BACK TO THE SCIENTIFIC METHOD. THE REASON YOU ASK THAT 22 QUESTION IS BECAUSE IF, IF IT DOES, IF IT -- IF YOU SEE SOME 23 EVIDENCE, OR IF YOU SEE A LOT OF EVIDENCE THAT IS, YOU KNOW, 24 THAT JOB TITLE COMPENSATION GOES WAY UP IN ONE YEAR AND WAY 25 DOWN IN ANOTHER YEAR AND THIS IS ALWAYS TRUE FOR JOB TITLES, UNITED STATES COURT REPORTERS 200 39 1 YOU WOULD NOT BE REASSURED THAT THE -- THAT YOU'RE REALLY 2 DETECTING A STRUCTURE HERE THAT'S DRIVEN BY JOB TITLE. 3 AND SO HE MAPS THESE -- HE CONSIDERS WHAT -- 4 THE COURT: SO TELL ME, HOW IS FIGURE 15 CREATED? 5 MR. GLACKIN: THIS -- I'M TRYING TO THINK OF THE 6 BEST WAY TO EXPRESS THIS. 7 THE VALUE OF COMPENSATION, DOLLAR VALUE OF COMPENSATION FOR A 8 PARTICULAR JOB TITLE THAT IS PREDICTED BY THE REGRESSION, THE 9 CORRELATION ANALYSIS IN ANY PARTICULAR YEAR. 10 THE COURT: THIS IS THE PERCENTAGE OF -- THIS IS SO YOU'RE SAYING THAT DR. LEAMER DID 11 WHATEVER HE DID TO CALCULATE THE NUMBERS IN FIGURES 11 AND 12 13 -- 13 MR. GLACKIN: 14 THE COURT: 15 AS THE ONLY DEPENDENT VARIABLE? -- THAT HE DID THAT AND ISOLATED TITLE 16 MR. GLACKIN: 17 THE COURT: 18 19 UM-HUM. NO, NO, NO. HOW DID HE COME UP WITH THIS GRAPH IN FIGURE 15? MR. GLACKIN: SO THE -- WELL, ACTUALLY THAT MIGHT -- 20 I THINK THE WORDS "DEPENDENT VARIABLE" MIGHT BE WRONG. 21 WHAT YOU MIGHT -- THE WAY I UNDERSTAND IT IS YOU LOOK AT THE 22 CORRELATION -- YOU LOOK AT THESE SIX FACTORS AND YOU PUT IN A 23 VALUE FOR EACH OF THE FACTORS, JOB TITLE, AGE, TENURE AT THE 24 COMPANY AND WHAT HAVE YOU, GENDER, AND THE ANALYSIS WILL SPIT 25 OUT A VALUE, OR PREDICT -- I SHOULDN'T SAY "SPIT OUT" -- IT UNITED STATES COURT REPORTERS I MEAN, 201 40 1 2 PREDICTS A DOLLAR AMOUNT OF COMPENSATION BASED ON THAT FACTOR. AND THIS IS -- SO, I MEAN, HERE -- 3 THE COURT: IS THIS -- 4 MR. GLACKIN: SO HERE HE'S ISOLATING -- "ISOLATING" 5 IS THE RIGHT WORD -- HE'S ISOLATING WHAT YOU PREDICT JUST BASED 6 ON AN INDIVIDUAL'S JOB TITLE. 7 SO FOR HERE, IF YOU'RE LOOKING AT THE TOP LINE, WHICH IS 8 THE LIGHT PURPLE, WHICH IS SOFTWARE DEVELOPER ENGINEER 4 -- 9 HOPEFULLY I GOT THE COLORS RIGHT -- THE CORRELATION ANALYSIS IS 10 PREDICTING THAT IF ALL YOU KNOW ABOUT A PERSON IS THAT THEY 11 HAVE THAT POSITION, THEY'RE MAKING $130,000 A YEAR. 12 KNOW ANYTHING ELSE ABOUT THEM. 13 THE COURT: 18 19 NO. MR. GLACKIN: THE COURT: AND THEN BELOW IS TOTAL COMP, SO WHAT WAS THIS BASED ON, THE TOTAL DATA OF ALL -MR. GLACKIN: 21 THE COURT: 23 RIGHT. RIGHT. 20 22 THE TOP OF FIGURE 15 IS BASE SALARY. 16 17 YOU JUST KNOW THAT. AND THAT'S TOTAL COMPENSATION HERE, NOT SALARY. 14 15 YOU DON'T RIGHT, ALL THE DATA. NO. THIS WAS JUST APPLE. RIGHT? FIGURE 15 IS JUST APPLE AND 16 IS JUST GOOGLE. MR. GLACKIN: YEAH, I THINK THAT'S RIGHT. I MEAN, 24 ALL THE DATA IS IN THE SET, BUT I THINK YOU'RE BASING THAT ON 25 APPLE AND GOOGLE DATA. UNITED STATES COURT REPORTERS 202 41 1 2 THE COURT: WHAT THESE ARE. SO WHAT -- I'M JUST TRYING TO FIGURE OUT IT'LL HELP IN THE ORDER. 3 MR. GLACKIN: 4 THE COURT: SO WHAT HELPS -- THIS IS SAYING THAT -- THIS IS LOOKING 5 AT ALL OF THE BASE SALARY AND TOTAL COMPENSATION DATA OF THESE 6 TEN CATEGORIES OF JOBS AT APPLE -- 7 MR. GLACKIN: 8 THE COURT: 9 -- AND PREDICTING WHAT THEIR SALARY WOULD BE -- 10 MR. GLACKIN: 11 THE COURT: 12 UM-HUM. UM-HUM. -- BASED SOLELY ON THE JOB TITLE? IS THAT WHAT THIS -- 13 MR. GLACKIN: 14 THE COURT: 15 MR. GLACKIN: THAT'S PRETTY MUCH RIGHT. I DON'T UNDERSTAND WHAT THIS IS. THAT'S PRETTY MUCH RIGHT. AND THE 16 SIGNIFICANCE OF THAT IS, AGAIN, THAT THE -- THIS IS, AGAIN, AN 17 EXERCISE IN ATTEMPTING TO FALSIFY, RIGHT? 18 IF -- IF THIS WERE A LOT DIFFERENT, THEN DR. LEAMER WOULD 19 BE OF THE OPINION THAT THERE -- YOU KNOW, IT WOULD BE 20 QUESTIONABLE, I GUESS. 21 YOU'D HAVE TO MAYBE DO MORE ANALYSIS. BUT YOU'D BE TROUBLED WITH YOUR CONCLUSION THAT THERE'S A 22 PAY STRUCTURE THAT PERSISTS OVER TIME THAT'S DRIVEN BY THIS 23 ADMINISTRATIVE PAY SYSTEM. 24 25 I MEAN, BECAUSE -- IN OTHER WORDS, WHEN YOU LOOK AT THE CORRELATION ANALYSIS, YOU'RE LOOKING AT A SNAPSHOT OF A UNITED STATES COURT REPORTERS 203 42 1 PARTICULAR YEAR, AND THAT SHOWS A STRUCTURE. 2 IT DOES SHOW A STRUCTURE. 3 BUT YOU ALSO WANT TO ASK YOURSELF IF THAT, IF THOSE 4 CORRELATIONS ARE HOLDING OVER TIME, BECAUSE IF THEY AREN'T, YOU 5 MIGHT HAVE TO DO SOME INVESTIGATION TO UNDERSTAND WHY THEY'RE 6 NOT. 7 THE COURT: SO WHAT DOES YOUR THEORY REQUIRE BE 8 SHOWN IN FIGURE 15? 9 TECHNICAL JOBS AT APPLE ARE GENERALLY INCREASING OR DECREASING 10 THAT ALL OF THESE DIFFERENT CATEGORIES OF TOGETHER? 11 MR. GLACKIN: 12 THE COURT: 13 MR. GLACKIN: NO. WHAT DOES YOUR THEORY REQUIRE? IT ABSOLUTELY DOESN'T. I DON'T 14 ACTUALLY THINK THAT -- I DON'T THINK THAT THE THEORY REQUIRES 15 THAT THESE LOOK A PARTICULAR WAY, OTHER THAN THEY NOT BE A 16 COMPLETE MISHMASH, I GUESS. 17 THE COURT: WELL, DOESN'T YOUR INTERNAL EQUITY 18 THEORY REQUIRE THAT THEY SOMEWHAT RISE OR FALL TOGETHER? 19 OTHERWISE YOU'RE GOING TO HAVE RESENTMENT, JEALOUSLY, 20 DISCONTENTMENT, PEOPLE START LEAVING? 21 MR. GLACKIN: NO, ABSOLUTELY NOT. AND THE REASON 22 FOR THAT IS THAT INTERNAL EQUITY IS -- AND WE'VE NEVER SAID 23 THIS, BY THE WAY. 24 DRIVES EMPLOYEE COMPENSATION. 25 DRIVES EMPLOYEE COMPENSATION. INTERNAL EQUITY IS NOT THE ONLY FACTOR THAT IT IS SIMPLY A FACTOR THAT UNITED STATES COURT REPORTERS 204 43 1 SO PEOPLE -- I'M SORRY. 2 THE COURT: I DIDN'T MEAN TO INTERRUPT YOU. WELL, I GUESS I'M JUST NOT -- I'M NOT 3 CLEAR ON WHAT THIS IS SHOWING, BASE SALARY VERSUS TOTAL 4 COMPENSATION, BROKEN DOWN BY TEN DIFFERENT ENGINEERING JOBS AT 5 TWO COMPANIES. 6 WHAT IS FIGURE 15 AND 16 SUPPOSED TO CONVEY? MR. GLACKIN: WHAT IT'S SUPPOSED TO CONVEY IS THAT 7 THE -- THE INDIVIDUAL STRUCTURE THAT'S BEEN SHOWN IN EVERY YEAR 8 BY THE CORRELATION ANALYSIS, WHICH IS FIGURES 11 THROUGH 14, 9 IS -- APPEARS TO BE PERSISTENT, MORE OR LESS, OVER TIME. 10 AND IT'S NOT -- IT'S NOT RANDOMLY RESETTING EVERY YEAR, 11 WHICH OF COURSE THERE'S NO EVIDENCE OF IN THE RECORD, RIGHT? 12 THEY DON'T DO A COMPLETE REBOOT OF THEIR PAY SYSTEM EVERY 12 13 MONTHS. 14 THE COURT: AND WHAT DOES THAT MEAN? THAT YOUR JOB 15 TITLE IS LARGELY GOING TO DETERMINE YOUR COMPENSATION IN A 16 GIVEN YEAR? 17 MR. GLACKIN: 18 THE COURT: 19 YEAH, AND IN FUTURE YEARS. I GUESS I JUST DON'T SEE THE RELATIONSHIP OF THAT WITH THE PLAINTIFFS' OVERALL THEORY. 20 MR. GLACKIN: WELL, AGAIN, IT'S JUST TO -- I MEAN, 21 AT THIS POINT WE'RE REALLY CONFIRMING SOMETHING THAT WE HAD NO 22 REASON TO DOUBT TO BEGIN WITH, WHICH IS THAT THESE COMPANIES 23 HAVE ADMINISTRATIVE PAY SYSTEMS THAT PAY PEOPLE ACCORDING TO A 24 STRUCTURE. 25 I MEAN, LET ME POSIT -- MAYBE I CAN EXPLAIN THIS BETTER. UNITED STATES COURT REPORTERS 205 44 1 LET'S SAY YOU HAVE RUN THE CORRELATION ANALYSIS FOR DIFFERENT 2 YEARS, AND EVERY YEAR YOU'RE SHOWING THAT 95 PERCENT OF -- 3 YOU'RE EXPLAINING 95 PERCENT OF COMPENSATION BASED ON SIX 4 FACTORS, OKAY? 5 THAT LOOKS GREAT. THAT LOOKS LIKE A STRUCTURE. BUT WHAT IF, WHAT IF, IN 2001, JOB TITLE IS DRIVING 90 6 PERCENT OF IT AND, IN 2002, GENDER IS DRIVING 90 PERCENT OF IT 7 AND JOB TITLE IS ONLY DRIVING 10 PERCENT OF IT? 8 9 10 11 WELL, YOU'RE STILL EXPLAINING 90 PERCENT, BUT YOUR THEORY OF A STRUCTURE IS QUESTIONABLE, TO SAY THE LEAST, UNDER THOSE CIRCUMSTANCES. AND WHAT THIS IS SHOWING IS THAT THAT DIDN'T HAPPEN, THAT 12 JOB TITLE CONTINUED TO BE IMPORTANT EVERY YEAR, AND THAT THE 13 SYSTEM WASN'T REBOOTING SO THAT IT WAS JOB TITLE ONE YEAR, 14 GENDER ANOTHER YEAR, AND THEN THE THIRD YEAR, THEY THREW THE 15 JOB TITLE BOOK OUT AND THEY JUST PAID PEOPLE BASED ON HOW LONG 16 THEY'D BEEN AT THE COMPANY, YOU GOT 50 GRAND FOR EVERY YEAR OF 17 SERVICE. 18 19 20 THAT DIDN'T HAPPEN. WE KNOW AS A FACTUAL MATTER THAT THAT DIDN'T HAPPEN, AND THIS SIMPLY CONFIRMS THAT IT DIDN'T HAPPEN. THE COURT: OKAY. SO WHAT IS THE RELATIONSHIP 21 BETWEEN THE THEORY THAT AN EMPLOYEE'S SALARY IS LARGELY 22 DETERMINED BY THEIR TITLE -- 23 MR. GLACKIN: 24 THE COURT: 25 UM-HUM. THEORY OF THIS CASE? -- WHAT DOES THAT HAVE TO DO WITH YOUR UNITED STATES COURT REPORTERS 206 45 1 MR. GLACKIN: WELL, WHAT IT HAS TO DO WITH IS THE 2 OPERATION OF INTERNAL EQUITY DOES REQUIRE SOME KIND OF A PAY 3 STRUCTURE AND -- THAT IS COMPANY-WIDE. 4 BE -- I MEAN, AGAIN, TO BEGIN WITH, WE START FROM THE PREMISE 5 THAT INTERNAL EQUITY IS WIDELY ACCEPTED -- EXCUSE ME -- IT'S 6 TAUGHT IN PERSONNEL HANDBOOKS. 7 TEXTBOOKS. 8 9 10 11 I MEAN, THERE HAS TO IT'S TAUGHT IN PERSONNEL IT'S NOT A CONTROVERSIAL PROPOSITION. SO NOW WE'RE ASKING, WAS INTERNAL -- IS IT REASONABLE TO BELIEVE THAT INTERNAL EQUITY AFFECTED COMPENSATION AT THESE COMPANIES? WELL, ONE THING THAT WOULD GIVE YOU A LOT OF PAUSE IS IF 12 THERE WAS NO STRUCTURE TO HOW THESE COMPANIES PAID THEIR 13 EMPLOYEES -- AND THIS WOULD BE IF THERE WAS NO SYSTEM OR 14 STRUCTURE, BECAUSE IF PAY IS NOT BEING CENTRALIZED AT THESE 15 COMPANIES IN ANY WAY, IT WOULD BE HARD FOR INTERNAL EQUITY TO 16 HAVE A SHARING EFFECT ACROSS THE ENTIRE FIRM. 17 SO THAT IS WHY WE'VE TRIED TO VERIFY HERE WHAT WE KNOW IS 18 TRUE, WHICH IS THAT THE COMPANIES HAVE ADMINISTRATIVE -- THEY 19 HAVE CENTRALIZED, ADMINISTRATIVE PAY SYSTEMS BY WHICH THEY SET 20 COMPENSATION FOR THE ENTIRE FIRM, AND THAT IS A VERY -- THAT 21 STRUCTURE IS A VERY IMPORTANT PART OF HOW THEY SET 22 COMPENSATION. 23 THE COURT: WELL, THAT SEEMS TO BE SOMEWHAT TRUE FOR 24 BASE SALARY, BUT DOESN'T SEEM TO REFLECT TOTAL COMPENSATION, 25 WHICH I WOULD ASSUME INCLUDES, YOU KNOW, STOCK OPTIONS AND UNITED STATES COURT REPORTERS 207 46 1 BONUSES. THERE'S A LOT MORE DEVIATION GOING ON IN TOTAL 2 COMPENSATION. SO HOW DO YOU -- 3 MR. GLACKIN: 4 THE COURT: WELL, YEAH. SO HOW DO YOU EXPLAIN THAT, THAT YOUR 5 SORT OF MORE LOCKSTEP INTERNAL EQUITY THEORY MIGHT APPLY TO THE 6 BASE, BUT IT'S NOT GOING TO ACCOUNT FOR THE OTHER FACTORS THAT 7 MAKE UP SOMEONE'S TOTAL COMPENSATION? 8 9 MR. GLACKIN: SO I GUESS WHAT I WOULD SAY IS THAT -- FIRST OF ALL, I MEAN, YOU CAN CERTAINLY IMAGINE A WORLD IN 10 WHICH THE EFFECTS OF THIS -- THE EFFECTS OF THE INCREASED 11 COMPETITION WOULD HAVE BEEN SHARED SIMPLY THROUGH BASE 12 SALARIES. 13 CERTAINLY POSSIBLE. 14 I MEAN, IT'S NOT HARD TO IMAGINE THAT WORLD. IT'S BUT I DON'T THINK THAT THE FACT THAT THE TOTAL 15 COMPENSATION LINES SHOW MORE VARIABILITY IS A PROBLEM. 16 THERE'S -- INTERNAL EQUITY DOESN'T MEAN EQUALITY. 17 MEAN EVERYBODY IS ALWAYS GOING TO GET A RAISE AT THE SAME TIME. 18 IT DOESN'T MEAN THAT EVERYONE IS GOING TO GET A PAY CUT AT THE 19 SAME TIME. 20 I MEAN, IT DOESN'T WHAT IT MEANS IS THAT IF SOMEONE, SOMEONE OR SOME GROUP 21 GETS A RAISE, THERE WILL BE AN INCREMENTAL BENEFIT TO OTHER 22 MEMBERS OF THAT COMPANY'S WORK FORCE BECAUSE OF THE GAINS -- 23 CAUSED BY THE GAINS MADE BY THAT PERSON OR THAT GROUP. 24 25 SO OTHER PEOPLE WHO ARE GETTING A PAY CUT MIGHT GET LESS OF A PAY CUT BECAUSE THERE MIGHT BE A BIGGER COMPENSATION UNITED STATES COURT REPORTERS 208 47 1 2 BUDGET. IT DOESN'T REQUIRE THAT, AT ALL, THAT COMPENSATION MOVE IN 3 LOCKSTEP, AND COMPENSATION AT THESE COMPANIES DOES NOT MOVE IN 4 LOCKSTEP. 5 THE COURT: SO WHAT -- WHY DON'T YOU EXPLAIN HOW THE 6 SECOND GRAPH OF FIGURE 16 STILL SUPPORTS YOUR INTERNAL EQUITY 7 THEORY. 8 9 MR. GLACKIN: SO I GUESS -- I MEAN, DR. LEAMER -- I'M GOING TO REFER TO HIS TESTIMONY, BECAUSE I FEEL LIKE HE 10 SHOULD BE THE ONE EXPLAINING IT. 11 THE COURT: 12 MR. GLACKIN: UM-HUM. AND HE TESTIFIED ABOUT THIS SPECIFIC 13 FIGURE AND HE SAID THAT, YOU KNOW, THAT THIS IS -- I MEAN, IT'S 14 NORMAL -- I REALLY OUGHT TO LOOK AT HIS TESTIMONY. 15 RECOLLECTION IS HE SAID THAT IT'S OKAY FOR THERE TO BE SOME 16 OUTLIERS. 17 JOB TITLE TO GET A BIG BUMP IN A PARTICULAR YEAR. 18 I MEAN, IT'S ALL RIGHT. THE COURT: 19 EQUITY? 20 MY IT'S OKAY FOR A GROUP OR A BUT WHAT DOES THAT DO FOR INTERNAL DISCONTENT? 21 DON'T THE REST OF THE FOLKS GET JEALOUS, RESENTFUL, MR. GLACKIN: THE POINT IS THAT THEY DON'T HAVE TO 22 GET THE SAME -- THEY DON'T HAVE TO GET THE SAME BUMP IN ORDER 23 TO NOT FEEL THAT WAY. 24 25 FOR EXAMPLE, IF -- YOU COULD GIVE ONE GROUP OF EMPLOYEES A PAY RAISE AND GIVE OTHER GROUPS OF EMPLOYEES A SMALLER PAY UNITED STATES COURT REPORTERS 209 48 1 RAISE AND YOU COULD -- YOU KNOW, BECAUSE IT'S NOT -- WE'RE NOT 2 THE SOVIET UNION AND WE'RE NOT POSTULATING THAT THESE COMPANIES 3 ARE THE SOVIET UNION. 4 COMMUNIST REGIME WHERE EVERYONE HAS AN EXPECTATION THAT THEY'RE 5 GOING TO BE PAID THE SAME AMOUNT AS THEIR COMRADE. 6 WE'RE NOT SAYING THAT THIS IS A BUT PEOPLE DO CARE ABOUT BEING PAID FAIRLY AND THEY DO 7 BELIEVE IF SOMEONE ELSE IS GETTING SOME GAINS, THEY SHOULD 8 SHARE IN THAT A LITTLE BIT. 9 THE COURT: SO WHY SHOULDN'T THEY GENERALLY RISE AND 10 FALL TOGETHER, EVEN IF THERE MIGHT BE SLIGHT DEVIATIONS? 11 SHOULDN'T THEY ALL RISE AND FALL TOGETHER UNDER YOUR THEORY? 12 13 14 MR. GLACKIN: WHY BECAUSE THERE ARE OTHER FACTORS THAT AFFECT COMPENSATION. AND WE'VE NEVER SAID THAT THIS -- THAT THESE AGREEMENTS OR 15 THAT COMPETITION AMONG THESE DEFENDANTS FOR WORKERS OR THAT 16 INTERNAL EQUITY ARE THE ONLY FACTORS THAT AFFECT COMPENSATION. 17 IT -- WE WOULD SAY THAT THERE IS -- THAT THERE ARE -- THAT 18 OTHER FORCES ARE GOING TO CONTINUE TO MOVE SALARIES AROUND, BUT 19 THAT THERE WILL BE -- IF ONE GROUP, IN THIS GREEN LINE HERE, IF 20 THEY GET A BIG BUMP IN ONE YEAR, THAT THAT IS GOING TO BE 21 SHARED, THAT THEY ARE NOT THE ONLY GROUP THAT IS GOING TO DO 22 BETTER THAT YEAR THAN THEY WOULD HAVE. 23 AND, AGAIN, THE THING TO REMEMBER HERE IS WE'RE TALKING 24 ABOUT A BUT-FOR WORLD THAT NEVER HAPPENED WHERE THERE WAS 25 INCREASED COMPETITION, AND WE'RE SAYING THAT IN THAT WORLD, IF UNITED STATES COURT REPORTERS 210 49 1 INCREASED COMPETITION CAUSED -- NOW, WE'RE NOT SAYING INCREASED 2 COMPETITION CAUSED THAT BUMP, RIGHT, BECAUSE THIS IS 2007 IN 3 THE MIDDLE OF THE AGREEMENTS. 4 BUT WE'RE SAYING IF INCREASED COMPETITION HAD CAUSED A 5 BUMP LIKE THAT FOR A JOB TITLE OR FOR A SMALL GROUP OF PEOPLE, 6 YOU WOULD EXPECT, UNDER INTERNAL EQUITY, THAT SOME -- THAT 7 OTHER PEOPLE IN THE SAME WORK FORCE WOULD SEE SOME GAINS AS 8 WELL. 9 THE COURT: WHY DID DR. LEAMER USE AVERAGED 10 COMPENSATION NUMBERS TO CREATE THESE CHARTS IN FIGURES 15, 16, 11 AND 17? 12 13 14 MR. GLACKIN: SO BECAUSE I THINK -- WELL, HE'S NOT BEEN ASKED THAT QUESTION. I WOULD SAY THAT WHEN YOU'RE TRYING TO ISOLATE THE 15 RELATIONSHIP THIS WAY, THAT THE MOST DESCRIPTIVE WAY TO DO THAT 16 IS TO USE AN AVERAGE. 17 THERE'S BEEN SOME TALK IN THIS CASE LIKE AVERAGING IS A 18 DIRTY TERM. 19 MATHEMATICAL PROCESSES, AND IT'S -- THERE ARE CERTAIN KINDS OF 20 DATA ANALYSIS THAT SIMPLY CAN'T BE DONE WITHOUT AVERAGING. 21 IT'S A FUNDAMENTAL WAY TO COMPARE DATA SETS TO ONE ANOTHER. 22 IT'S NOT. IT'S ONE OF THE MOST FUNDAMENTAL SO I THINK THAT YOU WOULD USE AVERAGING HERE FOR THE SAME 23 REASON YOU WOULD USE IT ANYWHERE, WHICH IS THAT WHEN YOU'RE 24 TRYING TO DISPLAY IN A WAY THAT'S EASY FOR SOMEONE LOOKING AT 25 IT TO SEE THE RELATIONSHIP OVER TIME, THAT AVERAGING IS USEFUL UNITED STATES COURT REPORTERS 211 50 1 FOR THAT PURPOSE. 2 YOU KNOW, DR. LEAMER TESTIFIED TO THIS AT HIS DEPO BECAUSE 3 HE WAS ASKED, I THINK, PRETTY MUCH THE SAME QUESTION AND HE 4 SAID, "YOU KNOW, WHEN I -- WHEN I TEACH STUDENTS ECONOMETRICS, 5 I SHOW THEM A CHART FULL OF NUMBERS AND THEN I SHOW THEM A 6 GRAPH WITH A LINE THAT REPRESENTS THOSE NUMBERS AND I SAY, WHEN 7 YOU LOOK AT THAT LINE, OR THAT CURVE OR WHATEVER IT IS, YOU ARE 8 SEEING WHAT YOU NEED TO SEE." 9 10 IT'S MORE USEFUL, IT'S MORE INFORMATIVE THAN LOOKING AT A CHART FULL OF NUMBERS. 11 THE COURT: AND IS IT THE PLAINTIFFS' POSITION THAT 12 THESE ARE REPRESENTATIVE OF HOW THE REST OF THE CLASS'S 13 ANALYSIS WOULD SIMILARLY COME OUT? 14 MADE A LOT OF THE FACT THAT THESE ARE JUST SORT OF TEN LIMITED 15 TITLES AT TWO OF THE MULTIPLE DEFENDANTS HERE. 16 MR. GLACKIN: OR -- I KNOW THE DEFENDANTS SO LET ME -- AND I APOLOGIZE, I NEED 17 TO STEP BACK A MINUTE AND MAKE ONE CORRECTION, WHICH IS, AGAIN, 18 THESE ARE NOT, STRICTLY SPEAKING, AVERAGES. 19 20 WHAT THEY ARE IS THE PREDICTED -- THE DOLLAR VALUE THAT'S PREDICTED BY THE REGRESSION BASED ON AN AGGREGATE DATA SET. 21 IT'S NOT -- BUT IT'S -- BUT "AVERAGE" IS AN OKAY TERM TO 22 USE. 23 REPRESENTATION OF AGGREGATE DATA USING ONE LINE, SO IT'S AN 24 AVERAGE KIND OF IN THAT SENSE. 25 I MEAN, IT'S CLOSE ENOUGH, I GUESS. IT IS DEFINITELY A SO WHAT WOULD WE SAY ABOUT THE REST OF THE DATA? UNITED STATES COURT REPORTERS 212 51 1 WELL, I THINK -- AGAIN, I MEAN, THE PURPOSE HERE WAS TO, 2 WAS TO ATTEMPT TO FALSIFY, AND SO DR. LEAMER DID NOT DO THIS -- 3 I MEAN, HE CERTAINLY HASN'T SHOWN US EVERY JOB TITLE. 4 SHOWN US AN ILLUSTRATION -- 5 6 THE COURT: I DON'T UNDERSTAND THE CONTEXT IN WHICH YOU'RE USING THAT WORD. 7 8 YOU KEEP SAYING "FALSIFY." HE'S MR. GLACKIN: SURE, OKAY. WELL, THIS IS ONE OF MY FAVORITE TOPICS. 9 THE COURT: 10 OKAY. MR. GLACKIN: 11 KEEP IT SHORT THEN. WELL -- (LAUGHTER.) 12 MR. GLACKIN: 13 I'LL TRY. I'LL REALLY TRY. SO THE CONCEPT OF FALSIFICATION IS CRUCIAL TO THE 14 SCIENTIFIC METHOD. 15 SCIENCE IN PARTICULAR, IT'S VERY HARD TO CONCLUSIVELY PROVE 16 ANYTHING EMPIRICALLY, AND IN ECONOMICS, IT'S PRETTY MUCH 17 IMPOSSIBLE. 18 IN SCIENCE IN GENERAL, AND IN SOCIAL WHAT YOU CAN DO IS YOU CAN PROPOSE A THEORY AND THEN YOU 19 CAN TEST IT, AND IF YOUR THEORY DOESN'T FAIL, THAT IS 20 INFERENTIAL SUPPORT THAT YOUR THEORY IS VALID. 21 HYPOTHETICAL BECOMES A THEORY UNDER THE SCIENTIFIC METHOD. 22 THAT'S HOW A AND SO WHAT DR. LEAMER IS DOING HERE IS HE'S SAYING, 23 "HERE'S AN EXAMPLE OF ME ASKING MYSELF IF I'M WRONG. I LOOK AT 24 THESE CHARTS AND I DON'T NEED THEM TO COME OUT A PARTICULAR 25 WAY. I DON'T NEED THE LINES TO BE IN A PARTICULAR PLACE. UNITED STATES COURT REPORTERS 213 52 1 "BUT THESE CHARTS TELL ME THAT MY CORRELATION ANALYSIS 2 DOESN'T HAVE THIS MAJOR PROBLEM, WHICH IS THIS YEARLY RESET 3 SORT OF HYPOTHETICAL, THAT I WAS AFRAID OF. 4 "AND SO, THEREFORE, THAT MAJOR PROBLEM NOT BEING THERE, I 5 AM MORE CONFIDENT IN MY CORRELATION ANALYSIS, WHICH I AM 6 OTHERWISE CONFIDENT IN." 7 THE COURT: BUT HOW CAN WE EXTRAPOLATE FROM THESE 8 TEN JOB TITLES AT TWO DEFENDANTS THAT THAT WOULD SIMILARLY BE 9 REFLECTED IF THE SAME ANALYSIS WAS DONE FOR ALL THE OTHER JOB 10 TITLES IN THE ALL EMPLOYEE CLASS FOR ALL DEFENDANTS? 11 MR. GLACKIN: WELL, I GUESS WHAT I WOULD SAY IS 12 THAT -- I MEAN, THERE'S -- THERE'S 500 -- THERE'S 100,000 13 EMPLOYEES. 14 THERE'S 500,000 OBSERVATIONS. YOU CANNOT CONCLUDE, FROM LOOKING AT THESE, THAT THE 15 ANSWER WOULD BE THE SAME IN EVERY CASE. 16 IT DOESN'T SAY THAT. 17 THIS IS A -- THIS IS A TEST FOR CLASS CERTIFICATION 18 PURPOSES. 19 FLAW EXISTS IN HIS MODEL. 20 I'D AGREE WITH THAT. THIS SHOWS DR. LEAMER ASKING HIMSELF IF THIS MAJOR THE COURT: HE DOESN'T SEE IT, SO WE MOVE ON. WHAT ABOUT 20 AND 22, PLEASE? 21 I'M UNCLEAR ON WHAT -- 22 MR. GLACKIN: WHAT -- I WILL SAY, IF I CAN JUST POINT ONE 23 THING OUT, THOUGH, WHICH IS THAT -- I MEAN, THESE WERE AT APPLE 24 AND GOOGLE. 25 ASKED ABOUT AT DR. LEAMER'S DEPOSITION -- THESE WERE TITLES FOR THEY WERE MAJOR TITLES -- AND I BELIEVE THIS WAS UNITED STATES COURT REPORTERS 214 53 1 WHICH THERE WERE A LOT OF OBSERVATIONS. 2 OF PEOPLE THAT -- A BUNCH OF TITLES THAT WERE INCONSEQUENTIAL 3 TO THE COMPANY I GUESS IS WHAT I WOULD SAY. 4 THE COURT: WE DIDN'T PICK A BUNCH LET ME ASK, WITH YOUR 100,000 ALL 5 EMPLOYEE CLASS, AND WITH 60,000 IN THE TECHNICAL ALTERNATIVE 6 CLASS -- NEVER MIND. I'LL STRIKE THAT QUESTION. 7 MR. GLACKIN: 8 THE COURT: 9 TELL ME ABOUT FIGURES 20 AND 22? 10 OKAY. LET'S GO AHEAD. MR. GLACKIN: OKAY. SO WHAT ELSE CAN YOU SO NOW WE ARE AT THE, AT WHAT'S 11 BEEN SOMEHOW -- SOMEBODY CALLED THIS THE CONDUCT REGRESSION AND 12 THAT STUCK AND SO PEOPLE CALL IT THE CONDUCT REGRESSION, AND 13 THIS IS THE REGRESSION ANALYSIS -- THE CORRELATION ANALYSIS WE 14 DISCUSSED IS ALSO A REGRESSION. 15 INCLUDES DEPENDENT VARIABLES, A DEPENDENT VARIABLE, AND 16 ATTEMPTS TO ESTIMATE THE EFFECT OF THE ANTICOMPETITIVE 17 AGREEMENTS. 18 19 20 THIS IS THE REGRESSION THAT I WILL TELL YOU AS MUCH AS I CAN ABOUT THE REGRESSION OUTPUTS. SO IF YOU LOOK AT FIGURE 20, THIS IS THE REGRESSION OUTPUT 21 FOR THE ALL SALARY CLASS. AND WHAT THAT MEANS IS YOU PUT THE 22 DATA IN, YOU WRITE CODE IN STATA, I THINK THEY -- I DON'T KNOW 23 WHICH OF THE TWO PROGRAMS THEY USE, BUT STATA IS COMMON -- YOU 24 HIT ENTER, AND IT ESTIMATES THESE COEFFICIENTS FOR THESE 25 DIFFERENT VARIABLES. UNITED STATES COURT REPORTERS 215 54 1 2 3 4 5 6 7 8 9 AND THE CONDUCT IS AT 1 THROUGH 4. I BELIEVE THAT'S WHAT'S BEING ESTIMATED. AND THEN THE VARIABLES BELOW THAT ARE THE VARIABLES THAT ARE DOING THE ESTIMATING. THE COURT: HOPEFULLY I GOT THAT RIGHT. WELL, I JUST DON'T KNOW WHAT -- IS THIS SHOWING UNDERCOMPENSATION? MR. GLACKIN: WHAT IS THIS SHOWING? YES. AND I JUST HAVE TO CONFESS, I'M -- I CAN'T POINT TO -- THE RESULT OF THESE -THE COURT: IS THIS ALL HYPOTHETICAL? OR THIS IS 10 THE SAME THING WHERE YOU TOOK AGGREGATED DATA OF ALL EMPLOYEES 11 OF ALL DEFENDANTS? 12 MR. GLACKIN: WELL, WE DIDN'T TAKE -- SO WE DID NOT 13 TAKE -- I JUST WANT TO BE CAREFUL ABOUT TERMS. 14 WE DIDN'T START WITH AGGREGATE DATA. WE STARTED WITH THE 15 WHOLE TRANSACTIONAL DATABASE -- EXCUSE ME -- THE WHOLE 16 COMPENSATION DATABASE. 17 OBSERVATIONS A YEAR FOR HOWEVER MANY YEARS. 18 19 20 21 22 23 24 25 SO ALL 500,000 OBSERVATIONS, 100,000 AND -THE COURT: AND "OBSERVATION" BEING THE TOTAL COMPENSATION FOR A SINGLE EMPLOYEE AT A DEFENDANT? MR. GLACKIN: CORRECT, WHAT SOMEBODY WAS PAID IN A YEAR, IN A PARTICULAR YEAR IS AN OBSERVATION. AND WE ASKED -- YES, THAT WAS THE DATA SET THAT WAS USED TO ESTIMATE THIS. AND THEN DR. LEAMER HAS PROGRAMMED A STATISTICAL UNITED STATES COURT REPORTERS 216 55 1 REGRESSION ANALYSIS THAT ATTEMPTS TO ANSWER THE QUESTION OF 2 WHAT COMPENSATION -- WHAT THEIR COMPENSATION SHOULD HAVE BEEN 3 IF THE AGREEMENTS HAD NOT BEEN IN PLACE. 4 THE COURT: SO THIS DEPENDENT VARIABLE THAT'S AT THE 5 TOP OF FIGURE 20, THAT'S THE HYPOTHETICAL INDIVIDUAL'S 6 COMPENSATION? 7 THAT YOU ANALYZED? 8 9 OR THAT'S AN AVERAGE OF ALL OF THE OBSERVATIONS WHAT IS THAT NUMBER? MR. GLACKIN: RIGHT. SO WHAT -- I'M -- AND THE ONLY REASON I'M GETTING TRIPPED UP A LITTLE BIT IS BECAUSE THE 10 EXACT -- WHAT EXACTLY EACH OF THESE REPRESENTS I'M -- I WANT TO 11 BE VERY CAREFUL ABOUT WHAT I SAY. 12 THE EASIEST WAY FOR ME TO EXPLAIN IT IS WHAT THE 13 REGRESSION DOES IS IT ESTIMATES, USING ALL THIS DATA, A SINGLE 14 VARIABLE FOR IMPACT OF THE AGREEMENTS, AND I THINK THAT MIGHT 15 BE THE QUESTION YOU'RE TRYING -- YOU'RE GETTING TO, AND I WILL 16 ADMIT THAT THAT IS WHAT IT DOES. 17 VARIABLE REPRESENTING THE ESTIMATED EFFECT OF THE AGREEMENTS. 18 IT IS ESTIMATING A SINGLE AND I CAN TELL YOU THAT IN BROAD TERMS WHAT IT'S DOING IS 19 IT'S LOOKING AT THE RELATIONSHIP OF COMPENSATION OF EMPLOYEES 20 IN YEARS PRIOR TO AND AFTER THE CONSPIRACY. 21 THE RELATIONSHIP BETWEEN COMPENSATION AND CERTAIN KNOWN 22 VARIABLES, LIKE AGE COMPOSITION -- EXCUSE ME -- LIKE 23 UNEMPLOYMENT IN SANTA CLARA, OR THE EMPLOYMENT RATE IN 24 SANTA CLARA COUNTY WAS USED TO -- EXCUSE ME -- REPRESENT THE 25 ROBUSTNESS OR THE HEALTH OF THE TECHNOLOGY SECTOR IN WHICH UNITED STATES COURT REPORTERS IT'S LOOKING AT 217 56 1 THESE COMPANIES OPERATE. 2 IT ESTIMATES THE RELATIONSHIP BETWEEN COMPENSATION AND 3 THAT -- AND A SET OF VARIABLES LIKE THAT, AND THEN IT ASKS, 4 ASSUMING THAT THAT RELATIONSHIP IS MEANINGFUL, WHAT WAS THE 5 EFFECT OF -- WHAT SHOULD HAVE BEEN THE COMPENSATION THAT WAS 6 PAID DURING THE PERIOD UNDER STUDY? 7 AND THEN THAT IS EXPRESSED AS A VARIABLE. AND THEN IT IS 8 POSSIBLE, USING THAT VARIABLE, TO DERIVE THE -- WELL, AND THEN 9 THE NEXT STEP ACTUALLY IS IN ORDER TO ACCOUNT FOR THE 10 HETEROGENEITY AT THESE FIRMS, IN ORDER TO ACCOUNT FOR THE FACT 11 THAT THEY'RE NOT ALL THE SAME, DR. LEAMER HAS THEN, FOR EVERY 12 FIRM, TAKEN THE CONDUCT VARIABLE AND ALLOWED IT TO BE CHANGED 13 DEPENDING ON FIRM-SPECIFIC FACTORS, SUCH AS A COMPANY'S 14 REVENUES, SUCH AS THE AGE COMPOSITION OF THE WORK FORCE. 15 16 THE COURT: IS THAT THE MINUS 1 AND MINUS 2? IS THAT 5 THROUGH 18? 17 MR. GLACKIN: YES. I THINK THAT'S PROBABLY -- YOU 18 KNOW, THAT IS PROBABLY REPRESENTING EXACTLY THE INTERACTIVE 19 RESULT. 20 AND THEN USING THAT DIFFERENT VARIABLE, THE NEW VARIABLE 21 FOR EVERY COMPANY FOR EACH YEAR, DR. LEAMER THEN IS ABLE TO 22 GENERATE AN ESTIMATE OF THE PERCENTAGE BY WHICH TOTAL 23 COMPENSATION WAS REDUCED AT THE COMPANY. 24 25 THE COURT: SO SOMEHOW HE'S ABLE TO CALCULATE HOW MUCH EACH EMPLOYEE SHOULD HAVE BEEN PAID AND WHAT PERCENTAGE OF UNITED STATES COURT REPORTERS 218 57 1 WHAT THEY WERE PAID THAT DELTA IS? 2 SHOWING? 3 MR. GLACKIN: 4 THE COURT: 5 WHAT IS THAT? 6 CORRECT. IS THAT WHAT THIS IS WELL, WHAT HE'S -- WHAT IS THIS IN THIS ESTIMATE COLUMN? THAT'S SAYING HOW MUCH OF THE TOTAL COMPENSATION -- 7 MR. GLACKIN: 8 THE COURT: 9 MR. GLACKIN: I'M ONLY -- SORRY. GO AHEAD. I'M ONLY HESITATING BECAUSE I DON'T 10 THINK THAT -- I DON'T KNOW THAT YOU CAN LOOK AT, FOR EXAMPLE, 11 THE LINE CONDUCT AND SAY THAT THAT MEANS MINUS 16 PERCENT. 12 DON'T THINK THAT THAT'S EXACTLY HOW YOU INTERPRET THAT. 13 I BUT WHAT THAT IS IS -- IT REPRESENTS THE DELTA, IF YOU 14 WILL, BETWEEN WHAT THE REGRESSION PREDICTS PEOPLE SHOULD HAVE 15 BEEN PAID AND WHAT THEY WERE ACTUALLY PAID. 16 AND IT'S -- STRICTLY SPEAKING, IT'S THE DELTA BETWEEN THE 17 TOTAL COMPENSATION, THE PREDICTED TOTAL COMPENSATION AT THE 18 FIRM AND THE ACTUAL COMPENSATION. 19 THE COURT: AND HOW DID HE COME UP WITH THE 20 PREDICTED COMPENSATION? 21 MR. GLACKIN: SO IN -- BY -- THE WAY REGRESSION 22 ANALYSIS WORKS IS YOU PICK A SET OF VARIABLES THAT ARE CALLED 23 THE EXPLANATORY VARIABLES, AND THESE ARE THE VARIABLES THAT YOU 24 THINK SHOULD EXPLAIN COMPENSATION, AND YOU EXAMINE THE 25 RELATIONSHIP BETWEEN THE EXPLANATORY VARIABLES AND COMPENSATION UNITED STATES COURT REPORTERS 219 58 1 DURING A TIME PERIOD NOT AFFECTED BY THE AGREEMENTS AND YOU 2 EXPRESS THAT RELATIONSHIP IN NUMBERS. 3 4 AND I BELIEVE THAT THAT IS THE -- SOME OF THAT IS WHAT'S HERE IN THE REGRESSION OUTPUT. 5 THEN YOU ASK YOURSELF, IF THOSE RELATIONSHIPS ARE STEADY, 6 AND THERE'S NO REASON TO BELIEVE THEY'RE NOT -- AND THAT'S ONE 7 THING WE TEST FOR, I THINK, AS YOU'RE DOING THE REGRESSION, 8 WHAT SHOULD HAVE BEEN COMPENSATION DURING THE PERIOD THAT THE 9 AGREEMENTS WERE IN EFFECT? 10 I MEAN, LIKE A -- THIS IS A TOTALLY SIMPLISTIC WAY TO LOOK 11 AT IT, BUT SUPPOSE YOU SHOW THAT, OR YOU -- YOUR REGRESSION 12 SHOWS THAT WHEN A COMPANY'S REVENUES GO UP, WORKER COMPENSATION 13 TENDS TO GO UP BY A CERTAIN AMOUNT. 14 BETWEEN INCREASED REVENUES AT A COMPANY AND WORKER 15 COMPENSATION. 16 THERE'S A RELATIONSHIP THEN YOU LOOK AT THE PERIOD UNDER STUDY AND YOU ASK 17 YOURSELF, WELL, IN THIS AREA WHERE -- YOU KNOW, DURING THIS 18 PERIOD OF TIME WHEN COMPETITION WAS RESTRAINED, DOES THE -- 19 DOES THAT RELATIONSHIP APPEAR TO BE RESPECTED? 20 IN REVENUES OR A DIMINISHMENT IN REVENUES HAVING THE EXPECTED 21 EFFECT ON COMPENSATION? 22 23 24 25 IS AN INCREASE THAT'S THE QUESTION YOU'RE ASKING. YOU PREDICT THAT, SEEING A COMPANY'S REVENUES GO UP, THE COMPENSATION SHOULD GO UP BY A CERTAIN AMOUNT. AND IF YOU SEE THAT NOT HAPPENING, THE REGRESSION IS TELLING YOU THAT THAT'S THE EFFECT OF THE THING THAT YOU'RE UNITED STATES COURT REPORTERS 220 59 1 2 STUDYING. AND THAT'S -- THIS IS A VERY UNEDUCATED WAY FOR ME OF -- 3 BECAUSE I'VE REACHED THE LIMITS, I THINK, OF WHAT I CAN 4 EXPLAIN. 5 THE COURT: WHAT ABOUT FIGURE 22? 6 MR. GLACKIN: WHAT IS THIS? SO FIGURE 22 IS TAKING THIS VALUE -- 7 SO WHAT THE -- WHAT THE REGRESSION TELLS YOU IS THE VALUE OF 8 THE CONDUCT VARIABLE, AND IF YOU APPLY THE CONDUCT VARIABLE TO 9 TOTAL COMPENSATION, OR -- IT TELLS YOU THE -- THE REGRESSION 10 TELLS YOU THE COMPENSATION THAT SHOULD HAVE BEEN. 11 HERE ON 22 IS THE AMOUNT BY WHICH ACTUAL COMPENSATION WAS LOWER 12 THAN THE COMPENSATION THAT SHOULD HAVE BEEN. 13 THE COURT: THIS FIGURE SO EVERY INDIVIDUAL EMPLOYEE OF THESE 14 COMPANIES RECEIVED THIS LEVEL, THIS PERCENTAGE REDUCTION IN 15 THEIR TOTAL COMPENSATION BECAUSE OF THE AGREEMENTS? 16 MR. GLACKIN: 17 THE COURT: 18 MR. GLACKIN: NO, NO. THAT'S NOT WHAT WE'RE SAYING. OKAY. WHAT WE'RE SAYING IS THAT, FOR 19 EXAMPLE, IN 2005 AT ADOBE, THE TOTAL COMPENSATION PAID TO 20 EMPLOYEES WAS 1.6 PERCENT LOWER THAN THE REGRESSION PREDICTS IT 21 SHOULD HAVE BEEN. 22 THE COURT: BECAUSE OF THE AGREEMENTS? 23 MR. GLACKIN: BECAUSE OF THE AGREEMENTS, EXACTLY. 24 BECAUSE THE ONLY THING THAT'S DIFFERENT ABOUT THE TWO PERIODS 25 OF TIME YOU'RE STUDYING IS THE AGREEMENTS. UNITED STATES COURT REPORTERS 221 60 1 2 THE COURT: BUT THAT APPLIES TO EVERY EMPLOYEE'S COMPENSATION AT ADOBE IN THAT YEAR. 3 MR. GLACKIN: RIGHT? WELL, IT APPLIES IN THE SENSE THAT 4 EVERY, EVERY MEMBER OF THE CLASS WAS PAID OUT OF THAT PILE OF 5 MONEY, OUT OF THAT TOTAL COMPENSATION. 6 IT DOESN'T APPLY -- WE ARE NOT SAYING THAT THERE WAS A 1.6 7 PERCENT -- THAT IT WAS 1.6 PERCENT FOR EVERY EMPLOYEE. 8 CAN'T -- WE CANNOT ESTIMATE -- 9 THE COURT: WE OH, YOU'RE SAYING IN TOTAL, THE TOTAL 10 COMPENSATION WAS THAT MUCH LESS? 11 MR. GLACKIN: 12 THE COURT: 13 MR. GLACKIN: EXACTLY. I SEE. TOTAL -- SO IN 2005, ADOBE PAID ITS 14 EMPLOYEES A MILLION DOLLARS -- A BILLION DOLLARS AND, IN 15 REALITY, ADOBE SHOULD HAVE PAID ITS EMPLOYEES 1.6 PERCENT MORE 16 THAN THAT. 17 18 THE COURT: I SEE. OKAY. ALL RIGHT. I HAVE SOME MORE QUESTIONS, BUT I'D LIKE TO -- 19 LET ME ASK MS. SHORTRIDGE -- 20 (DISCUSSION OFF THE RECORD BETWEEN THE COURT AND THE COURT 21 22 23 24 25 REPORTER.) THE COURT: AND I DO WANT TO HANDLE THE CMC AND TALK ABOUT DISCOVERY. LET ME ASK, SINCE WE DON'T HAVE THE DATA ON WHO WOULD HAVE BEEN COLD CALLED AND HOW MANY COLD CALLS WOULD HAVE ACTUALLY UNITED STATES COURT REPORTERS 222 61 1 BEEN CONDUCTED AND A LOT OF THE DATA IS NOT TRANSPARENT FROM 2 THE PAYROLL RECORDS, WHICH ARE SORT OF THE LIMITED UNIVERSE OF 3 WHAT DOES EXIST IN TERMS OF DOCUMENTATION, WHAT IS THERE TO 4 LINK THE DO NOT COLD CALL AGREEMENTS WITH DECREASED MOBILITY? 5 MR. GLACKIN: SO YOU'RE ASKING -- I GUESS, WHEN YOU 6 SAY WHAT IS IT, ARE YOU ASKING ME FROM A DATA PERSPECTIVE OR A 7 THEORY PERSPECTIVE OR FROM A DOCUMENTARY EVIDENCE PERSPECTIVE? 8 9 10 THE COURT: WELL, I GUESS I'M ASKING YOU FROM A HOW DO WE FIND DR. LEAMER AS NOT OVERLY SPECULATIVE PERSPECTIVE? 11 MR. GLACKIN: 12 THE COURT: 13 MR. GLACKIN: OKAY. YEAH. SO FIRST OF ALL, THE ECONOMIC THEORY 14 PREDICTS THAT REDUCED COLD CALLING WOULD HAVE THIS KIND OF 15 EFFECT. 16 THE COURT: UM-HUM. 17 MR. GLACKIN: AND IT'S NOT FRINGE ECONOMIC THEORY. 18 THIS IS MAIN STREAM, NOBEL PRIZE WINNING ECONOMIC THEORY. 19 SO THE THING THAT DR. LEAMER DID FROM A QUANTITATIVE 20 STANDPOINT TO TEST FOR WHAT HE CALLS THE PRICE DISCOVERY 21 PROCESS WAS THAT WAS THE MOVERS AND STAYERS ANALYSIS, AND WHAT 22 DR. LEAMER IS DOING THERE -- AND I CAN POINT YOU TO THE CHART 23 IF YOU WANT TO SEE IT. 24 RIGHT, PAGE 37 AND PAGE 38. 25 I THINK IT'S PAGE 37 AND PAGE 38. SO THE PREMISE OF THE PRICE DISCOVERY THEORY IS THAT LABOR UNITED STATES COURT REPORTERS 223 62 1 IS NOT A COMMODITY, AND THAT PEOPLE AREN'T PAID LIKE YOU SELL 2 PORK BELLIES ON THE CBOT, AND THAT WAGES ARE -- THAT PEOPLE -- 3 THAT WORKERS AND EMPLOYERS IN THE MARKET ARE CONSTANTLY LOOKING 4 FOR BETTER PRICE OR THE RIGHT PRICE FOR THEIR -- FOR THE SKILLS 5 THAT THEY ARE SEEKING TO BUY OR SELL. 6 NOW, IF YOU -- ONE SYMPTOM OF THAT, IF THAT'S TRUE, ONE 7 SYMPTOM OF THAT WOULD BE THAT WHEN PEOPLE LEAVE A COMPANY, THEY 8 SEE INCREASES IN THEIR PAY, AND IF YOU ASKED YOURSELF WHAT 9 HAPPENS TO PEOPLE WHEN THEY LEAVE THEIR COMPANY AND THE ANSWER 10 WAS THEY DIDN'T GET A BIG BUMP IN PAY, RIGHT, THAT WOULD 11 SUGGEST THAT THERE IS NOT -- YOU'RE WORKING WITH A MARKET WHERE 12 THERE ISN'T AN INFORMATION IMPERFECTION AND THAT EVERYBODY DOES 13 KNOW, SORT OF A PRIORI, WHAT THEY'RE WORTH. 14 SO DR. LEAMER -- WE WERE ABLE -- AGAIN, WE WERE WORKING 15 WITH THE DATA WE HAVE. 16 COMPENSATION THAT PEOPLE EXPERIENCE WHEN THEY MOVE BETWEEN 17 THESE FIRMS BECAUSE WE COULD TRACK THEM USING UNIQUE 18 IDENTIFICATION. 19 WE WERE ABLE TO LOOK AT THE CHANGE IN AND WHAT WE -- WHAT DR. LEAMER SAW IS THAT WHEN PEOPLE 20 MOVE FIRMS, THEY GOT A BIG PAY RAISE. 21 SURPRISING, ESPECIALLY IN THIS CONTEXT BECAUSE, AGAIN, WE'RE 22 NOT TALKING ABOUT COMMODITIES AND WE'RE NOT -- WE'RE ALSO NOT 23 TALKING ABOUT PEOPLE WHO ARE WORKING FOR MINIMUM WAGE AT A FAST 24 FOOD RESTAURANT. 25 AND THAT'S NOT THESE ARE SKILLED WORK FORCES. SO THAT CONFIRMS THAT THERE -- THAT THERE IS AN UNITED STATES COURT REPORTERS 224 63 1 INFORMATION PROBLEM IN THIS MARKET, THAT THE PEOPLE IN THE 2 MARKET DON'T HAVE PERFECT INFORMATION, THAT THEY ARE LOOKING TO 3 GET A BETTER PRICE FOR THEIR SKILLS, AND THAT WHEN THEY MOVE 4 FROM ONE DEFENDANT TO ANOTHER, THEY DO, ON AVERAGE, GET A MUCH 5 BETTER PRICE FOR THEIR SKILLS. 6 THAT'S WHAT THIS SHOWS. SO, AGAIN, IT'S AN ATTEMPT TO SAY -- IT'S AN ATTEMPT TO 7 QUESTION, IS THIS THING THAT STANDARD ECONOMIC THEORY PREDICTS, 8 IS IT TRUE OF THIS MARKET WHERE I BELIEVE IT IS TRUE? 9 THIS TEST. 10 I'LL RUN I -- THE TEST IS CONSISTENT WITH WHAT I WOULD PREDICT, SO THAT IS A REASON FOR ME TO BELIEVE I AM CORRECT. 11 THE COURT: HOW DO YOU EXPLAIN THAT THERE HAVEN'T 12 BEEN MANY HIRES AMONGST THE DEFENDANTS AFTER THE INJUNCTION WAS 13 ENTERED IN THE D.O.J. CASE IN D.C.? 14 15 16 17 18 MR. GLACKIN: SO THAT'S AN EXCELLENT QUESTION. THAT'S A VERY INTERESTING QUESTION ACTUALLY. I DON'T -- I CAN'T -- I DON'T HAVE THE EXPLANATION FOR WHY THAT IS. I DO KNOW THAT IN SOME OF THE DEPOSITIONS THAT HAVE 19 OCCURRED -- AT LEAST, I KNOW OF ONE WHERE THE WITNESS TESTIFIED 20 THAT THE COMPANY, NOTWITHSTANDING THE INJUNCTION, CONTINUES TO 21 UNILATERALLY, SUPPOSEDLY UNILATERALLY SIMPLY NOT HIRE FROM THE 22 COMPANY WITH WHICH IT PREVIOUSLY HAD AN AGREEMENT. 23 SO IT MIGHT BE THAT THEY ARE CONTINUING TO VIOLATE THE 24 LAW, OR IT MIGHT BE THAT THEY HAVE ALL -- THEY'RE NOT TALKING 25 TO EACH OTHER, BUT THEY ARE ALL UNILATERALLY DECIDING TO UNITED STATES COURT REPORTERS 225 64 1 CONTINUE TO NOT POACH EACH OTHER'S EMPLOYEES, OR IT MIGHT BE 2 SOME OTHER REASON. 3 EXPLAIN THAT. 4 I DON'T HAVE THE -- WE HAVEN'T TRIED TO THE COURT: UM-HUM. 5 OKAY. LET ME ASK THE DEFENDANTS A FEW QUESTIONS. 6 YOUR EXPERT, DR. MURPHY, FOCUSES ONLY ON PEOPLE WHO 7 ACTUALLY LEFT ONE OF THE DEFENDANT COMPANIES FOR ONE OF THE 8 CO-DEFENDANTS, AND I FIND DR. LEAMER'S THEORY THAT THAT'S TOO 9 LIMITED IN HOW YOU LOOK AT ANY POTENTIAL DAMAGE PERSUASIVE 10 BECAUSE, AS YOU SAID, IF AN EMPLOYEE GETS A BETTER OFFER FROM 11 ANOTHER COMPANY, THEY CAN VERY MUCH GO AND TRY TO NEGOTIATE AN 12 INCREASE IN THEIR OWN SALARY FROM THEIR CURRENT EMPLOYER. 13 AND SO WHY SHOULDN'T THAT BE TAKEN INTO ACCOUNT IN 14 DETERMINING WHETHER THERE'S DAMAGE VERSUS JUST LOOKING AT WHO'S 15 ACTUALLY MOVED, THE MOBILITY VERSUS ACTUAL MOVEMENT SORT OF 16 DISTINCTION THAT DR. LEAMER MAKES? 17 MR. MITTELSTAEDT: WELL, DR. MURPHY LOOKED AT 18 MOVEMENT FOR A DIFFERENT REASON. 19 PERCENT OF THE EMPLOYEES WHO LEFT THESE DEFENDANTS OR CAME TO 20 THESE DEFENDANTS CAME FROM NON-DEFENDANTS. 21 THE COURT: 22 HIS POINT ON MOVEMENT WAS 99 AGREEMENTS IN EFFECT. 23 24 25 BECAUSE THERE WERE THESE COLLUSIVE MR. MITTELSTAEDT: BEFORE THE AGREEMENT. NO, BEFORE. BEFORE, YOUR HONOR. IT DIDN'T CHANGE DURING THE AGREEMENT. AND THE POINT THAT MAKES IS THESE AGREEMENTS AFFECTED SUCH UNITED STATES COURT REPORTERS 226 65 1 A SMALL PERCENT OF THE MARKET THAT THERE WOULD BE NO REASON TO 2 THINK THERE WOULD BE ANY MEASURABLE OR BROAD IMPACT AT ALL, AND 3 EVEN FOR THE COMPANIES THAT HAD NO COLD CALL AGREEMENTS. 4 THE INFORMATION THAT AN EMPLOYEE WOULD HAVE RECEIVED WOULD 5 HAVE BEEN REPLACED -- OR WOULD HAVE COME FROM SOMEPLACE ELSE 6 BECAUSE THAT PERSON CONTINUED TO GET COLD CALLS IF THEY WERE 7 GETTING COLD CALLS FROM ALL THE -- 8 9 THE COURT: I THOUGHT THAT HE LIMITED HIS DATA TO JUST DURING THE CLASS PERIOD AND AFTER, WHEREAS DR. LEAMER 10 LOOKED AT BEFORE THE CLASS PERIOD, DURING THE CLASS PERIOD, AND 11 THEN AFTER. 12 MR. MITTELSTAEDT: 13 THE COURT: I THINK -- I THINK THIS -- DR. MURPHY LOOKED -- 14 NO. ISN'T THAT IN ONE INSTANCE WHERE 15 DR. MURPHY ONLY LOOKED AT THE CLASS PERIOD AND THEN TWO 16 YEARS -- HE LOOKED AT 2010/2011, BUT DID NOT ANALYZE THE PRE -- 17 MR. MITTELSTAEDT: 18 19 THE COURT: INSTANCE. 20 21 22 I THINK -- -- PERIOD. I KNOW THAT OCCURRED IN ONE I CAN'T REMEMBER EXACTLY THE CONTEXT. MR. GLACKIN: EXCUSE ME. I DIDN'T MEAN TO TALK OVER YOU. YOU MIGHT BE THINKING OF THE REGRESSION ANALYSIS WHERE 23 DR. MURPHY -- BASICALLY ONE OF HIS SENSITIVITY ANALYSES IS TO 24 ONLY USE HALF THE DATA AND RUN THE REGRESSION USING ONLY THE 25 AFTER PERIOD OR ONLY THE BEFORE PERIOD AND HE CLAIMS THAT UNITED STATES COURT REPORTERS 227 66 1 THAT'S PROBLEMATIC. 2 THAT MIGHT BE WHAT YOU'RE THINKING OF. MR. MITTELSTAEDT: YOUR HONOR, I'M REFERRING TO 3 MURPHY TABLE NUMBER 1 AT PAGE 8 AND APPENDIX 1A, WHICH SHOWS 4 BEFORE AS WELL. 5 BUT, YOUR HONOR, THERE IS A MUCH MORE FUNDAMENTAL PROBLEM 6 HERE, AND WHEN YOU WALK THROUGH WHAT LEAMER SUPPOSEDLY DID, 7 THAT WAS JUST NOT RIGHT. 8 LIKE TO, TO MAKE TWO POINTS. 9 THE COURT: IT WAS JUST NOT RIGHT, AND I WOULD CAN I ASK YOU, ALL OF THE DEFENDANTS' 10 POSITIONS SORT OF FLY IN THE FACE OF YOUR DOCUMENTS THAT WERE 11 CREATED CONTEMPORANEOUSLY. 12 CALLING CANDIDATES IS ONE OF THE MOST EFFICIENT AND EFFECTIVE 13 WAYS TO RECRUIT. 14 OFFER, THAT IT CAUSES UNHAPPINESS AND YOU HAVE TO HAVE A 15 SYSTEMATIC APPROACH TO COMPENSATION TO AVOID THESE BIDDING 16 WARS. 17 I MEAN, THE DOCUMENTS SAY COLD IT TALKS ALL ABOUT WHEN PEOPLE GET A COUNTER THAT I THINK IS THE BIGGEST PROBLEM FOR THE DEFENDANTS IS 18 THAT THE CONTEMPORANEOUS DOCUMENTS THAT WERE CREATED AT THE 19 TIME SORT OF ACKNOWLEDGE ALL OF THE EFFECTS THAT DR. LEAMER IS 20 TRYING TO PROVE. 21 22 23 I WILL AGREE THAT THERE ARE A LOT OF HOLES IN DR. LEAMER'S ANALYSIS. BUT ONE OF THE STRONGEST PIECES OF EVIDENCE THE PLAINTIFFS 24 HAVE IS YOUR OWN DOCUMENTS. 25 MR. MITTELSTAEDT: I DON'T THINK THAT'S RIGHT, YOUR UNITED STATES COURT REPORTERS 228 67 1 HONOR. 2 THE COURT: UM-HUM. 3 MR. MITTELSTAEDT: THERE IS NOT A SINGLE DOCUMENT 4 THAT SAYS WE'VE GIVEN A RAISE TO SOMEBODY AND SO NOW WE'RE 5 GOING TO RAISE EVERYBODY ELSE IN THAT PERSON'S WORK GROUP, LET 6 ALONE THAT WE'RE GOING TO RAISE EVERYBODY IN THE REST OF THE 7 COMPANY, LET ALONE THAT ALL THE OTHER COMPANIES ARE GOING TO 8 FOLLOW. 9 10 11 THEY DO NOT SAY THAT. THEY EXPRESS CONCERN ABOUT INTERNAL EQUITY. THEY TAKE A LOOK AT IT. 12 BUT, YOUR HONOR, IN THE BEFORE PERIOD, AS I SAID BEFORE, 13 IF THE PLAINTIFFS' RIPPLE THEORY WORKED, THERE WOULD BE A LOT 14 OF EVIDENCE IN IT, OF IT, AND IT WOULD BE IN THE DATA AND IT'S 15 NOT IN THE DATA. 16 THE COURT: I MEAN, DO YOU WANT ME TO GET INTO THESE 17 E-MAILS? 18 DON'T TALK ABOUT IF SOMEONE GETS A BETTER OFFER FROM A 19 COMPETITOR, YOU HAVE TO MAKE THE DECISION OF WHETHER YOU WANT 20 TO KEEP THIS PERSON BY RAISING THEIR COMPENSATION OR LETTING 21 THEM GO AND HOW WE SHOULDN'T DEAL WITH THIS IN THIS WAY, THAT 22 WE SHOULD HAVE A SYSTEMATIC APPROACH SO WE'RE NOT HAVING TO BUY 23 PEOPLE OFF INDIVIDUALLY. 24 25 I'M HAPPY TO DO IT. I DISAGREE WITH YOU THAT THEY I MEAN, IF YOU WANT TO GET INTO THESE DOCUMENTS, I'M HAPPY TO DO THAT. BUT TO SAY THEY DON'T EXIST -- UNITED STATES COURT REPORTERS 229 68 1 MR. MITTELSTAEDT: 2 THE COURT: 3 MR. MITTELSTAEDT: 4 THE COURT: 5 MR. MITTELSTAEDT: 6 -- I FIND IS REALLY PROBLEMATIC. YOUR HONOR -- YEAH. -- THE DOCUMENT I THINK YOU'RE REFERRING TO, OR THE DOCUMENTS, TALK ABOUT INDIVIDUALS. 7 IF WE -- 8 9 NO. THE COURT: AND THEY TALK ABOUT WHY THE INDIVIDUAL METHOD OF DEALING WITH THIS IS INFERIOR TO HAVING A SYSTEMATIC 10 APPROACH TO AVOIDING THESE BIDDING WARS BY HAVING THESE 11 COLLUSIVE AGREEMENTS WITH THE OTHER CO-DEFENDANTS. 12 MR. MITTELSTAEDT: 13 THE COURT: 14 MR. MITTELSTAEDT: BUT, YOUR HONOR -- YEAH. -- THAT DOES NOT HELP DETERMINE 15 WHICH OF THE EMPLOYEES WERE IMPACTED AND WHICH ONES WERE NOT 16 AND WHICH ONES BENEFITED. 17 AND WHEN I SAY THAT, WHAT I MEAN IS FOR ANY EMPLOYEE WHO 18 MISSED OUT ON A COLD CALL AND, THEREFORE, DIDN'T GET THE CHANCE 19 TO NEGOTIATE A JOB RAISE OR GET A NEW JOB, SOMEBODY GOT THAT 20 JOB. 21 22 23 SOMEBODY GOT THAT JOB. AND BECAUSE -- AND THEY'RE A CLASS MEMBER. AND SO WHAT WE HAVE HERE IN THIS GROUP -THE COURT: SO HOW DO WE KNOW THAT THAT PERSON WHO 24 CAME FROM A NON-DEFENDANT WHO GOT THE JOB WOULDN'T HAVE BEEN 25 PAID MORE BUT FOR THESE COLLUSIVE AGREEMENTS? UNITED STATES COURT REPORTERS HOW DO YOU KNOW 230 69 1 THAT? 2 MR. MITTELSTAEDT: WELL, THAT PERSON IS BETTER OFF 3 BECAUSE THAT PERSON TOOK THE JOB. 4 TAKEN THE JOB OTHERWISE? 5 I MEAN, WHY WOULD THEY HAVE THEY GOT THE JOB THAT -- 6 THE COURT: BUT WOULD YOU AGREE THAT THEY COULD HAVE 7 POTENTIALLY BEEN PAID MORE, THAT THAT JOB COULD HAVE BEEN WORTH 8 MORE IF THESE AGREEMENTS DIDN'T EXIST? 9 MR. MITTELSTAEDT: NO, I DON'T THINK THERE'S ANY 10 REASON TO THINK THAT BECAUSE OF THE 99 PERCENT POINT. 99 11 PERCENT OF THE MOVEMENT, MOBILITY, WHATEVER ANYONE WANTS TO 12 CALL IT, WAS UNAFFECTED BY ANY OF THIS. 13 BUT, YOUR HONOR, I REALLY WANT TO EXPLAIN, IF I CAN, WHAT 14 LEAMER IS DOING, BECAUSE THE ANSWERS YOU RECEIVED ARE JUST NOT 15 RIGHT, AND I'VE GOT -- AND I KNOW THAT, YOU KNOW, WE'RE SHORT 16 OF TIME, BUT I'VE HARDLY SAID ANYTHING AND I'VE GOT A BINDER 17 THAT WILL ALLOW ME TO WALK YOUR HONOR THROUGH WHAT'S REALLY 18 GOING ON HERE AS EXPEDITIOUSLY AS POSSIBLE, IF I CAN JUST DO 19 THIS. 20 THE COURT: 21 LOOKING QUITE THICK. 22 HOW MANY PAGES IS THAT BINDER? MR. MITTELSTAEDT: IT'S WELL, I'LL SKIP -- I'LL JUST GO 23 TO THE LEAMER PART, WHICH IS 37 PAGES, AND I CAN WALK YOUR 24 HONOR THROUGH IT QUICK AND I WON'T GO THROUGH ALL OF THEM. 25 JUST WANT TO GIVE YOU A FLAVOR -- UNITED STATES COURT REPORTERS I 231 70 1 THE COURT: HAVE YOU SHOWN THAT TO THE PLAINTIFFS? 2 MR. MITTELSTAEDT: 3 THE COURT: YES. WE GAVE IT TO THEM. WHY DON'T I TAKE A COPY OF IT, I'LL 4 REVIEW IT DURING THE BREAK, AND IF I HAVE QUESTIONS, I CAN ASK 5 YOU SPECIFICALLY. 6 I MEAN, I AGREE WITH YOU, FRANKLY, BOTH EXPERTS -- BOTH 7 EXPERTS' REPORTS HAVE A LOT OF ISSUES. 8 I THINK BOTH HAVE -- 9 MR. MITTELSTAEDT: 10 11 THE COURT: ECONOMICS. 12 I'LL PUT IT THAT WAY. YOUR HONOR -- -- A CONSIDERABLE AMOUNT OF CREATIVE I'LL PUT IT THAT WAY. MR. MITTELSTAEDT: YOUR HONOR, THEY HAVE THE BURDEN 13 HERE, AND THEIR BURDEN, UNDER THEIR OWN METHOD, IS TO SHOW THAT 14 THERE'S THIS RIGID PAY STRUCTURE. 15 GETS A RAISE OR PROMOTION, EVERYBODY ELSE GETS A RAISE OR 16 PROMOTION. 17 18 IT'S SO RIGID IF ONE PERSON THE DATA, WHICH IS IN THIS BINDER AT TABS 4 AND 6, SHOW THAT THAT'S JUST NOT RIGHT. 19 THE COURT: 20 MR. MITTELSTAEDT: THERE IS, AT TAB 4 -- TAB 4, OKAY. -- THIS SHOWS THE DISTRIBUTION OF 21 ANNUAL CHANGES IN TOTAL COMPENSATION FOR THE TOP TEN GOOGLE 22 JOBS THAT THEY'VE PICKED, AND IT SHOWS THAT WITHIN ONE JOB 23 TYPE -- AND EACH OF THESE ARE THE TEN JOB TYPES AT THE 24 BOTTOM -- IT SHOWS THAT ANNUAL CHANGES FOR INDIVIDUALS VARY 25 EXTREMELY WIDELY. UNITED STATES COURT REPORTERS 232 71 1 THE FIRST YEAR, FOR EXAMPLE, A QUARTER -- 2 THE COURT: BUT CAN I ASK YOU, THERE ARE CERTAINLY A 3 LOT OF DOCUMENTS THAT WERE CREATED CONTEMPORANEOUSLY WHERE THE 4 DEFENDANTS SAY THAT THEY ARE CERTAINLY CONSIDERING INTERNAL 5 EQUITY. 6 MR. MITTELSTAEDT: INTERNAL EQUITY MEANING FAIRNESS, 7 AND FAIRNESS MEANING THESE COMPANIES -- AND EACH OF THEM HAD 8 DIFFERENT PAY SYSTEMS, BUT WHAT THEY HAD IN COMMON WAS THEY 9 PAID FOR PERFORMANCE. 10 AND THE PLAINTIFFS INTERPRET "INTERNAL EQUITY" TO MEAN 11 THAT IF ONE PERSON GETS A RAISE, EVERYBODY GETS A RAISE, AND 12 THAT'S JUST NOT WHAT HAPPENED, AND THESE DATA SHOW THIS. 13 DATA THAT WE'RE LOOKING AT HERE SHOWS THAT WITHIN ONE JOB TYPE, 14 THERE'S A WIDE DISTRIBUTION OF THE ANNUAL CHANGES IN 15 COMPENSATION. THE 16 SO A QUARTER -- JUST THE FIRST ONE, THE SOFTWARE ENGINEER 17 FOR GOOGLE THE FIRST YEAR, A QUARTER OF THE EMPLOYEES RECEIVED 18 A RAISE MORE THAN 80 PERCENT. 19 AND A QUARTER DROPPED. 20 THAT'S THE TOP OF THE PINK. THE -- 21 THE COURT: A QUARTER WERE BELOW THAT. AND I GUESS I DON'T AGREE WITH YOU THAT 22 THEIR POSITION REQUIRES RIGID LOCKSTEP, AND THEN IT REQUIRES 23 THE ABSOLUTE SCENARIO THAT YOU JUST DESCRIBED, THAT IF ONE 24 PERSON GETS A RAISE, EVERYONE GETS ONE. 25 IF WE'RE SAYING THESE ARE GENERAL TRENDS AND GENERALLY UNITED STATES COURT REPORTERS 233 72 1 THERE COULD BE INDIVIDUAL DEVIATIONS, BUT GENERALLY THAT THERE 2 IS SOME ATTENTION PAID BY THE DEFENDANTS TO OVERALL PAY 3 STRUCTURE -- 4 MR. MITTELSTAEDT: 5 THE COURT: WELL -- -- THAT, YOU KNOW, OVERALL -- THERE 6 COULD BE AN INDIVIDUAL DEVIATION, BUT THAT OVERALL THESE TRENDS 7 ARE TRUE. 8 9 MR. MITTELSTAEDT: THE QUESTION IS, DO YOU HAVE TO -- TO DETERMINE IF AN EMPLOYEE WOULD HAVE GOT A RAISE, DO 10 YOU HAVE TO GO EMPLOYEE BY EMPLOYEE? 11 CIRCUMSTANCE? 12 13 14 CIRCUMSTANCE BY DEPARTMENT BY DEPARTMENT? OR IS THERE SOME WAY TO SAY, WITH A WAVE OF A HAND, EVERYBODY WOULD HAVE GOT A RAISE? AND WHAT LEAMER TRIES TO DO, YOUR HONOR, IS HE DOES TWO 15 STEPS. 16 ACROSS THE BOARD FOR ALL OF THE DEFENDANTS. 17 HIS FIRST STEP IS TO ESTIMATE AN AVERAGE OVERCHARGE AND SO WHEN YOUR HONOR ASKED THE QUESTION, YOU KNOW, DO 18 FIGURES 20 AND 22 SHOW THAT EACH EMPLOYEE WAS UNDERPAID, THE 19 ANSWER WAS NO. 20 AND IT'S WORSE THAN THAT, YOUR HONOR, BECAUSE WHAT THEY'VE 21 DONE IS INSTEAD OF GOING DEFENDANT BY DEFENDANT, EVEN TO 22 ESTIMATE AN OVER -- AN AVERAGE, THEY LUMP ALL THE DEFENDANTS 23 TOGETHER, AND THE BEST WAY I CAN EXPLAIN THIS IS FIGURE 19, 24 WHICH IS -- WHICH IS ON, IN THE BINDER I'VE HANDED THE COURT, 25 PAGE 7. UNITED STATES COURT REPORTERS 234 73 1 THE COURT: 2 MR. GLACKIN: 3 MR. MITTELSTAEDT: 4 5 UM-HUM. TAB 7? WELL, IT'S TAB 6, PAGE 7. I'M SORRY. AND WHAT HE'S DONE HERE, IT'S CALLED AVERAGE PERCENT 6 CHANGE IN TOTAL COMPENSATION, AND YOU SEE ON THE RIGHT-HAND 7 SIDE HE SAYS "ESTIMATED UNDERPAYMENT," AND THEN THIS LOOKS REAL 8 FANCY BECAUSE HE'S GOT THE NUMBER OF EMPLOYEES AND THEN THE 9 MEAN, THE MEDIAN AND SO FORTH, AND THEN HE'S GOT INITIAL AND 10 CUMULATIVE. 11 WHAT HE'S DONE HERE IS TAKE THE ANNUAL COMPENSATION FOR 12 EACH INDIVIDUAL, AND HE KNOWS WHAT COMPANY THEY'RE WITH, AND 13 INSTEAD OF ADDING IT UP EITHER BY INDIVIDUAL TO SHOW WHO WAS UP 14 OR WHO WAS DOWN DURING THE ALLEGED CONSPIRACY PERIOD, INSTEAD 15 OF DOING IT BY INDIVIDUAL, INSTEAD OF DOING IT BY COMPANY, HE 16 DID IT BY ALL THE DEFENDANTS. 17 AND SO WHEN HE HAD -- WHAT HE DID HERE WAS TAKE 2004, YOUR 18 HONOR, THE LINE, HE SHOWS, IN THE MEAN, THAT AVERAGE 19 COMPENSATION, TOTAL COMPENSATION FOR EVERYBODY WENT UP 10.3 20 PERCENT. 21 22 23 24 25 AND THEN HE TAKES 2011 AND IT GOES UP 9.7 PERCENT, YEAR TO YEAR. HE TAKES THE AVERAGE OF THOSE TWO TO GET A BASE LINE, SO THAT'S 10. AND THEN HE LOOKS AT THE NEXT YEAR, 2005, THE FIRST YEAR UNITED STATES COURT REPORTERS 235 74 1 OF THE ALLEGED VIOLATION PERIOD, AND COMPENSATION ONLY WENT UP 2 .5 PERCENT, SO HE SAYS THAT THAT MEANS THE ESTIMATED 3 UNDERPAYMENT, AS A RESULT OF THESE AGREEMENTS, WAS 9.5 -- A 4 NEGATIVE 9.5 OVER ON THE RIGHT. 5 THE COURT: 6 MR. MITTELSTAEDT: 7 10 AND THEN ON THE NEXT PAGE OF HIS REPORT HE SAYS, "WELL, THIS IS JUST SUGGESTIVE BECAUSE IT'S NOT BROKEN OUT BY DEFENDANTS." 11 12 AND THEN HE DOES THAT FOR THE REST OF THE YEARS. 8 9 UM-HUM. BUT THE QUESTION IS, WHY DIDN'T HE BREAK IT OUT BY DEFENDANTS? 13 AND THE ANSWER IS ON THE NEXT TAB, PAGE 8. ON THE 14 RIGHT-HAND SIDE IS LEAMER'S NUMBERS, AND SO YOU'LL SEE FOR 2005 15 THE .5 FROM THE PREVIOUS PAGE. 16 BUT WHEN, INSTEAD OF ADDING IT UP FOR ALL DEFENDANTS 17 TOGETHER, WHEN YOU JUST ADD UP ALL THE INDIVIDUALS IN A 18 COMPANY, YOU SEE THAT ADOBE WENT UP 9.8 PERCENT IN 2008, AND 19 APPLE WENT UP 10.6. 20 UP. 21 TWO COMPANIES WENT DOWN, AND THE REST WENT AND IF YOU COMPARE THAT, AND ACTUALLY I'VE DONE THE -- 22 I'VE BROKEN THIS OUT ON THE NEXT PAGE, PAGE 9. 23 HIS SAME PROCEDURE AND YOU DO A BASELINE FOR ADOBE, WHAT YOU 24 GET IS YOU TAKE THE 1.5 FOR 2004 -- THIS IS AT PAGE 9 -- YOU 25 TAKE THE 1.5 YEAR TO YEAR INCREASE FOR 2004, THE 2011 YEAR TO UNITED STATES COURT REPORTERS IF YOU FOLLOW 236 75 1 YEAR INCREASE OF 11.1, AVERAGE THOSE, AND YOU COME UP WITH A 2 6.3 PERCENT BASELINE. 3 IT FOR ALL OF THE DEFENDANTS TOGETHER. THIS IS THE APPROACH LEAMER TOOK TO DO 4 AND THEN YOU COMPARE THAT 6.3 PERCENT BASELINE WITH THE 5 ACTUAL IN 2005 OF 9.8, AND THAT GIVES YOU AN OVERPAYMENT AS A 6 RESULT OF THESE ALLEGED AGREEMENTS OF 3.4 PERCENT, WHICH IS ON 7 THE BOTTOM PART OF THE PAGE, ADOBE 2005. 8 9 YOU DO THE SAME THING FOR APPLE: YOU CONSTRUCT APPLE'S BASELINE, COMPARE IT TO 2005, YOU GET 4.2 PERCENT. 10 YOU GET NEGATIVES FOR GOOGLE AND INTEL. 11 BUT YOU GET POSITIVES FOR INTUIT, LUCASFILM, AND PIXAR IS 12 13 A POSITIVE 35.6 PERCENT. AND YOU KNOW WHAT LEAMER DID? HE AVERAGED ALL THOSE 14 TOGETHER IN ORDER TO SUGGEST TO THE COURT THAT THERE WAS AN 15 ESTIMATED UNDERPAYMENT AS A RESULT OF THESE AGREEMENTS, AND 16 THAT'S WHERE HE GETS HIS NEGATIVE 9.5 PERCENT. 17 18 19 WHAT DRIVES THIS CHART IS INTEL BECAUSE INTEL HAS A LITTLE OVER HALF THE EMPLOYEES IN THE GROUP. AND SO HE IS MISLEADING THE COURT IN SAYING THAT THIS 20 EXERCISE SHOWS AN ESTIMATED UNDERPAYMENT FOR ALL OF THE 21 DEFENDANTS OF 9.5 PERCENT, WHEREAS IF IT HAD ANY VALUE, IF YOU 22 COULD REALLY MAKE A CAUSE AND EFFECT JUMP FROM YEAR TO YEAR 23 WITHOUT ADJUSTING FOR ANYTHING, IT WOULD SHOW THAT ONE, TWO, 24 THREE, FOUR, FIVE OF THE COMPANIES, UNDER THEIR OWN THEORY, 25 OVERPAID. UNITED STATES COURT REPORTERS 237 76 1 2 3 AND SO THERE'S NO BASIS TO SAY, FOR THEM TO SAY, WELL, THERE'S THIS AVERAGE, AVERAGE OVERPAYMENT. AND THEN WHEN YOU GET TO HIS REGRESSION, IT'S WORSE, YOUR 4 HONOR. THIS IS FIGURE 20, AND THIS IS AT PAGE 11, PAGE 11 OF 5 THIS SAME THING. 6 THE COURT: PAGE 11 IS A DEPOSITION TRANSCRIPT. 7 MR. MITTELSTAEDT: 8 THE COURT: 9 MR. MITTELSTAEDT: YES, YES. OKAY. AND WHAT HE SAYS IN THE 10 DEPOSITION IS WHEN YOU DO A REGRESSION, YOU NEED TO DO A 11 SENSITIVITY ANALYSIS. 12 CONCLUSIONS ARE TO A CHOICE OF VARIABLES. YOU EXPLORE HOW SENSITIVE THE 13 AND THEN HE SAYS, "I'VE DONE SOME ALTERNATE EQUATIONS." 14 AND THEN ON THE NEXT PAGE, DOWN AT THE BOTTOM, "BEFORE YOU 15 RELY ON IT," A REGRESSION, "YOU NEED TO KNOW IF IT'S SENSITIVE 16 BEFORE RELYING ON IT? 17 "THAT'S CORRECT." 18 OKAY. 19 AND THEN THE NEXT PAGE, PAGE 13, WE WERE ASKING HIM, "WELL, WHAT SENSITIVITY ANALYSIS DID YOU DO?" 20 BECAUSE AS COUNSEL EXPLAINED, ON THIS REGRESSION, FIGURE 21 20, HE HAS A SINGLE CONDUCT VARIABLE FOR ALL OF THE DEFENDANTS 22 WHICH ASSUMES THAT THE EFFECT OF THE PIXAR/LUCASFILM AGREEMENT 23 WAS THE SAME ON PIXAR AS IT WAS ON ADOBE THAT DIDN'T HAVE 24 ANYTHING TO DO WITH IT, AND THEN HE ADJUSTS ONLY FOR THE AGE 25 AND THE HIRING RATE OF THE COMPANY. UNITED STATES COURT REPORTERS 238 77 1 2 3 SO THAT DOESN'T GIVE YOU ANY INDIVIDUAL COMPANY INFORMATION WORTH ANYTHING. BUT HERE'S WHAT HE SAYS, YOUR HONOR. 4 THE COURT: YOU SAY THESE ARE FROM THE MURPHY 5 REPORT, YOUR PAGES 9 AND 10. 6 MR. MITTELSTAEDT: 7 THE COURT: 8 MR. GLACKIN: 9 MURPHY REPORT, FIGURE 19. IT'S EXHIBIT 19 -- EXCUSE ME. IT'S EXHIBIT 19 TO DR. MURPHY'S REPORT. THE COURT: 11 MR. GLACKIN: 13 GIVE ME THE PAGE NUMBER OF THIS. IT'S -- IT'S DONE BY EXHIBIT. 10 12 "WELL, I" -- OH. IT'S NOT DR. LEAMER'S REPORT AT THAT POINT. MR. MITTELSTAEDT: YEAH, IT'S DR. MURPHY'S REPORT ON 14 THE LEFT-HAND SIDE WITH THE POOLING, THE AGGREGATE FROM MURPHY, 15 I MEAN FROM LEAMER. 16 17 18 BUT, YOUR HONOR, THIS REALLY GOES TO THE HEART OF WHAT'S GOING ON HERE AND HOW MISLEADING IT IS. AT PAGE 13, THIS IS LEAMER'S DEPOSITION, AND AT LINE 16 19 HE'S ASKED -- AND NOW WE'RE TALKING ABOUT WHAT SENSITIVITY 20 ANALYSES HE RAN TO SEE IF HIS, IF HIS FIGURE 20, HIS 21 REGRESSION, WAS RELIABLE. 22 AND HE SAID, "I RECALL ONE WHICH HAS TO DO WITH THE 23 DISAGGREGATION WITH DATA BY A DEFENDANT. 24 THAT HAS ALL THE DEFENDANTS. 25 "MR. GLACKIN: WAIT, WAIT, WAIT. SO I HAVE A MODEL I'M GOING TO INSTRUCT UNITED STATES COURT REPORTERS 239 78 1 2 3 4 5 6 YOU NOT TO ANSWER FURTHER." AND THEN THE QUESTION BY MR. PICKETT: "WHAT WERE THE RESULTS OF THE DISAGGREGATION?" THIS IS WHEN HE RAN IT INDIVIDUALLY BY DEFENDANT, SEPARATE CONDUCT VARIABLES. AND MR. GLACKIN SAYS, "IF YOU ANSWER SOMETHING OTHER THAN 7 'I DON'T KNOW' OR 'I DON'T REMEMBER,' I'M GOING TO INSTRUCT YOU 8 NOT TO ANSWER." 9 10 AND THE WITNESS, ALMOST PREDICTABLY, SAID, "I DON'T REMEMBER THE DETAILS." 11 "DID YOU RETAIN THE WORK?" 12 "WELL, IT'S PROBABLY ON MY HARD DRIVE SOMEPLACE." 13 AND THEN HE SAYS AT LINE 12, "WELL, IT'S NOT HARD TO DO. 14 YOUR EXPERTS WILL BE ABLE TO DO IT WITH THE PRESS OF A BUTTON." 15 AND SO THAT'S WHAT OUR EXPERT DID. 16 BEFORE I GO ON TO THAT, ON THE FOLLOWING EXCERPT HERE, 17 HE'S ASKED, "IF YOUR CONDUCT REGRESSIONS COME UP WITH A -- OR 18 CAME UP WITH A POSITIVE CONDUCT COEFFICIENT, MEANING THAT THE 19 ALLEGED AGREEMENT HAD A POSITIVE IMPACT ON COMPENSATION, WHAT 20 WOULD THAT TELL YOU ABOUT THE MODEL? 21 "WELL, IT WOULD RAISE CONCERNS ABOUT THE CONCEPTUAL 22 FRAMEWORK AND THE APPROPRIATENESS OF THE MODEL. 23 QUESTION ABOUT THAT." 24 25 THERE'S NO AND THEN -THE COURT: ALL RIGHT. LET ME ASK YOU A QUESTION. UNITED STATES COURT REPORTERS 240 79 1 IF THE PLAINTIFFS WERE TO -- WHAT IS YOUR POSITION ON 2 PREDOMINANCE AS TO JUST THE TECHNICAL CLASS? 3 4 MR. MITTELSTAEDT: THERE WAS ANY JOB CATEGORY -- 5 THE COURT: 6 MR. MITTELSTAEDT: 7 8 9 10 11 THERE IS NO BASIS TO THINK THAT UM-HUM. -- THAT -- WHERE THERE WAS ANY BROAD IMPACT OF THESE AGREEMENTS. WHAT WE HAVE SHOWN -- AND, YOUR HONOR, IF YOU -- I MEAN, GOING BACK TO TAB 5, THIS SHOWS -- YOU TALKED WITH COUNSEL ABOUT THE CONSTANT ATTRIBUTE COMPENSATION. THIS TAKES THE TOP 25 JOBS BY COMPANY AND IT SHOWS THE 12 ANNUAL CHANGES, AND WHAT THIS SHOWS IS THAT SOME JOBS WENT UP 13 IN TOTAL COMP, SOME JOBS WENT DOWN TO A NEGATIVE. 14 AND SO EXHIBIT 18, WHICH IS IN TAB 5, FOR ADOBE, THAT 15 FIRST YEAR, ONE JOB -- AND THESE ARE 25 DIFFERENT JOBS -- ONE 16 JOB COMPENSATION INCREASED 11 PERCENT. 17 BY 14 PERCENT. 18 19 GOOGLE, 2006, EVEN A LARGER SWING. ANOTHER JOB DECREASED 53 PERCENT TO A NEGATIVE 70 PERCENT. 20 THIS SHOWS THAT IF THE PLAINTIFFS WERE RIGHT, THERE WOULD 21 BE CORRELATION AMONG THESE JOB GROUPS, CORRELATION BOTH OF THE 22 EMPLOYEES WITHIN THE JOB GROUP AND THE AVERAGE. 23 THIS TAKES IT BY INDIVIDUAL WITHIN THAT -- OR NO. THIS 24 TAKES IT BY JOB TITLES AND IT SHOWS THAT THEY'RE NOT CORRELATED 25 WHEN THEY MOVE. UNITED STATES COURT REPORTERS 241 80 1 AND, YOUR HONOR, THE FIRST PART OF WHAT LEAMER DID WAS TO 2 TRY AND SHOW, IN THIS VERY MISLEADING WAY, AN AVERAGE 3 OVERCHARGE FOR EVERYBODY. 4 5 WE ASKED HIM, AT HIS DEPOSITION, AND HE SHOWED -- ON ONE OF THESE YOU'LL SEE 20 PERCENT UNDERCHARGE FOR LUCASFILM. 6 7 WE ASKED HIM, "HOW DOES IT MAKE ANY SENSE THAT A COMPANY COULD UNDERPAY BY 20 PERCENT AND STILL HIRE PEOPLE?" 8 9 10 11 AND HE PAUSED ALMOST A MINUTE AND HE SAID THAT HE WAS TIRED AND IN HIS -- HE COULD NOT CONSTRUCT A STORY TO JUSTIFY THAT. AND WHAT THAT TELLS ME IS THAT EVEN HE KNOWS THAT THE 12 RESULTS OF HIS REGRESSION DON'T MAKE SENSE, THEY DON'T COMPORT 13 WITH THE REAL WORLD, AND, WORSE, HE DIDN'T DO IT DEFENDANT BY 14 DEFENDANT. 15 AND WHEN, WHEN -- 16 THE COURT: OKAY. I'M GOING TO TAKE A BREAK NOW. 17 WE'VE BEEN GOING FOR MORE THAN TWO HOURS AND MS. SHORTRIDGE 18 NEEDS TO BREAK. OKAY? 19 THANK YOU ALL. 20 (RECESS FROM 3:36 P.M. UNTIL 3:57 P.M.) 21 22 THE COURT: OKAY. WELCOME BACK. PLEASE HAVE A SEAT. 23 ALL RIGHT. 24 WHAT -- WHAT DISCOVERY DISPUTES ARE STILL OUTSTANDING? 25 LET'S MOVE ON TO THE CMC. I WAS GOING TO MAKE A SUGGESTION WITH THE E-MAILS BETWEEN INTUIT UNITED STATES COURT REPORTERS 242 81 1 BOARD CHAIRMAN GLENN CAMPBELL AND GOOGLE'S IN-HOUSE LAWYER, I 2 WAS GOING TO SUGGEST THAT YOU SUBMIT THEM TO ME IN CAMERA. 3 I'LL BE HAPPY TO DECIDE IT FOR YOU AND I WILL SEE IF THERE 4 REALLY IS SOME KIND OF ATTORNEY-CLIENT PRIVILEGE AGREEMENT 5 BETWEEN MR. CAMPBELL AND GOOGLE SUCH THAT IT WOULD ACTUALLY BE 6 PRIVILEGED. 7 8 9 10 11 BUT IF IT'S JUST MORE TALKING ABOUT THESE AGREEMENTS, I DON'T REALLY THINK THAT'S PRIVILEGED. SO WHY DON'T YOU SUBMIT THEM TO ME IN CAMERA? DO YOU WANT TO DO THAT BY NEXT WEDNESDAY? MR. RUBIN: SURE, YOUR HONOR. WE WOULD ALSO BE 12 SUBMITTING FACTUAL -- WITH THE COURT'S PERMISSION, WE WOULD 13 ALSO BE SUBMITTING FACTUAL DECLARATIONS ABOUT THE NATURE OF THE 14 RELATIONSHIP. 15 THE NATURE OF THE RELATIONSHIP AND WE WOULD LIKE TO SUBMIT 16 THOSE IN CAMERA AS WELL. I THINK ONE OF THE ISSUES THAT WAS RAISED WAS 17 MS. DERMODY: 18 PLAINTIFF -- EXCUSE ME. 19 20 21 22 MR. RUBIN: AND, YOUR HONOR, ON BEHALF OF I'M SORRY. IF -- YOUR HONOR, IF YOU CAN INDULGE US, IF WE CAN SUBMIT IT BY FRIDAY? THE COURT: LET ME HEAR, WHAT OTHER -- NONE OF THE 23 CEO'S HAVE BEEN DEPOSED, THE SENIOR VICE-PRESIDENT OF HUMAN 24 RESOURCES AT INTEL HAS NOT BEEN DEPOSED. 25 HASN'T BEEN DEPOSED? WHO ELSE? UNITED STATES COURT REPORTERS WHO ELSE 243 82 1 MS. DERMODY: WELL, YOUR HONOR, JUST FOR THE RECORD, 2 PLAINTIFFS REQUESTED MOST OF THESE INDIVIDUALS BACK IN 3 SEPTEMBER AND IT'S BEEN QUITE A LONG PROCESS OF NEGOTIATION, 4 WITH SOME DEFENDANTS ACTUALLY ASKING THAT WE WAIT UNTIL AFTER 5 THE COURT'S ORDER ON CLASS CERTIFICATION. 6 THE COURT: NO, THAT'S NOT HAPPENING. 7 MS. DERMODY: WE HAVE NOT AGREED TO THAT AND WE HAVE 8 AGREED TO ACCOMMODATE SCHEDULES WHENEVER WE COULD, BUT WE'VE 9 INSISTED THAT DEPOSITIONS START. 10 11 I'LL GIVE YOU A LIST, YOUR HONOR, IF YOU'D LIKE OF WHAT'S ON CALENDAR. 12 THE COURT: OKAY. 13 MS. DERMODY: 14 THE COURT: 15 MS. DERMODY: 16 THE COURT: 17 MS. DERMODY: 18 THE COURT: 19 MS. DERMODY: FOR GOOGLE, SHONA BROWN, JANUARY 30TH. AND SHE'S AN H.R. PERSON? YES, YOUR HONOR. OKAY. THAT'S JANUARY 30TH? YES. OKAY. AND ERIC SCHMIDT HAD BEEN SCHEDULED 20 FOR FEBRUARY 21ST. I UNDERSTAND WE WERE TOLD BY DEFENSE 21 COUNSEL A FEW MOMENTS AGO THAT THAT DATE MAY NOT WORK FOR 22 MR. SCHMIDT. 23 POSSIBLE. WE WOULD LIKE TO HAVE ONE SCHEDULED AS SOON AS 24 MR. RUBIN: YOUR HONOR, WE HAD PROPOSED 25 FEBRUARY 20TH, THE DAY BEFORE. UNITED STATES COURT REPORTERS 244 83 1 MS. DERMODY: AND WE HAVE TO CHECK WITH MR. HEIMANN, 2 WHO WAS SCHEDULED TO TAKE THAT DEPOSITION, IF THAT WORKS FOR 3 HIS SCHEDULE. 4 THE COURT: WELL, LET'S -- I AM REALLY DISAPPOINTED 5 THAT ALL OF THIS DISCOVERY WAS NOT DONE BEFORE THE CLASS 6 CERTIFICATION HEARING. 7 SO LET'S SUBMIT RIGHT NOW, WHAT'S THE DATE FOR 8 ERIC SCHMIDT? NO ONE IS LEAVING UNTIL WE HAVE THESE DATES SET. 9 IF WE NEED TO BE HERE UNTIL MIDNIGHT, THAT'S WHAT HAPPENS. 10 MR. RUBIN: HE'S AVAILABLE FEBRUARY 20TH. 11 THE COURT: CAN YOU TAKE IT FEBRUARY 20TH? 12 MS. DERMODY: 13 THE COURT: 14 17 OKAY. YOU BETTER MAKE SOMEONE AVAILABLE. 15 16 SOMEONE WILL TAKE IT, YOUR HONOR, YES. MS. DERMODY: YES, YOUR HONOR. SO LUCASFILM RIGHT NOW, IF I HAVE THIS RIGHT, MICHELINE CHAU, C-H-A-U, AND IT'S FEBRUARY 20TH. 18 THE COURT: 19 MR. SAVERI: AND WHAT IS THAT PERSON'S JOB? SHE WAS, AT VARIOUS TIMES, THE CHIEF 20 OPERATING OFFICER, OR SOMEONE AT THAT LEVEL AT LUCASFILM. 21 TITLE DID CHANGE THROUGHOUT THE PERIOD OF TIME AFFECTED BY THE 22 AGREEMENT, BUT SHE WAS ONE OF THE MOST SENIOR PEOPLE AT 23 LUCASFILM. 24 MR. LUCAS HIMSELF. 25 HER IN FACT, I BELIEVE SHE REPORTED DIRECTLY TO THE COURT: OKAY. WHO ELSE? UNITED STATES COURT REPORTERS 245 84 1 MS. DERMODY: 2 THE COURT: 3 MS. DERMODY: 4 5 JAN VAN DER VORT, FEBRUARY 5TH. HAVE -- LUCAS HAS REFUSED TO GIVE US DATES. MR. PURCELL: HONOR. THAT'S ACTUALLY NOT ACCURATE, YOUR WE HAVEN'T REFUSED TO GIVE THEM DATES. 8 9 OKAY. AND WE HAVE REQUESTED MR. LUCAS FOR SOME TIME, BUT WE 6 7 MICHELLE MAUPIN, FEBRUARY 12TH. THE COURT: OKAY. GIVE ME A DATE. WE'RE SETTING THEM RIGHT NOW. 10 MR. PURCELL: 11 THE COURT: I CAN'T GIVE YOU A DATE TODAY. I'M TELLING YOU, I HAVE BEEN SO TOUGH ON 12 BOTH SIDES AT EVERY CMC ON DISCOVERY. I DON'T WANT THESE 13 GAMES, OKAY? 14 IN THESE AGREEMENTS HAVEN'T BEEN DEPOSED YET, I REALLY FEEL 15 LIKE YOU INTENTIONALLY WITHHELD THEIR DEPOSITIONS UNTIL AFTER 16 THE CLASS CERT HEARING, OKAY? SO THE FACT THAT THE PEOPLE WHO ARE MOST INVOLVED 17 MR. PURCELL: 18 THE COURT: YOUR HONOR -- I'M REALLY DISAPPOINTED BECAUSE THESE 19 ARE THE INDIVIDUALS, LIKE ERIC SCHMIDT IS ON ALL THE E-MAILS 20 THAT WERE IN THIS CMC STATEMENT FROM JANUARY 26TH OF 2012, A 21 YEAR AGO. 22 SO, YOU KNOW, I'M DISAPPOINTED. 23 MR. LUCAS'S DEPOSITION. 24 MR. PURCELL: GIVE ME A DATE FOR 25 I CANNOT GIVE YOU A DATE TODAY. DON'T KNOW WHEN HE'S AVAILABLE. I I JUST DON'T HAVE THAT UNITED STATES COURT REPORTERS 246 85 1 INFORMATION. 2 3 THE COURT: 6 SO HOW LONG HAS THIS LAWSUIT BEEN PENDING AND YOU'VE NEVER GOTTEN A DATE FOR HIM? 4 5 OKAY. MR. PURCELL: YOUR HONOR, MR. LUCAS'S DEPOSITION WAS FIRST REQUESTED IN MID-DECEMBER, NOT IN SEPTEMBER. THERE WAS ONE LUCASFILM WITNESS WHOSE DEPOSITION WAS 7 REQUESTED PRIOR TO THAT. 8 EARLY NOVEMBER. 9 10 THE COURT: SHE WAS DEPOSED IN LATE OCTOBER OR GIVE ME A DATE BY WHICH YOU'RE GOING TO PROVIDE A DATE. 11 MR. PURCELL: GIVE YOU A DATE BY WHICH WE'RE GOING 12 TO PROVIDE A DATE? 13 FROM FRIDAY, NEXT FRIDAY? 14 15 HOW ABOUT A WEEK FROM TOMORROW, OR A WEEK THE COURT: ALL RIGHT. I'LL GIVE YOU A WEEK, JANUARY 23RD. WHAT ELSE? 16 MS. DERMODY: 17 THE COURT: 18 MS. DERMODY: 19 THE COURT: 20 MS. DERMODY: 21 FOR INTEL, YOUR HONOR, PAUL OTELLINI. ALL RIGHT. WHEN IS THAT? JANUARY 29TH. OKAY. AND PATRICIA MURRAY, FEBRUARY 14. AND, EXCUSE ME, YOUR HONOR. I CAN ALSO PASS YOU UP THIS 22 LIST IF IT WOULD BE HELPFUL SO YOU DON'T HAVE TO TRY TO GET THE 23 SPELLINGS OF EVERY NAME. 24 25 THE COURT: OKAY. HAVE THE DEFENDANTS SEEN THAT LIST? UNITED STATES COURT REPORTERS 247 86 1 MR. SAVERI: 2 MS. DERMODY: 3 4 I DON'T THINK THEY'VE SEEN THE LIST. I CAN READ IT ALOUD IF THAT WOULD BE HELPFUL AND I CAN PASS IT UP IF IT WOULD BE ACCEPTABLE. MR. SAVERI: THESE REFLECT DATES THAT WE HAVE HAD 5 EXTENSIVE COMMUNICATION WITH THE DEFENDANTS, SO I THINK WITH 6 RESPECT TO EACH DEFENDANT WHOSE EXECUTIVE IS ON THE LIST, THEY 7 KNOW ABOUT IT. 8 9 10 11 12 BUT WE CAN SHARE IT, READ IT OUT, WHATEVER MAKES SENSE. MS. DERMODY: YES. I JUST WANT TO SAVE THE COURT TIME, YOUR HONOR, BUT I'M HAPPY TO KEEP READING THE LIST. THE COURT: WELL, LET ME SEE THE LIST. CAN YOU JUST SHOW IT TO THE DEFENDANTS? 13 MS. DERMODY: 14 MS. HENN: SURE (HANDING). I WOULD JUST POINT OUT THAT THE LIST HAS 15 NOTES AT THE BOTTOM AND I'M NOT SURE THEY'RE ACCURATE, FOR 16 EXAMPLE, THAT ALL OF THESE WERE REQUESTED IN SEPTEMBER. 17 AS WE JUST HEARD, SOME OF THEM WERE -- AT LEAST MR. LUCAS 18 WAS FIRST REQUESTED IN DECEMBER. 19 THAT THE COURT'S AWARE THAT THAT'S NOT ACCURATE. 20 21 MR. KIERNAN: SO I JUST WANT TO MAKE SURE DAVID KIERNAN. YOUR HONOR, THERE ARE A FEW DEFENDANTS' WITNESSES THAT 22 WERE MOVED BY PLAINTIFFS, NOT BECAUSE OF ANY ACTION -- FOR 23 EXAMPLE, BRUCE CHIZEN WAS SCHEDULED FOR DEPOSITION IN DECEMBER 24 AND WE ACCOMMODATED MR. SAVERI'S SCHEDULE AND WE WENT TO 25 JANUARY, AND THEN IT HAD TO GET MOVED AGAIN UNTIL FEBRUARY. UNITED STATES COURT REPORTERS 248 87 1 THE COURT: 2 MR. KIERNAN: 3 THE COURT: 4 MR. KIERNAN: 5 WHY DID IT HAVE TO MOVE UNTIL FEBRUARY? THERE WAS ANOTHER SCHEDULING CONFLICT. ON WHOSE PART? ACTUALLY, I THINK IT MIGHT HAVE BEEN YOURS AS WELL. 6 MR. SAVERI: I BELIEVE ONE OF THEM WAS -- 7 MR. KIERNAN: BUT WE'VE BEEN WORKING TOGETHER. 8 MEAN, THE POINT IS WE'VE BEEN WORKING TOGETHER ABOUT THE 9 SCHEDULING ISSUES. I 10 11 12 13 14 15 16 17 IT HASN'T BEEN QUITE AS CHARACTERIZED -- AS PLAINTIFFS' COUNSEL CHARACTERIZED IT. THE COURT: WHY DON'T YOU JUST LIST THE NAMES AND THE DATES, PLEASE? MS. DERMODY: SURE, YOUR HONOR, YES. FOR ADOBE, MR. BRUCE CHIZEN. THE COURT: SO FOR INTEL, IT'S ONLY MS. MURRAY AND MR. OTELLINI? MS. DERMODY: YES, IN TERMS OF DEPOSITIONS THAT HAVE 18 BEEN SET, YOUR HONOR. THERE ARE MORE THAT WERE REQUESTED. 19 MR. HINMAN: YOUR HONOR, FRANK HINMAN FOR INTEL. 20 BEFORE WE LEAVE MR. OTELLINI, THERE'S JUST A LITTLE BIT OF 21 A DETAIL THERE ACTUALLY HAVING TO DO WITH THIS MOTION THAT'S 22 BEEN FILED WITH RESPECT TO THESE GOOGLE -- THE GOOGLE DOCUMENTS 23 AND THE PRIVILEGE ISSUE BECAUSE MR. OTELLINI, AS I UNDERSTAND 24 IT, IS ALSO ON A NUMBER OF THOSE DOCUMENTS. 25 SO I THINK WE HAVE AN UNDERSTANDING WITH MR. SAVERI THAT UNITED STATES COURT REPORTERS 249 88 1 THERE MAY BE A CONTINGENCY IN WHICH MR. OTELLINI'S DEPOSITION 2 MIGHT HAVE TO MOVE, BUT I DON'T THINK WE HAVE ANY -- I THINK 3 WE'RE BOTH ON THE SAME PAGE AS TO HOW THAT'S GOING TO WORK, IF 4 IT HAS TO WORK. 5 BUT PLEASE GO AHEAD. 6 THE COURT: OKAY. LET ME -- I'M SORRY. LET ME 7 UNDERSTAND SOMETHING, WHICH I DIDN'T UNDERSTAND WITH THE 8 SEALING REQUEST, EITHER. 9 YOU HAVE THIRD PARTY COMPETITORS, THEY HAVE AGREED TO 10 ENTER INTO THESE AGREEMENTS, AND NO ONE HAS EVER ALLEGED THAT 11 THERE'S A NONDISCLOSURE AGREEMENT. 12 SO WHAT IS THE BASIS FOR CONFIDENTIALITY AND FOR SEALING 13 OF DOCUMENTS OF THIRD PARTY COMPETITORS? OKAY? UNLESS YOU'RE 14 TELLING ME THAT ALL OF THESE CEO'S ARE ACTUALLY CONSULTANTS AND 15 ADVISORS FOR ALL THEIR COMPETITORS, WHICH WOULD REALLY SHOCK 16 ME, WHAT IS THE BASIS FOR AN EXPECTATION OF CONFIDENTIALITY AND 17 OF SEALING? 18 IT HAPPENED TIME AND AGAIN ON THE SEALING REQUEST. YOU 19 HAVE THIRD PARTY COMPETITORS WHO HAVE CHOSEN TO TALK TO EACH 20 OTHER AND SUDDENLY THAT'S -- HOW IS THAT CONFIDENTIAL? 21 MR. RUBIN: MR. OTELLINI IS ON THE BOARD OF 22 DIRECTORS FOR GOOGLE. HE IS A MEMBER OF THE BOARD OF 23 DIRECTORS. 24 CONFIDENTIAL COMMUNICATIONS WITH YOUR BOARD ON MATTERS RELATING 25 TO RUNNING THE CORPORATION. AS FAR AS I KNOW, YOU'RE ENTITLED TO HAVE UNITED STATES COURT REPORTERS 250 89 1 THE COURT: TELL ME ABOUT THIS EDWARD COLLIGAN FROM 2 PALM AND STEVE JOBS OF APPLE. 3 EXPECTATION OF CONFIDENTIALITY WHEN THEY'RE TALKING TO EACH 4 OTHER? 5 WHAT IS THE BASIS FOR ANY DON'T TELL ME THAT THEY'RE ACTUALLY CONSULTANTS AND 6 ACTUALLY WORK FOR THEIR COMPETITORS. 7 I WOULD FIND THAT REALLY HARD TO BELIEVE. 8 THOSE KINDS OF THINGS JUST KEEP POPPING UP, AND I'M 9 TELLING YOU, THAT'S NOT CONFIDENTIAL AND IT'S NOT GOING TO BE 10 SEALED. 11 OF NDA OR SOME BASIS FOR THAT TO BE CONFIDENTIAL, I'M NOT GOING 12 TO SEAL IT. 13 14 15 16 UNLESS YOU TELL ME THAT THERE WAS ACTUALLY SOME KIND MR. TUBACH: YOUR HONOR, MICHAEL TUBACH FOR APPLE. I DON'T BELIEVE APPLE MOVED TO HAVE THAT SEALED AS CONFIDENTIAL. I BELIEVE PALM DID. 17 THE COURT: ANYWAY, OKAY. 18 MS. DERMODY: SO -- YOUR HONOR, IF I MIGHT CLARIFY FOR THE 19 COURT, WE BELIEVE THAT PALM, AS A THIRD PARTY, TRIED TO AVAIL 20 ITSELF UNDER THE PROTECTIVE ORDER IN THE CASE AND THE COURT 21 DISAGREED WITH PALM'S DESIGNATION. 22 23 SO I THINK ALL THE PARTIES ACCEPT THAT. DEFENDANTS. I WON'T SPEAK FOR PLAINTIFFS EXCEPT THAT. 24 MR. SAVERI: 25 THE COURT: RIGHT. OKAY. SO YOU'RE SAYING WHO ELSE IS ON UNITED STATES COURT REPORTERS 251 90 1 THESE PRIVILEGED E-MAILS BETWEEN -- WHO IS THE GOOGLE IN-HOUSE 2 LAWYER? 3 WHO IS ON THESE PRIVILEGED E-MAILS? MR. RUBIN: THE GOOGLE -- THERE ARE A NUMBER OF 4 GOOGLE IN-HOUSE, BUT ONE OF THEM BEING KENT WALKER, THE GENERAL 5 COUNSEL. 6 ASSISTING THE BOARD. 7 AT OTHER TIMES IT'S LAWYERS WHO WERE INVOLVED IN SO MR. OTELLINI, AS I SAID, IS ON COMPENSATION COMMITTEE 8 DOCUMENTS WHERE THERE'S PRIVILEGED ADVICE BEING GIVEN TO THE 9 BOARD OF DIRECTORS AND MR. -- IN MR. CAMPBELL'S ROLE AS A 10 SENIOR ADVISER TO THE COMPANY, AND AS I SAID, WE'LL PROVIDE YOU 11 MORE DETAIL ABOUT THE LEGAL STATUS OF THAT RELATIONSHIP -- 12 13 THE COURT: ALL RIGHT. TELL ME HOW MANY PRIVILEGED COMMUNICATIONS ARE THE SUBJECT OF THE MOTION TO COMPEL. 14 MR. RUBIN: WELL, YOUR HONOR, WE'RE ACTUALLY TRYING 15 TO GET THAT BREAKDOWN. 16 PLAINTIFFS LISTED ABOUT 160, BUT I THINK WE'RE -- RIGHT NOW, AS 17 WE SPEAK, WE'RE TRYING TO DE-DUPE THOSE BECAUSE I THINK THERE 18 ARE ACTUALLY SIGNIFICANTLY FEWER E-MAILS AT ISSUE. 19 I THINK, THE NUMBER THAT WERE IDENTIFIED. 20 I BELIEVE THAT THE -- I BELIEVE MS. DERMODY: YES, YOUR HONOR. BUT THAT'S, IT PROBABLY HASN'T 21 COME ACROSS THE COURT'S DESK YET, BUT WE FILED A MOTION TO 22 COMPEL YESTERDAY ON THESE DOCUMENTS WHICH DESCRIBES 166 E-MAILS 23 AND SETS FORTH -- 24 25 THE COURT: THAT. I'M GOING TO LET JUDGE GREWAL HANDLE I MEAN, IT WAS FILED BEFORE HIM. UNITED STATES COURT REPORTERS 252 91 1 I THOUGHT THERE WAS A DISCRETE AMOUNT. I MEAN, I'M 2 LOOKING AT THE DECEMBER 5TH JOINT CASE MANAGEMENT STATEMENT AND 3 IT LOOKED LIKE IT WAS A VERY DISCRETE NUMBER. 4 MR. RUBIN: AT THAT TIME, YOUR HONOR, I THINK TWO 5 HAD BEEN IDENTIFIED, AND THEN AS PART OF OUR SUPPLEMENTAL 6 PRODUCTION, WE PRODUCED SUPPLEMENTAL LOGS THAT INCLUDED 7 ADDITIONAL E-MAILS THAT INCLUDED MR. CAMPBELL. 8 9 THE COURT: THAT'S RIGHT. THERE WERE ONLY TWO E-MAILS THAT WERE THE SUBJECT OF THIS ANTICIPATED MOTION TO 10 COMPEL AS OF DECEMBER. 11 E-MAILS? 12 MS. DERMODY: BUT YOU'RE SAYING THAT'S GROWN TO 166 YES, BECAUSE THEY PRODUCED PRIVILEGE 13 LOGS SINCE THAT TIME, INCLUDING THOUSANDS OF E-MAILS ON 14 PRIVILEGE LOGS OVER THE HOLIDAYS. 15 SO WE JUST IDENTIFIED THEM AND MOVED TO COMPEL AS QUICKLY 16 AS POSSIBLE. 17 FOR A DEPONENT WHERE WE THOUGHT THESE E-MAILS WOULD BE 18 NECESSARY TO BE PRODUCED BECAUSE THEY WERE ON THAT DEPONENT'S 19 PRIVILEGE LOG AND WE HAD A DISCUSSION WITH DEFENDANTS ABOUT 20 GOING FORWARD WITH THE DEPO AND KEEPING IT OPEN. 21 22 23 24 25 WE HAD A DEPOSITION ON CALENDAR FOR LAST THURSDAY THEY DISAGREED TO KEEP IT OPEN AND SAID THEY WOULD CONTINUE IT SUBJECT TO OUR MOTION BEING HEARD. SO WE FILED IT ON AN EXPEDITED TIME TABLE AND HOPEFULLY IT WILL BE HEARD SOON. THE CRUX OF THE ISSUE REALLY IS MORE THAN JUST THE NATURE UNITED STATES COURT REPORTERS 253 92 1 OF THE RELATIONSHIPS, BUT ALSO THE MEANS OF COMMUNICATION. 2 SO WHATEVER THE RELATIONSHIP WAS TO GOOGLE, WHETHER A 3 PERSON WAS ON THE BOARD OF DIRECTORS OR SOMETHING ELSE, 4 GOOGLE'S DECISION TO SEND THOSE E-MAILS WITHOUT ANY EXPECTATION 5 OF PRIVACY TO THEIR COMPETITOR'S E-MAIL ADDRESSES, SO IN 6 MR. CAMPBELL'S CASE, THEY WERE SENDING WHATEVER IT WAS, 7 SENSITIVE, WHAT THEY WOULD CALL PRIVILEGED INFORMATION TO 8 INTUIT.COM WHERE INTUIT ITSELF HAS A PERSONNEL POLICY TELLING 9 ALL EMPLOYEES THAT ANY OF THE COMPUTER SYSTEMS BELONG TO INTUIT 10 11 12 AND INTUIT CAN INVESTIGATE THEM AT ANY TIME. THERE SHOULD HAVE BEEN NO EXPECTATION OF PRIVACY. IT WAS A WAIVER OF THE PRIVILEGE IN OUR VIEW. 13 SO WHATEVER YOU FIND THE RELATIONSHIP TO BE SEEMS TO ME TO 14 BE ALMOST BESIDE THE POINT GIVEN HOW THEY FAILED TO PROTECT THE 15 PRIVILEGE AND SENT IT OFF TO THEIR COMPETITOR'S E-MAIL ADDRESS. 16 MR. RUBIN: WELL, OBVIOUSLY, YOUR HONOR, THESE ARE 17 ALLEGATIONS IN THEIR MOTION, BUT THERE'S A SIGNIFICANT FACTUAL 18 SHOWING THAT WE'RE PREPARED TO MAKE, BOTH ON THE NATURE OF THE 19 RELATIONSHIP BEING CONSISTENT WITH PRIVILEGE, AND THE FACT THAT 20 MR. CAMPBELL, IN THE STATUS THAT HE HAD, TREATED THEM WITH 21 CONFIDENTIALITY AND UNDERSTOOD HE HAD A DUTY TO DO SO AND THAT 22 NOBODY EVER REVIEWED OR SAW OR TOOK PART IN PART OF THE REVIEW 23 OF THESE E-MAILS. 24 25 THE COURT: SO WHO ELSE IS -- I'M SORRY TO INTERRUPT YOU -- WHO ELSE IS ON THESE 166 E-MAILS THAT STILL NEEDS TO BE UNITED STATES COURT REPORTERS 254 93 1 2 DEPOSED? ARE THERE OTHERS OTHER THAN MR. OTELLINI? MR. RUBIN: WELL, PERHAPS SHONA BROWN MAY WELL BE ON 3 THEM, AND THOSE ARE THE ONLY OTHER TWO GOOGLE INDIVIDUALS WHOSE 4 DEPOSITIONS HAVE BEEN REQUESTED. 5 MR. SAVERI: EXCUSE ME. MR. CAMPBELL IS ONE OF THE 6 PRIME ACTORS FROM OUR PERSPECTIVE IN THE CONSPIRACY. 7 HIS NAME IS ALL OVER THESE DOCUMENTS AND RIGHT NOW I THINK WE 8 HAVE A DATE FOR MR. CAMPBELL'S DEPOSITION ON FEBRUARY 5. 9 10 MS. DERMODY: MR. RUBIN: HE IS -- YES. I KNOW MS. DERMODY MADE THE REFERENCE TO 11 THE FACT THAT WE GOT THEM TO THEM OVER THE HOLIDAYS. 12 ACTUALLY EXPEDITED THEM TO GET THEM TO THEM OVER THE HOLIDAYS 13 AT THEIR REQUEST SO THAT WE COULD TEE THIS ISSUE UP TO THE 14 EXTENT THAT THEY WANTED TO PURSUE IT AS QUICKLY AS WE COULD. 15 SO THE OVER THE HOLIDAYS WAS AT PLAINTIFFS' REQUEST. 16 17 18 19 20 21 22 23 24 25 THE COURT: THAT'S -- WHAT DATE WAS THAT? WE BECAUSE I THINK JUDGE GREWAL SET THE MOTION FOR FEBRUARY 26TH. IS THAT RIGHT? MS. DERMODY: UNDER NORMAL TIME, AND WE MADE A MOTION FOR SHORTENED TIME, WHICH HAS NOT BEEN RULED ON. MR. SAVERI: SO LET ME ANSWER TWO QUESTIONS. THE DATE FOR MR. CAMPBELL RIGHT NOW IS FEBRUARY 5. WITH RESPECT TO THE MOTION, AS I UNDERSTAND IT, WE HAVE ASKED GOOGLE TO AGREE TO SHORTEN TIME. MR. RUBIN: AND WE'RE PREPARED TO DO THAT. UNITED STATES COURT REPORTERS I THINK 255 94 1 THE INITIAL REQUEST WAS TO HAVE IT DUE TOMORROW, WHICH WE 2 WEREN'T IN A POSITION TO DO GIVEN THIS WEEK. 3 4 THE COURT: NOW. OKAY. LET'S SET THIS SCHEDULE RIGHT WHEN ARE YOU GOING TO FILE THE OPPOSITION? 5 MR. RUBIN: WE CAN FILE A RESPONSE -- 6 THE COURT: WHEN ARE YOU GOING TO FILE A REPLY? 7 MR. RUBIN: WE CAN FILE A RESPONSE BY NEXT FRIDAY, 8 AND I BELIEVE PLAINTIFFS SAID THEY DON'T NEED A REPLY AND THEY 9 WERE PREPARED TO SUBMIT. 10 AND SO I THINK THAT WE WOULD BE PREPARED TO DO THAT. 11 BE PREPARED TO SET -- AN EIGHT PAGE BRIEF I THINK IS WHAT THEY 12 PROPOSED, SUBMIT ANY SUPPORTING DECLARATIONS, AND SUBMIT WITH 13 THE EIGHT PAGE BRIEF AND LET EITHER YOUR HONOR OR JUDGE GREWAL 14 DECIDE THE ISSUE. 15 THE COURT: I THINK JUDGE GREWAL -- 16 MR. RUBIN: OKAY. 17 THE COURT: -- IS THE DECIDER ON THAT. 18 MS. DERMODY: WE'D 19 YES, WE WOULD WAIVE THE REPLY AND WE WOULD WAIVE ARGUMENT JUST TO MOVE THIS ALONG. 20 THE COURT: OKAY. 21 MR. RUBIN: SO WE'LL SEND THAT BY FRIDAY, THE 25TH. 22 THE COURT: THE 24TH. 23 WRONG YEAR. 24 RIGHT. 25 I'M SORRY. OH, MAYBE I'M LOOKING AT THE MR. RUBIN: I'M LOOKING AT THE WRONG YEAR. YOU'RE JANUARY 25TH. UNITED STATES COURT REPORTERS 256 95 1 THE COURT: I'M A LITTLE BIT UNCLEAR ON HOW THIS 2 DOCUMENT DISCOVERY WORKED SO FAR. 3 PRODUCE DOCUMENTS OF CUSTODIANS THAT ARE IDENTIFIED BY THE 4 PLAINTIFFS? 5 MS. DERMODY: DID THE DEFENDANTS ONLY THAT HAS BEEN A POINT OF CONTENTION, 6 YOUR HONOR, ACTUALLY. 7 THAT IF A WITNESS IS ON THE RULE 26 DISCLOSURE, THEY SHOULD BE 8 A CUSTODIAN BECAUSE THEY WERE IDENTIFIED AS A WITNESS IN THE 9 CASE. 10 WE HAVE -- WE BELIEVED FOR SOME TIME IT BECAME CLEAR TO US OVER TIME THAT THAT WASN'T ALWAYS 11 THE PRACTICE OF EVERY DEFENDANT, AND WE'VE HAD -- AS THE COURT 12 MIGHT HAVE SEEN IN THE DECEMBER 12TH CMC STATEMENT THAT WE 13 PREVIOUSLY SUBMITTED, THERE WAS A LOT OF DISAGREEMENT BETWEEN 14 THE PARTIES ABOUT WITNESSES AND THE TIMING OF DISCLOSING 15 WITNESSES. 16 I THINK THAT WE NOW AT LEAST HAVE MADE CLEAR OUR REQUEST 17 THAT EVERYONE WHO'S ON DEFENDANTS' RULE 26 DISCLOSURE LIST 18 SHOULD BE A CUSTODIAN AND THEIR DOCUMENTS SHOULD BE DISCLOSED. 19 PRESUMABLY WE'LL TAKE THE DEPOSITIONS OF ALL OF THOSE PEOPLE. 20 WE -- AS WE'RE GETTING MORE DOCUMENTS, WE'VE BECOME AWARE 21 OF THE PEOPLE WHO ARE MOST INSTRUMENTAL IN THE CHAIN AND WE, AS 22 QUICKLY AS WE CAN, RAISE THOSE ISSUES WITH THE DEFENDANTS. 23 WE'VE HAD VERY EXTENSIVE MEET AND CONFERS WITH A NUMBER OF 24 DEFENDANTS, INCLUDING APPLE AND GOOGLE, TRYING TO ACCOMMODATE 25 RESISTANCE OF THE DEFENDANTS TO SOME OF OUR WITNESS LISTS AND UNITED STATES COURT REPORTERS 257 96 1 WE'VE CUT DOWN WITNESS LISTS AND WE'VE TRIED TO REDUCE 2 REDUNDANCIES. 3 IT'S A CHALLENGE WITH THOSE COMPANIES. GOOGLE IN 4 PARTICULAR HAD SUCH A BIG RECRUITING DEPARTMENT THAT FOR US TO 5 GET A SENSE OF HOW THINGS WERE DONE, WE THOUGHT WE HAD TO GET A 6 FEW MORE PEOPLE THAN WE HAD INITIALLY REQUESTED. 7 ONGOING DEBATE WITH THEM. 8 COURT ON THAT. 9 10 11 THAT'S AN WE MIGHT HAVE TO COME BACK TO THE SO FAR I THINK THAT WE'RE WORKING PRETTY SMOOTHLY, BUT THERE HAVE BEEN SOME HICCUPS IN THE ROAD. THE COURT: SO THERE'S NO DOCUMENT REQUEST THAT 12 SAYS, YOU KNOW, "PRODUCE ALL DOCUMENTS THAT YOU INTEND TO RELY 13 ON AT TRIAL OR FOR THE CLASS CERTIFICATION MOTION"? 14 MS. DERMODY: 15 MR. SAVERI: 16 17 YEAH. WE -- I THINK ACTUALLY THERE'S MORE THAN ONE THAT SAYS, IN SUM OR SUBSTANCE, THAT. THE COURT: OKAY. BECAUSE I DIDN'T UNDERSTAND WITH, 18 FOR EXAMPLE, MS. MAUPIN, LUCASFILM SAYS, "WELL, WE PROPOSED 19 ONLY 16 KEY CUSTODIANS OUT OF THE PLAINTIFFS' LIST OF 57, AND 20 THEY NEVER RESPONDED TO OUR LETTER, SO WE HAD NO OBLIGATION TO 21 DISCLOSE THE DOCUMENTS OF ANYONE OTHER THAN OUR 16, EVEN IF WE 22 WERE INTENDING TO RELY ON THESE INDIVIDUALS IN OUR OPPOSITION 23 TO CLASS CERT." 24 25 I THOUGHT THAT WAS KIND OF A WEAK ARGUMENT. MR. PURCELL: I'M NOT SURE, DID WE ACTUALLY SAY UNITED STATES COURT REPORTERS 258 97 1 THAT? 2 I'M NOT SURE THAT WE SAID EXACTLY THAT. WHAT WE SAID WAS THAT WE HAD A MEET AND CONFER WITH THEM, 3 WE WERE TRYING TO IMPOSE A REASONABLE LIMIT ON THE NUMBER OF 4 CUSTODIANS AND WE MADE A COUNTER PROPOSAL THAT THEY NEVER 5 RESPONDED TO. 6 7 AT THE POINT THAT WE HAD THAT DISCUSSION, THAT WAS IN MARCH OF LAST YEAR. 8 9 THE COURT: MS. MAUPIN -SO TELL ME, FOR THE ENTIRE YEAR, SINCE MARCH, YOU'VE ONLY BEEN PRODUCING DOCUMENTS AS TO THE 16 PEOPLE 10 THAT YOU UNILATERALLY SELECTED -- 11 MR. PURCELL: 12 THE COURT: 13 MR. PURCELL: 14 WE DIDN'T UNILATERALLY -- -- AS THE CUSTODIANS? WE DIDN'T UNILATERALLY SELECT THEM. WE SELECTED THEM -- 15 THE COURT: OUT OF THE 57. 16 MR. PURCELL: -- IN A MEET AND CONFER WITH 17 PLAINTIFFS, AND IF THEY HAD A COUNTER PROPOSAL, WE WOULD EXPECT 18 THEM TO MAKE A COUNTER PROPOSAL. 19 THE COURT: OKAY. SO IF THERE ARE ANY OTHER 20 WITNESSES YOU ARE INTENDING TO RELY ON AT TRIAL, YOU ARE NOT 21 PRODUCING THEIR DOCUMENTS BECAUSE THEY'RE NOT ON YOUR LIST OF 22 16? 23 MR. PURCELL: WE'VE SUBSEQUENTLY HAD ADDITIONAL MEET 24 AND CONFERS AND WE'VE PRODUCED FROM OTHER CUSTODIANS, INCLUDING 25 MS. MAUPIN WHO, BY THE WAY, WAS NOT ADDED TO OUR INITIAL UNITED STATES COURT REPORTERS 259 98 1 DISCLOSURES UNTIL SEPTEMBER OF THIS YEAR. 2 LITTLE LATER, BUT IN PLENTY OF TIME TO BE DEPOSED AND TO HAVE 3 HER DOCUMENTS PRODUCED, BOTH OF WHICH THINGS ARE SCHEDULED AND 4 ARE GOING TO BE COMPLETED IN THE NEXT FEW WEEKS. 5 6 THE COURT: SHE WAS ADDED A WHEN DID YOU FIRST PRODUCE DOCUMENTS FOR MS. MAUPIN? 7 MR. PURCELL: WE PRODUCED THE VAST VOLUME OF WHAT WE 8 CALL TRACK ONE DOCUMENTS EARLIER THIS YEAR, I THINK IN THE 9 MIDDLE OF THE YEAR, WHICH CONSISTS BASICALLY OF ALL OF 10 LUCASFILM'S COMPENSATION DATA, ALL OF THE THINGS THAT 11 DR. LEAMER PURPORTED TO RELY ON IN HIS REPORT. 12 WE HAVE SOME ADDITIONAL DOCUMENTS FROM MS. MAUPIN THAT ARE 13 IN PROCESS NOW AND THAT ARE GOING TO BE PRODUCED AROUND 14 FEBRUARY 1ST. 15 AND THAT WAS -- 16 THE COURT: I DON'T UNDERSTAND. WHY ARE YOU -- YOU 17 RELY ON HER DECLARATION FOR YOUR OPPOSITION THAT'S FILED, WHAT, 18 IN DECEMBER, AND THEN YOU PRODUCE HER DOCUMENTS IN FEBRUARY? 19 20 21 MR. PURCELL: WELL, THEY ASKED FOR THE DOCUMENTS AND THEY ASKED FOR THE DEPOSITION IN DECEMBER OR NOVEMBER. YOUR HONOR, I DON'T BELIEVE THERE'S ANY OBLIGATION THAT 22 EVERYBODY ON YOUR RULE 26 DISCLOSURE HAS TO BE A DOCUMENT 23 CUSTODIAN. 24 THE RULE. 25 I JUST DON'T THINK THAT'S THE LAW. THE COURT: THAT'S NOT IN WELL, I THINK THERE'S BEEN A DOCUMENT UNITED STATES COURT REPORTERS 260 99 1 REQUEST THAT YOU PRODUCE DOCUMENTS THAT YOU INTEND TO RELY ON 2 FOR YOUR DEFENSES, SO WHY WOULD THAT NOT INCLUDE WHATEVER YOU 3 HAVE FOR MS. MAUPIN? 4 MR. PURCELL: 5 ARE PRODUCING THEM NOW. 6 THE COURT: WELL, IT IS INCLUDING IT. I MEAN, WE YOU'RE PRODUCING THEM FEBRUARY 1ST AFTER 7 YOU'VE ALREADY RELIED ON HER DECLARATION FOR YOUR OPPOSITION 8 FOR YOUR EXPERT REPORT. 9 MR. PURCELL: 10 11 I THINK THAT'S PROBLEMATIC. I GUESS I WOULD DISAGREE, YOUR HONOR. I DON'T SEE WHY THAT'S PROBLEMATIC. THEY RAISED THE ISSUE, OBVIOUSLY -- 12 THE COURT: WOULD YOU BE SATISFIED IF YOU DIDN'T 13 HAVE THE PLAINTIFFS' DOCUMENTS AND YOU'RE REQUIRED TO FILE AN 14 OPPOSITION TO THEIR MOTION FOR CLASS CERT WITHOUT HAVING ALL 15 THE PLAINTIFFS' DOCUMENTS AND THE PLAINTIFFS COME IN AND SAY, 16 "WELL, WE'RE PRODUCING THEM ON FEBRUARY 1ST"? 17 18 MR. PURCELL: WELL, I MIGHT RAISE THE ISSUE, YOUR HONOR. 19 BUT THEY HAD THE OPPORTUNITY TO ASK FOR ADDITIONAL 20 CUSTODIANS, INCLUDING MS. MAUPIN -- THEY KNEW WHO MS. MAUPIN 21 WAS -- AND THEY NEVER RESPONDED TO A LETTER THAT WE SENT THEM 22 SAYING "WE THINK 57 CUSTODIANS IMPOSES AN UNREASONABLE BURDEN. 23 HOW ABOUT THESE 16 WHICH ARE THE CORE PEOPLE?" 24 25 WE NEVER HEARD FROM THEM FOR SIX TO EIGHT MONTHS. THAT'S NOT DILIGENCE, YOUR HONOR. UNITED STATES COURT REPORTERS 261 100 1 THE COURT: A CASE OF THIS MAGNITUDE -- YOU THINK 57 2 CUSTODIANS IS TOO MUCH TO COLLECT DOCUMENTS FROM IN A CASE OF 3 THIS MAGNITUDE? 4 5 6 MR. PURCELL: IN A COMPANY OF 400 WORKERS, YES, YOUR HONOR. AND IN ANY EVENT, IF THEY DISAGREED, WHICH THEY DID 7 EVENTUALLY AFTER THE FACT, THEY HAD AN OBLIGATION TO BE 8 DILIGENT AND FOLLOW UP WITH US, WHICH THEY DIDN'T DO. 9 CAN'T SIT ON THEIR HANDS FOR SIX TO EIGHT MONTHS AND THEN COME 10 11 THEY IN AND COMPLAIN THAT WE DIDN'T PRODUCE SOMETHING. MS. DERMODY: WELL, YOUR HONOR, I THINK IT'S A 12 LITTLE UNFAIR TO CHARACTERIZE OUR ACTION THAT WAY. 13 HAD TO RELY, AS YOU DO WHEN YOU HAVE NO INFORMATION, ON THE 14 GOOD FAITH OF THE DEFENDANTS IN PRODUCING THE RELEVANT 15 DOCUMENTS, THE CORE DOCUMENTS. 16 I MEAN, WE WHEN MID-JUNE CAME AND WENT AND WE HAD A CHANCE TO LOOK AT 17 DOCUMENTS, WHAT IT REVEALED TO US IS WE WERE MISSING A LOT AND 18 WE GOT BACK TO DEFENDANTS WITH NAMES AS THEY CAME TO US. 19 IT WAS A SURPRISE TO US, QUITE CANDIDLY, WHEN WE 20 DISCOVERED THAT THE DEFENDANTS' EXPERT HAD BEEN TALKING TO 21 WITNESSES, DOING INTERVIEWS OVER THE SUMMER, AND THAT THOSE 22 PEOPLE WERE NOT DOCUMENT CUSTODIANS AND THOSE DOCUMENTS WEREN'T 23 PRODUCED TO US AND WE WERE STILL EXPECTED TO TELL THE 24 DEFENDANTS, "THESE PEOPLE THAT YOUR EXPERT THOUGHT WERE 25 IMPORTANT ENOUGH TO INTERVIEW, THE PLAINTIFFS HAVE TO COME UNITED STATES COURT REPORTERS 262 101 1 2 FORWARD AND TELL YOU TO PRODUCE THOSE DOCUMENTS." SO WE HAVE DONE THAT. WE HAVE COME FORWARD AND WE HAVE 3 REQUESTED THINGS, AND SOMETIMES WE'VE HAD TO NEGOTIATE FOR 4 WEEKS ON SOMETHING AS SIMPLE AS THAT. 5 BUT WE HAVE DONE IT AND WE THINK THAT WE'RE DOING 6 EVERYTHING THAT WE CAN TO GET THE DOCUMENTS AS QUICKLY AS 7 POSSIBLE. 8 BUT THE NOTION THAT WE'RE SITTING ON OUR HANDS I DON'T 9 THINK IS A VERY FAIR ASSESSMENT OF WHAT HAS HAPPENED SO FAR FOR 10 11 PLAINTIFFS. THE COURT: IF AT SUMMARY JUDGMENT ANY PARTY RELIES 12 ON THE DECLARATION OF A WITNESS THAT THEY HAVE NOT PREVIOUSLY 13 PRODUCED DOCUMENTS FOR, I'M GOING TO STRIKE THAT DECLARATION. 14 MR. PURCELL: 15 THE COURT: UNDERSTOOD, YOUR HONOR. OKAY? SO I'M REALLY DISPLEASED WITH THE 16 DEFENDANTS ON THIS EMPLOYEE ISSUE AND I'M GOING TO STRIKE 17 SEVERAL OF THOSE DECLARATIONS, IF NOT ALL OF THEM. 18 TO BE GAMESMANSHIP AND I'M REALLY DISAPPOINTED. 19 I FIND THIS I HAD HOPED THAT I'D MADE IT CLEAR AT PREVIOUS CMC'S THAT 20 I REALLY DIDN'T WANT TO SEE THIS KIND OF GAMESMANSHIP, SO TO 21 PLAY HIDE THE BALL AND THEN SAY, "WELL, IT'S THEIR OBLIGATION 22 TO BE ABLE TO LOOK THROUGH OUR OPAQUE COMPANY AND FIGURE OUT 23 WHO IS THE RELEVANT PERSON THEY SHOULD ASK FOR DOCUMENTS FROM" 24 WHEN THEY'RE NOT ON YOUR INITIAL DISCLOSURES IN MOST INSTANCES, 25 I'M JUST VERY DISAPPOINTED. UNITED STATES COURT REPORTERS 263 102 1 ANYWAY, ALL RIGHT. 2 DEPOSITIONS. 3 LET'S GO THROUGH WITH THE REST OF THE GOING TO GO FORWARD. 4 5 6 7 THESE ARE GOING TO BE SCHEDULED AND THESE ARE MS. DERMODY: THANK YOU, YOUR HONOR. FOR PIXAR, WE HAVE ED CATMULL, C-A-T-M-U-L-L, ON JANUARY 24TH. FOR INTUIT, BILL CAMPBELL, FEBRUARY THE 5TH. AND WE 8 TALKED ABOUT HIM EARLIER AND THE DOCUMENTS THAT ARE 9 OUTSTANDING. 10 11 AND THEN WE HAVE REQUESTED QUITE A FEW WITNESSES FROM APPLE THAT HAVE NOT BEEN SCHEDULED. 12 THE COURT: OKAY. 13 MS. DERMODY: WHO HAVE YOU REQUESTED? SO ON THE RULE 26 DISCLOSURES, THERE 14 ARE ONE, TWO, THREE, FOUR, FIVE, SIX, SEVEN, EIGHT, NINE PEOPLE 15 THEY'VE LISTED. 16 THE NAMES IF YOU'D LIKE, YOUR HONOR. WE'VE REQUESTED ALL OF THEM. 17 THE COURT: 18 MS. DERMODY: 19 THE COURT: 20 I CAN GIVE YOU AND YOU DON'T HAVE ANY DATES? NO DATES. ALL RIGHT. WHO'S HERE FROM APPLE? IS THAT MR. TUBACH? 21 MR. TUBACH: 22 THE COURT: 23 PROVIDE DATES FOR THE WITNESSES. 24 MR. TUBACH: 25 YES. GIVE ME A DATE BY WHICH YOU'RE GOING TO I CAN GIVE YOU THE DATES, SAME AS FOR GOOGLE, A WEEK FROM FRIDAY IF THAT'S OKAY WITH THE COURT. UNITED STATES COURT REPORTERS 264 103 1 THE COURT: 2 WHEN DID YOU REQUEST THESE DEPOSITIONS? MR. TUBACH: DECEMBER 17TH, YOUR HONOR, IN ONE 3 LETTER THEY SENT TO ALL DEFENDANTS SAYING, "WE WANT DATES FOR 4 EVERY PERSON ON YOUR RULE 26 LIST." 5 6 7 THE COURT: 10 SO THAT WOULD BE JANUARY 25TH. ALL RIGHT. 8 9 ALL RIGHT. WHO ELSE DO YOU NEED? MS. DERMODY: YOUR HONOR, THAT SO FAR IS THE LIST OF NAMES THAT I HAVE. AS I MENTIONED, WE HAVE REQUESTED ALL THE RULE 26 PEOPLE 11 FROM ALL DEFENDANTS. 12 WITNESSES. 13 WE HAVE NOT RECEIVED EVERYONE'S AND WE HAVE BEEN WORKING WITH GOOGLE ON AN ADDITIONAL 14 GROUP OF CUSTODIANS. 15 DEPOSITION DATES FOR ALL OF THEM OR SOME SUBSET OF THEM. 16 17 18 THE COURT: I IMAGINE THAT WE ARE GOING TO REQUEST OKAY. I DO WANT TO TALK ABOUT CUSTODIANS -- I'M SORRY TO INTERRUPT YOU. WHAT ABOUT DEBORAH CONRAD? SHE WAS IN YOUR CMC STATEMENT. 19 HAS SHE BEEN DEPOSED OR NOT? I HAD ON MY LIST THAT IT WAS 20 PATRICIA MURRAY, THE SENIOR VICE-PRESIDENT -- 21 MR. SAVERI: YES. 22 MR. HINMAN: YOU TOOK THAT DEPOSITION. 23 MR. SAVERI: I TOOK DEBORAH CONRAD'S DEPOSITION. 24 THE COURT: 25 MR. SAVERI: OKAY. SO THAT'S DONE. THAT'S DONE. UNITED STATES COURT REPORTERS 265 104 1 2 THE COURT: OTHER THAN THE ONES THAT YOU'VE LISTED? 3 4 5 SO ANYONE ELSE THAT NEEDS TO BE DEPOSED, MR. SAVERI: THAT WE'VE -- AGAIN, MS. DERMODY IDENTIFIED WHERE WE ARE WITH GOOGLE. AND YOU KNOW, OF COURSE PART OF THE PROBLEM WE FACE, YOUR 6 HONOR, IS THAT WHEN WE REVIEW DOCUMENTS, WE MAY FIND ADDITIONAL 7 WITNESSES. 8 9 10 BUT TO THE BEST OF OUR RECOLLECTION AT THIS POINT, WE'VE GIVEN YOU A COMPLETE LIST OF WHO WE'VE IDENTIFIED AND REQUESTED AT THIS TIME. 11 THE COURT: 12 MS. DERMODY: 13 THE COURT: 14 MR. SAVERI: 15 MS. DERMODY: 16 17 ALL RIGHT. I'M SORRY -- LET'S TALK ABOUT THE DOCUMENT REQUESTS. I'M SORRY. DID I MISSPEAK? I WANT TO MAKE SURE THE RECORD IS CLEAR. FOR APPLE, YOUR HONOR, I DID SAY THERE ARE OUTSTANDING 18 RULE 26 WITNESSES. THERE IS ALSO ONE SEPARATE WITNESS, 19 TIM COOK, THAT THERE'S BEEN A NEGOTIATION FOR A WHILE ABOUT A 20 DATE, I BELIEVE, FOR TIM COOK, AND IF THAT CAN BE ON THE LIST 21 FOR NEXT FRIDAY OF SOMEONE TO SCHEDULE -- 22 MR. TUBACH: NO, YOUR HONOR, WE HAVEN'T AGREED TO 23 PRODUCE TIM COOK FOR DEPOSITION. 24 WE AMENDED THAT LIST, PROVIDED IT TO PLAINTIFFS, AND TOOK HIM 25 OFF THE LIST. HE WAS ON OUR RULE 26 LIST. UNITED STATES COURT REPORTERS 266 105 1 BASED ON THE DEPOSITIONS OF TWO APPLE WITNESSES, THEY 2 CONFIRM THAT MR. COOK WAS NOT INVOLVED AND DOES NOT HAVE 3 FIRSTHAND KNOWLEDGE OF ANY OF THESE AGREEMENTS AND DOES NOT 4 HAVE DISCOVERABLE INFORMATION, SO WE REMOVED HIM FROM THE RULE 5 26 LIST. 6 7 8 9 10 PLAINTIFFS TOLD US TWO DAYS AGO THAT THEY DISAGREED WITH THAT, SO IF THAT NEEDS TO BE BROUGHT TO THE -THE COURT: WHEN DID HE ASSUME HIS ROLE? I MEAN, I KNOW HE'S BEEN AT APPLE FOR A VERY LONG TIME. MR. SAVERI: WELL, AND THAT'S -- YOUR HONOR, HIS 11 ROLE HAS CHANGED, AND IT CHANGED IN A SIGNIFICANT WAY. 12 BECAME MORE SENIOR WITH THE PASSAGE OF TIME IN THE COMPANY. 13 DON'T KNOW EXACTLY WHEN THE DATES ARE. 14 THE COURT: 15 MR. SAVERI: 16 THE COURT: 17 MR. SAVERI: HE I WAS IT DURING THE CLASS PERIOD? YES. IT'S BEFORE 2009? YES. SO THERE ARE DOCUMENTS, WE 18 BELIEVE, AND WE -- THIS IS PART OF THE DISAGREEMENT. 19 DOCUMENTS, RELEVANT DOCUMENTS IN THIS CASE THAT, FRANKLY, WE 20 THINK ARE GOING TO BE EVIDENCE AT TRIAL THAT MR. COOK RECEIVED 21 AND HAS KNOWLEDGE OF. 22 THE COURT: 23 24 25 THERE ARE WHEN -- I KNOW HE'S HAD VARIOUS ROLES. TELL ME WHAT HIS ROLE WAS BEFORE DECEMBER OF 2009. MR. RILEY: YOUR HONOR, HE WAS THE -- THIS IS GEORGE RILEY FOR APPLE -- HE WAS THE CHIEF OPERATING OFFICER OF UNITED STATES COURT REPORTERS 267 106 1 2 3 THE COMPANY. HE HAD NO ROLE IN H.R., NO ROLE IN RECRUITING. SUBSEQUENT, AFTER MR. JOBS HAD AN OPERATION, HE BECAME ACTING CEO. 4 LATER WHEN MR. JOBS RETURNED TO THE COMPANY, MR. COOK 5 BECAME CEO IN AUGUST OF 2011, WELL AFTER THE CLASS PERIOD. 6 THE COURT: WELL, I JUST FIND IT REALLY HARD TO 7 BELIEVE THAT A CHIEF OPERATING OFFICER WOULD HAVE NO SAY OVER 8 SALARIES AND COMPENSATION OF ALL OF THE EMPLOYEES OF THE 9 COMPANY. 10 MR. RILEY: AT APPLE -- 11 MR. SAVERI: EXCUSE ME. 12 MR. RILEY: AT APPLE, THE CHIEF OPERATING OFFICER 13 WORKS ON OPERATIONS. THE COMPENSATION OFFERS ARE SET BY THE 14 COMPENSATION COMMITTEE. 15 MR. COOK HAD NO REPORTING OBLIGATIONS, NO REPORTING LINES 16 AT ALL TO THE COMPENSATION COMMITTEE. 17 APPLE REPORTS DIRECTLY TO THE CEO, MR. JOBS. 18 19 20 THE H.R. DIRECTOR AT SO, YOUR HONOR, THAT'S WHY WE -- THEY TOOK THE DEPOSITION -THE COURT: SO SOMEONE IN CHARGE OF OPERATION HAS NO 21 SAY OR NO KNOWLEDGE ABOUT THE GREATEST PROBABLY EXPENSE OF 22 OPERATIONS, WHICH IS SALARIES AND COMPENSATION OF EMPLOYEES? 23 24 25 MR. RILEY: OBVIOUSLY HE WOULD HAVE THE SAME KNOWLEDGE AS ANY EXECUTIVE OFFICER WOULD OF THE BUDGET. BUT IN TERMS OF ACTUALLY SETTING COMPENSATION LEVELS FOR UNITED STATES COURT REPORTERS 268 107 1 THE COMPANY COMPANY-WIDE, HE DID NOT PLAY A ROLE IN THAT. 2 AND THEY HAVE HAD AN OPPORTUNITY TO DEPOSE THOSE 3 4 INDIVIDUALS WHO DID PLAY THOSE ROLES. AND, YOUR HONOR, THEY HAVE NOT PRODUCED IN THIS CASE ANY 5 E-MAIL THAT HAS MR. COOK'S NAME ON IT THAT RELATES TO THESE 6 AGREEMENTS AT ALL. 7 THE COURT: HAVE YOU PRODUCED MR. COOK'S DOCUMENTS? 8 MR. SAVERI: WELL, I'M SORRY, THEY ARE MR. COOK'S 9 10 DOCUMENTS. THE COURT: I KNOW. THAT'S WHAT I'M ASKING. I'M 11 ASKING -- YOU'RE SAYING PLAINTIFFS HAVEN'T PRODUCED A SINGLE 12 E-MAIL FROM MR. COOK. 13 14 SO LET ME ASK YOU, HAVE YOU PRODUCED MR. COOK'S E-MAILS? BECAUSE YOU WOULD HAVE THEM MORE THAN THE PLAINTIFFS. 15 MR. RILEY: WE -- 16 THE COURT: HAS THERE BEEN ANY DOCUMENT COLLECTION 17 OF MR. COOK'S DOCUMENTS SUCH THAT THE PLAINTIFFS COULD HAVE 18 POINTED TO A DOCUMENT, THE RELEVANT DOCUMENT THAT HE WOULD BE 19 LISTED AS A RECIPIENT OR SENDER? 20 MR. RILEY: YES, YOUR HONOR. IN CONNECTION WITH THE 21 DEPARTMENT OF JUSTICE INVESTIGATION, WE DID A SEARCH AND WE 22 PRODUCED DOCUMENTS, AND I BELIEVE THEY HAVE GOTTEN A HANDFUL OF 23 DOCUMENTS, NOT RELEVANT TO THESE AGREEMENTS, THAT HAVE 24 MR. COOK'S NAME ON THEM. 25 BUT THAT'S -- THAT IS THE POINT, YOUR HONOR, AND THAT'S UNITED STATES COURT REPORTERS 269 108 1 WHY THEY HAVEN'T ASKED FOR HIS DEPOSITION ANY EARLIER IS THAT 2 HE DID NOT PLAY A ROLE IN THESE AGREEMENTS. 3 4 THE COURT: WHEN WAS THE DOCUMENT PRODUCTION IN THE D.O.J. CASE? 5 MR. SAVERI: 6 WAS THEIR PRODUCTION. 7 MR. RILEY: 8 MR. SAVERI: 9 WHEN WAS IT? AGAIN, I DON'T KNOW. IT YOUR HONOR -IT WAS PRESUMABLY SOME TIME DURING THE PROCEEDING. 10 MR. RILEY: 11 PRODUCE FOR MR. COOK. 12 THE COURT: YOUR HONOR, WE DID THOROUGHLY SEARCH AND HE WAS A CUSTODIAN. I JUST DON'T THINK THAT HIS ROLE -- IF I 13 REMEMBER CORRECTLY THE DATES OF THAT D.O.J. CASE, I THINK IT 14 MAY HAVE PRECEDED HIS SORT OF ASCENDENCY AT THE COMPANY. 15 MR. SAVERI: AND YOUR HONOR, IF I MAY, I MEAN, I -- 16 THERE'S AT LEAST ONE DOCUMENT, I BELIEVE, THAT IS -- THAT HAS 17 RELEVANT INFORMATION THAT THE DEFENDANTS DID PRODUCE TO US. 18 DON'T KNOW THE GENESIS OF IT AND WHOSE FILE IT CAME FROM, BUT 19 IT HAS MR. COOK'S NAME ON IT. 20 I AND MR. COOK, WE BELIEVE, FROM WHAT WE UNDERSTAND, WAS 21 AWARE OF APPLE'S DO NOT COLD CALL LIST AND SO WE THINK HE'S A 22 PERCIPIENT WITNESS. 23 AND IT STANDS TO REASON THAT SOMEONE AT THAT LEVEL IN THE 24 COMPANY KNEW ABOUT THE EXISTENCE OF THE DO NOT COLD CALL LIST, 25 KNEW ABOUT WHAT WAS GOING ON WITH RESPECT TO COMPENSATION. UNITED STATES COURT REPORTERS 270 109 1 2 3 BUT AGAIN, YOUR HONOR, WE'D LIKE TO PUT HIM UNDER OATH AND ASK THE QUESTIONS. THAT'S THE WAY THE PROCEDURE WORKS. I MEAN, WE'RE NOT -- THIS ISN'T JUST A WILD GOOSE CHASE. 4 MR. RILEY: YOUR HONOR, WE PRODUCED ALL OF HIS 5 DOCUMENTS. WE UPDATED THAT PRODUCTION AFTER THE D.O.J. CASE. 6 THEY DIDN'T HAVE ANY DOCUMENTS TO MR. COOK THAT RELATE TO THESE 7 AGREEMENTS OR TO THE DO NOT CALL LIST. 8 THEY DEPOSED THE HEADS OF H.R., BOTH PAST AND CURRENT, WHO 9 TESTIFIED UNDER OATH THAT THEY HAD NO DISCUSSIONS WITH MR. COOK 10 WHATSOEVER ABOUT THIS. 11 THE COURT: I'M GOING TO ORDER HIS DEPOSITION. 12 MR. RILEY: YOUR HONOR, WE WOULD LIKE IT LIMITED TO 14 THE COURT: I THINK A LIMIT OF HOURS IS REASONABLE. 15 MR. SAVERI: 13 16 TWO HOURS. ASKING A LOT. YOUR HONOR, I THINK TWO HOURS IS REALLY PERHAPS -- 17 THE COURT: MAKE A COUNTER PROPOSAL. 18 MR. SAVERI: I WOULD SAY HALF A DAY. 19 THE COURT: 20 MR. SAVERI: 21 MS. DERMODY: FOUR HOURS? FOUR HOURS IS FINE. AND WE WOULD ASK, YOUR HONOR, THAT HE 22 BE A DOCUMENT CUSTODIAN SO THAT THAT DEPOSITION BECOMES MORE 23 FRUITFUL THAN JUST ON A BLANK RECORD. 24 25 MR. RILEY: DOCUMENT CUSTODIAN. I WILL SAY FOR THE THIRD TIME, HE WAS A WE DID PRODUCE HIS DOCUMENTS. UNITED STATES COURT REPORTERS 271 110 1 2 THE COURT: WELL, I WOULD JUST ASK THAT YOU CONFIRM MR. SAVERI: AND MAYBE I DO -- WE NEED TO CLARIFY THAT. 3 4 THIS. WHEN MR. -- WHEN APPLE AFFIRMS THAT HE WAS A DOCUMENT 5 CUSTODIAN, DOES THAT MEAN HE WAS A DOCUMENT CUSTODIAN FOR THE 6 D.O.J. CASE AND THIS CASE OR BOTH? 7 8 9 10 MR. RILEY: BOTH. OR -- WE -- EARLY ON IN THIS CASE WE PRODUCED ALL THE DOCUMENTS THAT WE PRODUCED TO THE D.O.J. WE'VE SUBSEQUENTLY SEARCHED HIS DOCUMENTS AS A CUSTODIAN IN THIS CASE. I DON'T KNOW IF I CAN BE ANY CLEARER THAN THAT. 11 MR. SAVERI: THAT'S CLEAR. 12 MS. DERMODY: I MISUNDERSTOOD YOU. YOU'RE -- SO WE 13 UNDERSTAND, YOU'RE SAYING THAT YOU ACTUALLY USED THE SEARCH 14 TERMS AGREED TO IN THIS CASE AGAINST HIS E-DISCOVERY? 15 MR. RILEY: 16 MS. DERMODY: 17 THE COURT: 18 19 YES. OKAY. THANK YOU. ALL RIGHT. HE'LL BE DEPOSED FOR FOUR HOURS. WHO ELSE? 20 WHO ELSE NEEDS TO BE DEPOSED IN THIS CASE? MS. DERMODY: I THINK THAT'S THE COMPLETE LIST THAT 21 WE HAVE RIGHT NOW, YOUR HONOR. THANK YOU FOR THE OPPORTUNITY. 22 THE COURT: LET'S TALK ABOUT DOCUMENT 23 24 25 ALL RIGHT. REQUESTS. WITH REGARD TO KARINE KARPATI, CARSON PAGE, PATRICK FLYNN, YOU'RE GOING TO PRODUCE THEIR DOCUMENTS. I KNOW YOU'RE SAYING UNITED STATES COURT REPORTERS 272 111 1 THEY'RE LOW LEVEL H.R. PEOPLE. 2 DOCUMENTS. 3 THEIR NAMES ON ARE RELEVANT THEM. YOU NEED TO REVIEW AND PRODUCE DOCUMENTS AS TO 4 LET ME HEAR ABOUT LARRY PAGE AND SERGEY BRIN. 5 MY UNDERSTANDING OF THIS CASE IS THAT THESE AGREEMENTS 6 HAPPENED AT THE HIGHEST LEVELS OF ALL OF THESE COMPANIES AND 7 THE HIGHEST LEVELS OF THESE COMPANIES WERE INVOLVED IN 8 ENFORCEMENT OF THE AGREEMENTS. 9 10 11 SO LET ME HEAR WHY LARRY PAGE AND MR. BRIN SHOULD NOT BE CUSTODIANS. GO AHEAD. MR. RUBIN: YOUR HONOR, FIRST OF ALL, WE HAD ALREADY 12 REACHED AT LEAST PARTIAL AGREEMENT ABOUT THE GROUP THAT YOU HAD 13 ALREADY SAID AND WE WOULD AGREE TO SEARCH KARINE KARPATI'S 14 E-MAILS AND I BELIEVE -- WHO WAS THE OTHER -- WHAT WAS THE 15 OTHER NAME? 16 THE COURT: CARSON PAGE AND PATRICK FLYNN. 17 MR. RUBIN: PATRICK FLYNN. 18 THE COURT: IN THE JOINT CASE MANAGEMENT STATEMENT, 19 YOUR POSITION IS THEY ARE TWO LOW LEVEL H.R. PEOPLE AND YOU 20 WOULDN'T GET ANYTHING RELEVANT FROM THEM. 21 MR. RUBIN: AND WE HAD ACTUALLY AGREED THAT BECAUSE 22 KARINE CARPATTI AND CARSON PAGE WERE DUPLICATE, THEY AGREED TO 23 DROP CARSON PAGE. 24 WAS WHAT THE LETTER SAID. 25 THAT'S PART OF OUR ONGOING DISCUSSION. MS. SHAVER: I'M SORRY. THAT ANNE SHAVER FOR PLAINTIFFS. UNITED STATES COURT REPORTERS 273 112 1 WE'VE HAD ONGOING MEET AND CONFER EFFORTS. 2 REACHED AN AGREEMENT. 3 MR. RUBIN: WE HAVEN'T 4 5 COULD I ASK PLAINTIFFS' COUNSEL, THAT WAS A PROPOSAL IN THE LAST LETTER, THAT WE DROP CARSON PAGE. MS. SHAVER: AND WE -- THE PROPOSAL WAS DEPENDENT ON 6 A HOST OF AGREEMENTS, ALL THE CUSTODIANS THAT ARE AT ISSUE, AND 7 WE HAVEN'T HEARD BACK FROM YOU YET. 8 9 10 11 MR. RUBIN: RIGHT. SO -- SO ANYWAY, I HAD UNDERSTOOD WE HAD REACHED A TENTATIVE AGREEMENT TO DROP CARSON PAGE, BUT KEEP THE OTHER TWO. WITH LARRY PAGE AND SERGEY BRIN, WE HAD AGREED TO, IN 12 CONCEPT, PRODUCE DOCUMENTS, WHICH WE ARE IN THE MIDDLE OF 13 WORKING WITH THE PLAINTIFFS ON PARTICULAR SEARCH TERMS. 14 WE'VE DONE SOME RUNNING OF TERMS AND WE'RE FINDING THERE'S 15 A GOOD NUMBER OF WHAT I'LL CALL FALSE POSITIVES, AND THEY ARE 16 SIGNIFICANT NUMBERS. 17 18 19 SO WE'RE SIMPLY TRYING TO NARROW IT DOWN IN A WAY THAT I THINK EACH SIDE CAN LIVE WITH AND THEN RUN THOSE TERMS. SO WE'RE NOT TAKING A POSITION NOT TO RUN THEM. WE'RE 20 JUST SIMPLY SAYING LET'S KEEP THEM NARROWED TO WHAT THE LIKELY 21 ISSUES ARE FOR THOSE TWO CUSTODIANS. 22 THE COURT: ALL RIGHT. YOU'RE GOING TO PRODUCE 23 DOCUMENTS FOR ALL FIVE OF THEM, LARRY PAGE, SERGEY BRIN, 24 KARINE KARPATI, CARSON PAGE, AND PATRICK FLYNN. 25 OKAY? NOW, I WANT TO KNOW THE DATES OF WHEN THESE UNITED STATES COURT REPORTERS 274 113 1 DOCUMENTS ARE GOING TO BE PRODUCED, OKAY? 2 DATES. 3 LET'S START DOING SO YOU TELL ME. MR. RUBIN: YOUR HONOR, I WOULD THINK FROM THE TIME 4 THAT WE COULD -- WE WOULD TRY TO MEET AND CONFER WITH 5 PLAINTIFFS NEXT WEEK TO AGREE ON IF WE CAN -- 6 THE COURT: NO. I WANT A DATE. I DON'T WANT THIS 7 HANGING OUT THERE. 8 TO SET A HEARING AND EVERYTHING LIKE THAT. 9 I DON'T WANT THIS TO BE BRIEFED AND HAVING MR. RUBIN: I WANT A DATE. JANUARY 25TH, SO I WOULD SAY THREE WEEKS 10 FROM THE 25TH, SO WHATEVER THAT DATE IS. 11 FEBRUARY THE 15TH. 12 THE COURT: THAT WOULD BE NOW, I GUESS THIS IS THE PROBLEM. YOU 13 HAVE DEPOSITIONS OF SHONA BROWN HAPPENING JANUARY 30TH AND 14 ERIC SCHMIDT ON FEBRUARY 20TH, AND I'M NOT GOING TO HAVE 15 DELAYED PRODUCTION OF DOCUMENTS BE THE REASON WHY THESE HAVE TO 16 CONTINUE TO BE POSTPONED. SO -- 17 MR. RUBIN: WELL, THOSE CUSTODIANS -- 18 THE COURT: -- I THINK FEBRUARY 15TH IS TOO LATE. 19 MR. RUBIN: WELL, THOSE DOCUMENTS HAVE BEEN FULLY 20 PRODUCED, SHONA BROWN'S AND ERIC SCHMIDT'S. 21 HAVE BEEN SUBJECT TO INITIAL PRODUCTIONS, SUPPLEMENTAL 22 PRODUCTIONS. 23 THOSE DOCUMENTS SO I CERTAINLY CAN'T TELL YOU THAT THEY WOULDN'T SHOW UP 24 ON AN E-MAIL THAT WASN'T IN THEIR CUSTODIAL FILES AND NOW WOULD 25 BE IN THE OTHERS. UNITED STATES COURT REPORTERS 275 114 1 BUT I DO THINK THAT, YOUR HONOR, JUST BY WAY OF NECESSITY, 2 THERE'S SOME SEQUENCING THAT HAS TO TAKE PLACE. 3 SITUATION LIKE THIS WHERE I THINK PLAINTIFFS EXPLAINED THEY 4 CAME BACK, THEY ASKED FOR ADDITIONAL NAMES BASED UPON THE 5 PRODUCTION THAT WE HAD MADE, WE'VE THEN GONE BACK AND SAID YES 6 AS TO SOME, WHY AS TO OTHERS. 7 SO THERE HAS TO BE SOME SEQUENCING. I MEAN, IN A OTHERWISE EVERYBODY 8 WOULD WAIT UNTIL -- WE'RE JUST TRYING TO RESPOND TO THE 9 REQUESTS THAT HAVE COME AFTER OUR INITIAL PRODUCTIONS. 10 THE COURT: WELL, I UNDERSTAND. THE PROBLEM IS 11 WE'RE BREATHING DOWN THE NECK OF A MARCH 29TH FACT DISCOVERY 12 CUT OFF AND THE LATER THESE GET PRODUCED, THEN IT'S GOING TO 13 CREATE THIS MAD SCRAMBLE FOR EITHER ANY FOLLOW-UP DISCOVERY 14 REQUESTS OR MORE DEPOSITIONS AND THIS DEADLINE IS LOOMING, SO I 15 NEED IT SOONER THAN THAT. 16 MR. RUBIN: WELL, I THINK WE COULD DO -- I THINK WE 17 COULD DO THE THREE -- WE'VE ALREADY -- THERE WERE FOUR THAT WE 18 HAD ALREADY AGREED TO. 19 EARLIER. 20 21 I THINK THOSE COULD BE PRODUCED THE THREE, CARSON PAGE AND KARINE KARPATI AND PATRICK FLYNN, PERHAPS THE WEEK BEFORE. 22 THE COURT: OKAY. 23 MR. RUBIN: BUT I REALLY DO -- WE REALLY DO NEED THE 24 TIME, YOUR HONOR, TO PRODUCE THE PAGE AND BRIN DOCUMENTS, SO -- 25 WE REALLY DO. UNITED STATES COURT REPORTERS 276 115 1 SO IF WE -- I CERTAINLY CAN PROPOSE A ROLLING PRODUCTION 2 OVER THE TWO WEEK PERIOD BEGINNING FEBRUARY 1, FEBRUARY 8TH, 3 FEBRUARY 15TH, AND THEN SUBSTANTIALLY COMPLETE THIS 4 SUPPLEMENTAL GROUP THAT WE'RE TRYING TO FOLLOW UP ON AT THEIR 5 REQUEST, THAT WE FINISH BY FEBRUARY 15TH, UNDERSTANDING THAT 6 PAGE AND BRIN MAY TAKE THE LONGEST TIME. 7 8 THE COURT: WELL, I'D LIKE TO SAY FEBRUARY 1ST FOR KARPATI, PAGE, AND FLYNN. I'M SORRY, CARSON, PAGE, AND FLYNN. 9 MR. RUBIN: CARSON PAGE IS ONE PERSON. 10 THE COURT: FRANKLY -- 11 MR. RUBIN: THERE ARE TWO PAGES. 12 13 14 THERE'S LARRY PAGE AND CARSON PAGE. THE COURT: KARINE KARPATI, CARSON PAGE, AND PATRICK FLYNN, FEBRUARY 1ST. 15 MR. RUBIN: OKAY. 16 THE COURT: OKAY? 17 MR. RUBIN: BUT IF WE COULD HAVE UNTIL THE 15TH, I -- 18 YOUR HONOR, FOR THE OTHER TWO, THAT WOULD -- I'M JUST TRYING TO 19 BE REALISTIC. 20 DOCUMENTS AND IT'S -- WE NEED THAT TIME. 21 WE'VE BEEN PRODUCING SUBSTANTIAL AMOUNTS OF THE COURT: I'LL GIVE YOU UNTIL FEBRUARY 11TH, OKAY, 22 JUST BECAUSE THEY MAY NEED THOSE DOCUMENTS FOR THE ERIC SCHMIDT 23 DEPOSITION ON FEBRUARY 20TH. 24 CAN KEEP GETTING KICKED DOWN THE ROAD. 25 CLOSE TO ALL OF THIS. I DON'T WANT TO KEEP HAVING THE WE NEED TO BRING A UNITED STATES COURT REPORTERS 277 116 1 2 ALL RIGHT. LET'S GO TO APPLE. TO PRODUCE THE DOCUMENTS. 3 MR. SAVERI: 4 THE COURT: 5 6 9 YOUR HONOR -TONY FADELL, F-A-D-E-L-L. HE COMMUNICATED WITH STEVE JOBS ABOUT THE POACHING, AND YOU'RE SAYING HE DOESN'T HAVE RELEVANT DOCUMENTS. 7 8 TONY FADELL, YOU'RE GOING MR. TUBACH: YOUR HONOR, THE PLAINTIFFS HAD AGREED TO TAKE HIM OFF THE LIST AND THEY TOOK HIM OFF THE LIST. THEY DID NOT ASK FOR THE DEPOSITION UNTIL TWO DAYS AGO, 10 AND FOR THE FIRST TIME THEY SAID, "WE ADMIT WE'RE CHANGING OUR 11 MINDS AND WE'VE NOW CHANGED OUR MINDS AND WE WANT TONY FADELL 12 AFTER ALL." 13 14 15 16 17 WE HEARD ABOUT THIS FOR THE FIRST TIME TWO DAYS AGO, YOUR HONOR. THE COURT: WELL, THIS IS BRIEFED IN THE CMC -- THE JOINT CASE MANAGEMENT STATEMENT FOR THE DECEMBER CMC. MR. TUBACH: THAT'S WHY WE FILED AN ADDITIONAL CMC 18 STATEMENT, YOUR HONOR, PROVIDING WHAT ARE THE NOW CURRENT SETS 19 OF DISPUTES, AND WE HAD AGREED WITH THE PLAINTIFFS THAT THEY -- 20 THAT THEY WOULD NOT BE DOING TONY FADELL. 21 THE COURT: 22 MR. TUBACH: OKAY. WELL, I -- THE PLAINTIFFS HAD AGREED WE DON'T HAVE 23 TO DO TONY FADELL, YOUR HONOR. 24 THE COURT: 25 MR. SAVERI: THESE DOCUMENTS HAVE BEEN RESOLVED? WE DO. WE WANT THE DOCUMENTS. UNITED STATES COURT REPORTERS 278 117 1 MS. DERMODY: 2 MR. TUBACH: YES. YOUR HONOR, UNTIL TWO DAYS AGO, THE 3 ANSWER WAS NO, AND THAT ANSWER WAS NO FROM NOVEMBER 30TH UNTIL 4 TWO DAYS AGO. 5 6 7 MR. SAVERI: YOUR HONOR, WE'D LIKE MR. FADELL'S DOCUMENTS. THE COURT: I MEAN, IF HE COMMUNICATED WITH 8 STEVE JOBS ABOUT THE ANTI-POACHING WITH GOOGLE, I JUST DON'T 9 SEE HOW YOUR POSITION WAS THAT HE DOESN'T HAVE RELEVANT 10 11 INFORMATION. MR. TUBACH: THE PLAINTIFFS AGREED THEY DIDN'T NEED 12 TO TAKE HIS DEPOSITION OR GET DOCUMENTS, YOUR HONOR. 13 A MATTER OF OUR POSITION. 14 IT'S NOT THEY AGREED WITH IT. AND IF THE PLAINTIFFS WANT TO CHANGE THEIR MIND, WHAT WE 15 ASKED THEM TO DO TWO DAYS AGO, WHICH THEY SHOULD BE REQUIRED TO 16 DO, IS TO AT LEAST SEND US A LETTER. 17 YOUR HONOR. 18 LETTER AND EXPLAIN TO US WHY THEY WANT TO GO BACK ON AN 19 AGREEMENT THAT WE REACHED TWO MONTHS AGO. 20 21 22 THIS WAS IN A PHONE CALL, THEY SHOULD AT LEAST BE REQUIRED TO SEND US A MR. SAVERI: AND YOUR HONOR, IF WE WERE TO SEND THE LETTER, IT WOULD BE SOME VERSION OF WHAT YOU JUST SAID. AND WE'RE HAPPY TO SEND MR. TUBACH A LETTER AND WE'RE 23 HAPPY IF HE WANTS TO LOOK AT IT, BUT I CAN PREDICT WITH SOME 24 CERTAINTY THAT WE'RE GOING TO ASK FOR THE DOCUMENTS. 25 MR. TUBACH: I'D LIKE TO SEE WHAT THE LETTER SAYS, UNITED STATES COURT REPORTERS 279 118 1 YOUR HONOR. 2 THEY ADMITTED THEY WERE CHANGING THEIR MINDS FROM THE AGREEMENT 3 WE HAD TWO MONTHS AGO, A CALL TWO DAYS AGO. 4 SO FAR IT'S BEEN ONE PHONE CALL TWO DAYS AGO WHERE THE COURT: ALL RIGHT. IF HE IS ON CORRESPONDENCE 5 WITH STEVE JOBS ABOUT WHETHER IT'S PERMISSIBLE TO POACH FROM 6 GOOGLE, WHAT WAS THE BASIS OF YOUR POSITION THAT HE HAD NO 7 RELEVANT DOCUMENTS? 8 9 10 MR. TUBACH: DOCUMENT. YOUR HONOR, I DON'T RECALL THE PRECISE THAT'S WHY -- WE HAVEN'T THOUGHT ABOUT THIS FOR TWO MONTHS BECAUSE THE PLAINTIFFS AGREED -- 11 THE COURT: WELL, THIS IS A DECEMBER 5TH DOCUMENT 12 FOR A DECEMBER 12TH CASE MANAGEMENT CONFERENCE, AND I'M SORRY I 13 WAS IN A PATENT TRIAL AT THAT TIME AND I COULDN'T HAVE THE CMC 14 AND I APOLOGIZE THAT I CONTINUED IT TO TODAY. 15 MR. TUBACH: 16 THE COURT: THAT'S NOT THE COURT'S FAULT. BECAUSE THIS IS NOW JUST -- YOU KNOW, 17 I'M JUST CONCERNED THAT WE'RE RUNNING UP AGAINST THIS DEADLINE 18 OF THE END OF MARCH, AND SO I CAN'T HAVE THESE DISPUTES 19 CONTINUING TO JUST DRAG ON. 20 ON THIS. 21 MR. TUBACH: I MEAN, WE NEED TO COME TO CLOSURE WE CAN COME TO CLOSURE WITH THE 22 PLAINTIFFS ON THIS, YOUR HONOR, AND IF WE CAN-NOT, WE WILL COME 23 BACK TO THE COURT EXPEDITIOUSLY. 24 BUT IT IS SIMPLY NOT FAIR FOR THEM TO CALL US TWO DAYS AGO 25 AND SAY, "YES, WE CHANGED OUR MIND," AND HAVE THE COURT RULE ON UNITED STATES COURT REPORTERS 280 119 1 IT TODAY. IT'S JUST NOT FAIR. 2 MS. DERMODY: 3 MR. TUBACH: 4 5 BUT NOW THAT WE'RE ALL HERE -WE WILL ACT EXPEDITIOUSLY TO RESPOND TO THE PLAINTIFFS' REQUEST. WE WILL RESPOND IMMEDIATELY. BUT WE HAVE THE RIGHT TO HEAR WHAT THEY HAVE TO SAY, TO 6 LOOK BACK INTO THE ISSUE, AND TO DECIDE WHETHER OR NOT THIS IS 7 SOMETHING THAT WE WANT TO AGREE TO OR NOT. 8 9 THE COURT: ALL RIGHT. THIS IS WHAT IT SAYS. IS DEFENDANT'S STATEMENT ON ECF NUMBER NUMBER 245. THIS "WITH 10 RESPECT TO THE SIXTH AND FINAL PROPOSED CUSTODIAN, TONY FADELL, 11 PLAINTIFFS HAVE IDENTIFIED NO SPECIFIC REASON FOR NEEDING HIS 12 DOCUMENTS, APART FROM IDENTIFYING A SINGLE DOCUMENT IN WHICH HE 13 INQUIRED ABOUT APPLE'S 'POACHING' PRACTICES, AND APPLE HAS 14 EXPLAINED THAT IT DOES NOT BELIEVE ADDING HIM AS A CUSTODIAN IS 15 WARRANTED." 16 17 I JUST -MR. TUBACH: YOUR HONOR, I NEED TO GO BACK AND LOOK 18 AT THAT DOCUMENT. IF IT'S A SINGLE DOCUMENT, IT PROBABLY IS 19 NOT WORTH HAVING THE ENTIRE PRODUCTION -- 20 THE COURT: IT'S A SINGLE DOCUMENT BECAUSE YOU 21 HAVEN'T PRODUCED HIS DOCUMENTS. 22 CUSTODIAN, SO YOU HAVEN'T PRODUCED HIS DOCUMENTS. 23 IS REALLY CIRCULAR. 24 THE DOCUMENTS UNTIL THE PLAINTIFFS CAN POINT TO OUR DOCUMENT 25 THAT SHOWS THAT THIS IS A RELEVANT CUSTODIAN." YOU DON'T CONCEDE HE'S A I MEAN, THIS YOU'RE SAYING, "WE'RE NOT GOING TO PRODUCE UNITED STATES COURT REPORTERS 281 120 1 MR. TUBACH: 2 THE COURT: 3 MR. TUBACH: 4 WE PRODUCED DOCUMENTS -THAT IS A RIDICULOUS BURDEN. THAT'S NOT -- I DON'T BELIEVE IT'S RIDICULOUS FOR THIS REASON, YOUR HONOR. 5 THE COURT: 6 OKAY. MR. TUBACH: WE PRODUCED DOCUMENTS FROM LOTS OF 7 OTHER CUSTODIANS, ALL OF WHOM HAVE BEEN INVOLVED IN ONE WAY OR 8 THE OTHER IN COMPENSATION, IN THE COLLABORATIVE VENTURES, OR IN 9 THE AGREEMENTS, AND THAT'S WHAT WE'VE PRODUCED. 10 AND IF THEY CAN POINT TO ONE E-MAIL, WHICH WE NEED TO GO 11 BACK AND LOOK AT -- IT DEPENDS ON WHAT THE E-MAIL SAYS, YOUR 12 HONOR. 13 14 15 THE COURT: IT'S A HIGHLY RELEVANT E-MAIL. IT'S AN E-MAIL TO STEVE JOBS ABOUT POACHING. SO I DON'T GET IT. MR. RILEY MADE THE SAME ARGUMENT, 16 LIKE, "WELL, IF YOU CAN'T POINT TO OUR DOCUMENTS, THEN WE'RE 17 NOT GOING TO PRODUCE THOSE DOCUMENTS." 18 I MEAN, THAT JUST MAKES NO SENSE. 19 20 21 AS A CUSTODIAN OF RECORD. YOU HAVEN'T TREATED HIM YOU HAVEN'T COLLECTED HIS DOCUMENTS. YOU'RE SAYING YOU HAVE TO GET HIM ON EVERYONE ELSE'S DOCUMENTS TO PROVE THAT HE'S RELEVANT. 22 WELL, THEY HAVE ACTUALLY FOUND HIM ON A VERY HIGHLY 23 RELEVANT DOCUMENT, AND NOW YOU'RE NOT WILLING TO PRODUCE HIS 24 DOCUMENTS? 25 KNOW THAT EVEN IF YOU CAPTURE ANOTHER PEOPLE'S E-MAILS, THEY IT JUST MAKES -- IT MAKES NO SENSE BECAUSE WE ALL UNITED STATES COURT REPORTERS 282 121 1 WON'T CAPTURE EVERYTHING THAT YOU HAVE SENT, THAT YOU HAVE 2 RECEIVED. 3 I MEAN, MAYBE HE'S A CC ON SOMEBODY ELSE'S E-MAIL. MR. TUBACH: IT MADE ENOUGH SENSE, YOUR HONOR, THAT 4 THE PLAINTIFFS AGREED TO IT, AND ALL I'M ASKING IS THAT THEY 5 SEND US A LETTER AND GIVE US A CHANCE TO LOOK AT THE E-MAIL 6 AGAIN. 7 BEFORE A CLASS CERTIFICATION HEARING. 8 SHOULD HAVE THIS RESOLVED HERE TODAY. 9 WE HEARD ABOUT THIS LITERALLY TWO DAYS AGO, TWO DAYS MR. SAVERI: I DON'T BELIEVE WE YOUR HONOR, I AM HAPPY TO SEND 10 MR. TUBACH A LETTER, BUT IT'S GOING TO COME AS NO SURPRISE 11 BECAUSE IT'S GOING TO REPEAT BASICALLY WHAT YOUR HONOR JUST 12 SAID TO HIM. 13 BUT IF -- I'M WILLING TO DO THAT. 14 MR. TUBACH: AND WE'LL TAKE AN IMMEDIATE AND CLOSE 15 LOOK AT WHAT THEY SAY AND RESPOND RIGHT AWAY. 16 TO SLOW DOWN -- 17 THE COURT: WHICH IS TO DO WHAT? WE'RE NOT TRYING YOU'VE ONLY 18 POINTED TO ONE E-MAIL THAT MR. TUBACH HAS SENT. 19 ENOUGH. 20 MR. TUBACH: 21 THE COURT: THAT'S NOT I'M MR. TUBACH. SHOW ME, WHAT, 10, 25, 30, 75, A 22 THOUSAND TO SHOW THAT HE'S RELEVANT? 23 STANDARD HERE? 24 SAYING, "CAN WE POACH FROM GOOGLE?" 25 I MEAN, WHAT'S THE THEY HAVE A DOCUMENT FROM HIM TO STEVE JOBS MR. TUBACH: IF THAT'S ALL IT IS -- UNITED STATES COURT REPORTERS 283 122 1 THE COURT: 2 MR. TUBACH: 3 THE COURT: 4 ADMISSIBLE EVIDENCE? 5 6 7 8 9 THAT'S NOT RELEVANT? IF THAT -THAT'S NOT GOING TO LEAD TO RELEVANT, MR. TUBACH: IF THAT'S ALL IT IS AND THERE'S NO RESPONSE, PROBABLY NOT. PROBABLY NOT. IF THERE'S MORE, WE'LL LOOK INTO IT, AND WE'LL LOOK INTO IT IMMEDIATELY. ALL I'M ASKING FOR IS AN OPPORTUNITY. THE COURT: OKAY. BUT YOU'RE SAYING, "WE'RE NOT 10 WILLING TO PRODUCE HIS DOCUMENTS UNTIL THEY SHOW US ENOUGH OF 11 HIS DOCUMENTS TO MAKE US HAVE TO DO A COLLECTION." 12 MR. TUBACH: 13 THE COURT: 14 THAT'S NOT WHAT I'M SAYING, YOUR HONOR. DOES THAT MAKE SENSE? THAT'S WHAT YOU'RE SAYING. 15 MR. TUBACH: 16 THE COURT: NO. YOU'RE SAYING, "THEY NEED TO POINT TO 17 ENOUGH OF HIS DOCUMENTS FOR US TO CONCEDE THAT HIS DOCUMENTS 18 ARE RELEVANT." 19 TO A SINGLE DOCUMENT OF HIS TO SHOW THAT HE'S RELEVANT AND, 20 THEREFORE, WE SHOULD DO A COLLECTION OF THIS PERSON'S 21 DOCUMENTS." 22 23 THAT'S YOUR ARGUMENT. "THEY'RE ONLY POINTING THAT MAKES NO SENSE TO ME. MR. TUBACH: I'M NOT SAYING THEY HAVE TO POINT TO 24 MORE THAN ONE DOCUMENT FOR US TO CHANGE OUR MIND. 25 TAKE A LOOK AT THE DOCUMENT. UNITED STATES COURT REPORTERS I WANT TO 284 123 1 THE COURT: 2 MR. TUBACH: 3 4 5 6 OKAY. OBVIOUSLY THE COURT MAY NOT BE PERSUADED. THE PLAINTIFFS WERE PERSUADED BY THE ARGUMENT AND DROPPED HIM TWO MONTHS AGO. SO ALL I WANT TO DO IS TAKE -- WE MAY CHANGE OUR MINDS. 7 WE'VE NOW PRODUCED MORE DOCUMENTS. 8 WE'LL TALK TO PEOPLE. 9 WE'LL LOOK THROUGH THOSE. WE MAY CHANGE OUR MINDS. I'M NOT PUTTING A NUMERIC NUMBER ON HOW MANY E-MAILS HAVE 10 TO BE FROM A PARTICULAR WITNESS BEFORE HE'S A CUSTODIAN. 11 I'M ASKING FOR IS AN OPPORTUNITY TO TAKE A LOOK AT IT, AND 12 WE'LL RESPOND IMMEDIATELY. 13 ALL AND I APPRECIATE MR. SAVERI'S OFFER TO WRITE A LETTER, AND 14 WE'LL RESPOND TO IT IMMEDIATELY. 15 THE COURT: 16 ALL RIGHT. TOMORROW, JANUARY 18TH. 17 MR. TUBACH: 18 THE COURT: 19 MR. TUBACH: 20 THE COURT: 21 THAT LETTER IS GOING OUT ALL RIGHT. THANK YOU. WHEN IS YOUR RESPONSE COMING IN? WE CAN RESPOND BY TUESDAY, THE 22ND. ALL RIGHT. JANUARY 22ND. AND I WANT A STATUS REPORT, YOU ALL FILE A 22 STATUS REPORT BY THURSDAY, THE 24TH, AS TO WHAT'S GOING ON WITH 23 MR. FADELL'S DOCUMENTS. 24 THINK THEY SHOULD BE PRODUCED, SO I HOPE THAT YOU REACH A 25 SUITABLE AGREEMENT. I FIND THAT THEY'RE RELEVANT AND I UNITED STATES COURT REPORTERS 285 124 1 2 3 4 MR. SAVERI: I DON'T WANT TO PROMISE, BUT I'LL TRY TO GET THE LETTER TONIGHT. THE COURT: I'LL GO BACK AND WRITE A LETTER. WHAT ELSE? I'M TRYING TO BE VERY CLEAR, EVERY TIME WE HAVE A CMC, PLEASE, LET'S NOT HAVE THESE ISSUES. 5 MR. SAVERI: 6 THE COURT: YOUR HONOR -I HAMMERED THE PLAINTIFFS WHEN THEY 7 WEREN'T BEING TIMELY WITH THEIR PRODUCTION. 8 IT'S ALL EQUAL OPPORTUNITY HAMMERING. 9 GET THIS CASE RESOLVED. YOU KNOW, IF -- I MEAN, WE NEED TO JUST WE'RE COMING UP AGAINST THE FACT 10 DISCOVERY CUT OFF DATE AND WE JUST NEED THESE ISSUES TO MOVE 11 FORWARD AND THIS CASE TO PROGRESS TO THE MERITS. 12 13 14 15 SO ANYWAY, IS THERE ANY OTHER DISPUTE AS TO APPLE CUSTODIANS OF RECORD? MS. DERMODY: NO, YOUR HONOR, NOT THAT I'M AWARE OF. BUT I WANTED JUST TO GO BACK TO -- ON GOOGLE, WE TALKED 16 ABOUT THE DOCUMENTS, AND I THINK THAT WHAT THAT ALSO HIGHLIGHTS 17 IS THAT THERE IS LIKELY GOING TO NEED TO BE A DISCUSSION ABOUT 18 DEPOSITION DATES FOR CUSTODIANS, AND WE WANTED TO GET AN 19 AGREEMENT WITH GOOGLE ON A DATE CERTAIN WHEN THEY WILL GIVE US 20 THOSE DATES. 21 PROBABLY FOR LARRY PAGE AND MR. BRIN, WE WILL HAVE TO DO 22 DEPOSITIONS IN MARCH GIVEN THE PRODUCTION TIMEFRAME WE'RE 23 TALKING ABOUT. 24 BUT WE WANT TO MAKE SURE WE START TALKING ABOUT SCHEDULES 25 BECAUSE IT'S BEEN VERY HARD TO SCHEDULE THE SENIOR EXECUTIVES. UNITED STATES COURT REPORTERS 286 125 1 THE COURT: NOW, THAT'S ONLY IF YOU FIND RELEVANT 2 DOCUMENTS WITHIN THEIR PRODUCTION. 3 MS. DERMODY: 4 THE COURT: YES. I CERTAINLY DON'T WANT HARASSMENT 5 DEPOSITIONS JUST TO TIE UP A TOP EXECUTIVE'S TIME AND BURDEN 6 THEM. 7 MS. DERMODY: 8 TO MAKE SURE WE GET -- 9 MR. RUBIN: ABSOLUTELY, YOUR HONOR. WE JUST WANT YOUR HONOR, WE'RE CERTAINLY HAPPY TO 10 TALK TO THEM AS SOON AS -- AFTER THEY GET THE DOCUMENTS. 11 THINK WE'RE ALWAYS WILLING TO TAKE ANYBODY'S CALL FROM 12 LIEFF CABRASER. 13 WE'RE ALWAYS AVAILABLE. I WE WILL TALK TO THEM. AS SOON AS THEY LOOK AT DOCUMENTS AND THEY WANT TO TALK 14 ABOUT THE NEED FOR A DEPOSITION AND WHY, WE'LL RESPOND 15 PROMPTLY. 16 BUT I AGREE WITH YOUR HONOR THAT WE'RE NOT QUITE THERE 17 YET. 18 WE'RE NOT QUITE THERE YET TO TALK ABOUT THOSE DATES. 19 I KNOW THAT MS. DERMODY IS LAYING DOWN A MARKER, BUT THE COURT: ALL RIGHT. 20 REASONABLE ABOUT THIS. 21 MS. DERMODY: 22 THE COURT: WELL, PLEASE, EVERYONE BE 23 24 25 THANK YOU, YOUR HONOR. ALL RIGHT. SO LET'S FIGURE OUT WHEN WE SHOULD GET TOGETHER AGAIN FOR A CASE MANAGEMENT CONFERENCE. I THINK WE SHOULD PROBABLY DO ONE IN MARCH OR EARLY APRIL, BUT I WOULD LIKE TO HEAR FROM THE PARTIES OF WHEN MAKES SENSE. UNITED STATES COURT REPORTERS 287 126 1 2 MR. MITTELSTAEDT: ANY DATE IS FINE WITH US, YOUR HONOR. 3 MS. DERMODY: 4 OFF MIGHT MAKE SENSE, YOUR HONOR. 5 PROBLEM MEETING IT, BUT IT MIGHT BE GOOD TO CHECK IN WITH THE 6 COURT. 7 I THINK MARCH BEFORE THE DISCOVERY CUT MR. MITTELSTAEDT: WE EXPECT THERE WILL BE NO YOUR HONOR, WOULD IT BE OKAY FOR 8 THE PARTIES TO MEET AND CONFER AND AGREE ON A COUPLE OF DATES 9 IN MARCH AND CHECK WITH YOUR STAFF TO SEE IF THAT'S ACCEPTABLE 10 WITH THE COURT? 11 12 13 THE COURT: THAT'S FINE. BUT CAN WE NOT DO THAT TODAY? MR. SAVERI: I'M HAPPY TO TALK TO MR. MITTELSTAEDT, 14 BUT IT SEEMS TO ME THAT WE'RE MORE THAN LIKELY TO HAVE DATES 15 THAT WE CAN AGREE ON AND KEEP IF WE DO IT RIGHT NOW. 16 MR. MITTELSTAEDT: 17 TIME, BUT EITHER WAY IS FINE WITH US. 18 19 20 21 22 23 24 25 THE COURT: OKAY. I JUST THOUGHT IT WOULD SAVE SOME I JUST DON'T WANT TO HAVE A LOT OF LOOSE ENDS. SO WHAT DATES DO WE HAVE IN MARCH? THE CLERK: JUST FROM OUR CALENDAR, IT LOOKS AS THOUGH THE 20TH WOULD BE THE BEST. THE COURT: OKAY. WHAT ABOUT MARCH 20TH? I GUESS IT'LL BE WEDNESDAY AT 2:00 O'CLOCK. THE CLERK: OR THE 6TH ALSO WOULD WORK. UNITED STATES COURT REPORTERS 288 127 1 THE COURT: LET'S DO IT THE 20TH. 2 MS. DERMODY: IS IT POSSIBLE, YOUR HONOR, TO DO IT 3 THE WEEK BEFORE THAT? 4 THE COURT: I THINK THE 13TH MIGHT BE LONG. 5 THE CLERK: THE 13TH WE HAVE SIX. 6 THE 6TH WE ONLY HAVE THREE. 7 MS. DERMODY: 8 THE COURT: 9 10 11 IS THE 6TH IS NOT -- BUT IS ONE OF THEM THE PRETRIAL CONFERENCE -THE CLERK: NO. THREE J & J CASES. HOW THAT HAPPENED. 12 MS. DERMODY: 13 THE COURT: 14 I DON'T HAVE A TRIAL SET THEN. 15 THE CLERK: 16 17 I DON'T KNOW DO YOU DO MONDAYS, YOUR HONOR? I WOULD BE HAPPY TO SPECIALLY SET IT IF I JUST DON'T KNOW. LET ME SEE. ALL THE MONDAYS IN MARCH WE CURRENTLY HAVE TRIALS SET. THE COURT: YEAH. OKAY. I'D BE RELUCTANT TO 18 SPECIALLY SET IT BECAUSE I DO HAVE A CIVIL RIGHTS CASE THAT MAY 19 GO ON MARCH 4, SO -- YOU KNOW, WE COULD ADD IT TO THE 13TH. 20 THE CLERK: WE HAVE NOTHING ON THE 22ND. 21 THE COURT: WE DON'T HAVE ANYTHING ON THE 22ND? 22 THE CLERK: THAT'S BETWEEN SMITH AND FERRETTI. 23 MS. DERMODY: 24 25 THE 13TH WOULD BE BETTER FOR ME, BUT I CAN MAKE THE 22ND. MR. MITTELSTAEDT: I'M TOLD THE 22ND ISN'T GOOD FOR UNITED STATES COURT REPORTERS 289 128 1 US, EITHER. 2 THE COURT: 3 MR. MITTELSTAEDT: 4 THE COURT: 5 MR. MITTELSTAEDT: 6 THE COURT: THAT RIGHT? 9 10 11 IS NOT. IS THE 13TH GOOD FOR THE DEFENDANTS? I SUSPECT WE CAN GET A REPRESENTATIVE FROM EACH COMPANY HERE ON THE 13TH. 7 8 IS NOT GOOD? OTHERWISE YOU CAN'T DO THE 20TH? IS SOMEBODY CAN'T DO THE 20TH? MS. DERMODY: YES, THAT'S ME, YOUR HONOR. I'M SORRY. THE COURT: ALL RIGHT. 12 YEAH, ON THE 13TH. 13 LET'S DO IT ON THE 13TH. 13TH OF 2013 AT 2:00 O'CLOCK. 14 SO THE NEXT CMC IS GOING TO BE MARCH THE LET ME ASK A COUPLE OF QUESTIONS ON THE MOTION TO STRIKE 15 AND I'LL TRY TO WRAP THIS UP. 16 TAKING A LONG TIME. 17 I APOLOGIZE THE HEARING IS DID MR. MURPHY OR ANY OF HIS TEAM RELY ON THE INTERVIEW 18 NOTES WHEN FORMING THE OPINIONS ABOUT WHICH DR. MURPHY WROTE, 19 TESTIFIED, FORMED? 20 21 MR. HINMAN: YOUR HONOR, FRANK HINMAN. THE ANSWER TO THAT IS NO. 22 THE COURT: 23 MR. HINMAN: 24 THE COURT: 25 MR. HINMAN: NOT AT ALL? CORRECT, YOUR HONOR. ALL RIGHT. MR. MURPHY DIDN'T TAKE ANY NOTES, SO HE UNITED STATES COURT REPORTERS 290 129 1 DIDN'T HAVE ANY OF HIS OWN TO RELY ON, NOR DID HE RELY ON ANY 2 NOTES THAT ANYBODY ELSE MAY HAVE TAKEN. 3 MR. GLACKIN: 4 THE COURT: SO THE ANSWER IS NO. BUT THE -- BUT WHAT ABOUT -- WHO WROTE HIS REPORT? 5 I ASSUME SOME MEMBERS OF HIS TEAM HELPED HIM IN DRAFTING HIS 6 REPORT AND FORMING HIS OPINIONS. THAT'S USUALLY WHAT HAPPENS. 7 DID THAT NOT HAPPEN IN THIS CASE? HE WROTE IT HIMSELF, ALL 70 8 PAGES? 9 10 MR. HINMAN: HAPPEN. NO, YOUR HONOR. IT ABSOLUTELY DID THERE WAS A DRAFTING PROCESS, AS THERE OFTEN IS. 11 THE COURT: 12 MR. HINMAN: OKAY. BUT THE FINAL REPORT, THE NOTES WERE 13 NOT RELIED UPON IN FORMING THE OPINIONS THAT ARE EXPRESSED IN 14 THE FINAL REPORT. 15 16 17 AND SO, YOU KNOW, NOT ONLY -- I MEAN, PUTTING ASIDE THE USUAL -THE COURT: OKAY. I'M SORRY TO INTERRUPT YOU. LET 18 ME ASK, DID THE PEOPLE WHO WORKED ON THE TEAM THAT DRAFTED THE 19 REPORT, DID THEY DRAFT INTERVIEW NOTES? 20 MR. HINMAN: YES. 21 THE COURT: OKAY. 22 MR. HINMAN: THEY DID. 23 THE COURT: ALL RIGHT. 24 MR. HINMAN: 25 BUT THEY WERE NOT -- AS I SAY, THEY WERE NOT USED BY HIM OR ANYBODY ELSE IN FORMING THE OPINIONS UNITED STATES COURT REPORTERS 291 130 1 THAT ARE CONTAINED IN THE REPORT. 2 AND WE HAVE A STIPULATION IN THIS CASE, YOUR HONOR, 3 THAT'S, I THINK, VERY CLEAR THAT WAS, YOU KNOW -- I MEAN, IT'S 4 NOT UNCOMMON IN THESE ANTITRUST CASES WITH LOTS OF EXPERTS ON 5 BOTH SIDES AND THINGS LIKE THIS THAT WE'RE NOT GOING TO ALLOW 6 DISCOVERY INTO, YOU KNOW, THIS SORT OF PRELIMINARY WORK PRODUCT 7 AND NOTES THAT PEOPLE MAY HAVE TAKEN, ET CETERA. 8 9 AND SO EVEN PUTTING ASIDE -- AND I'M NOT PUTTING IT ASIDE EXCEPT FOR THE MOVEMENT -- ISSUES OF WORK PRODUCT, THE 10 STIPULATION GOES BEYOND THAT. 11 SUPERSEDES ANY RULE OF CIVIL PROCEDURE THAT MIGHT APPLY. 12 IT EXPLICITLY SAYS THAT IT I DON'T THINK THAT THESE NOTES ARE PRODUCEABLE EVEN UNDER 13 THOSE RULES, BUT THE STIPULATION SAYS IT'S BROADER AND IT IS 14 INTENDED TO AND DOES CARVE OUT ALL OF THIS KIND OF PRELIMINARY 15 WORK PRODUCT. 16 AND IF THERE'S -- THERE REALLY, I THINK, SHOULDN'T BE ANY 17 DISPUTE ABOUT THAT BECAUSE JUST, FOR EXAMPLE, IN THE INSTANCE 18 OF PROFESSOR LEAMER'S DEPOSITION -- AND IT WASN'T THE ONLY 19 INSTANCE -- THAT MR. MITTELSTAEDT REFERRED TO EARLIER, 20 DR. LEAMER WAS INSTRUCTED NOT TO TESTIFY ABOUT, NOT TO DISCLOSE 21 PRELIMINARY WORK PRODUCT THAT HE HAD DONE THAT, INDEED, HE DID 22 RELY ON, THAT HE DID RELY ON IN ORDER TO -- THIS IS THE 23 SENSITIVITY ANALYSIS. 24 25 HE DID IT, HE RELIED UPON IT TO DECIDE AND CONCLUDE THAT THE AGGREGATED, I'LL CALL IT, REGRESSION MODEL THAT HE OFFERED UNITED STATES COURT REPORTERS 292 131 1 WAS SUFFICIENT AND THAT THE DISAGGREGATED SENSITIVITY TEST THAT 2 HE RAN DIDN'T TELL HIM ANYTHING TO THE CONTRARY AS MR. GLACKIN, 3 I THINK, SAID. 4 SO, I MEAN, THIS IS JUST -- THIS IS JUST NOT THE SORT OF 5 THING THAT I THINK ANYBODY CONTEMPLATED WOULD BE PRODUCED, AND 6 I THINK THAT BOTH SIDES ARE READING IT IN JUST THAT WAY. 7 MR. GLACKIN: WELL, SO FIRST OF ALL, I STILL DON'T 8 THINK YOU HAVE A STRAIGHT ANSWER TO YOUR QUESTION, WHICH IS, 9 DID ANYBODY WHO HELPED WRITE THIS REPORT LOOK AT THE NOTES WHEN 10 11 THEY WERE DOING IT? WHAT MR. HINMAN SAID WAS THE NOTES WERE NOT RELIED ON IN 12 FORMING THE OPINIONS, AND I DON'T KNOW WHAT THAT MEANS. 13 THINK YOU ASKED A STRAIGHTFORWARD QUESTION, AND I DIDN'T HEAR 14 AN ANSWER. 15 I SECOND, I THINK TRYING TO BRING UP WHAT WE DID IS 16 COMPLETELY INAPPROPRIATE WITH DR. LEAMER. 17 WHAT WE DID WITH DR. LEAMER FOR MONTHS. 18 WRONG ABOUT WHAT WE DID, THEY'VE HAD EVERY OPPORTUNITY TO RAISE 19 THAT AND ASK FOR THE STUFF AND MOVE ON IT IF THEY DISAGREED 20 WITH US. 21 SO WE'VE ABIDED BY THE STIPULATION. THEY'VE KNOWN ABOUT IF THERE WAS ANYTHING THE STIPULATION SAYS 22 PRELIMINARY DATA ANALYSIS IS NOT PRODUCEABLE. 23 WE DIDN'T PRODUCE PRELIMINARY DATA ANALYSIS. 24 BUT EVEN BEYOND THE STIPULATION, DR. MURPHY HAS AN 25 OBLIGATION, OR I SHOULD SAY THE DEFENDANTS HAVE AN OBLIGATION, UNITED STATES COURT REPORTERS 293 132 1 2 TO TELL US THE FACTS ON WHICH HE'S RELYING TO FORM HIS OPINION. THEY CAN DO THAT A LOT OF DIFFERENT WAYS. IF YOU -- IN 3 THE CASE OF THESE INTERVIEWS, ONE WAY THEY COULD DO IT WOULD 4 HAVE BEEN TO RECORD THE INTERVIEWS AND GIVE US THE RECORDINGS. 5 ANOTHER WAY THEY COULD DO IT -- 6 THE COURT: 7 MR. GLACKIN: 8 9 THAT'S NOT GOING TO HAPPEN. WELL, THEY WEREN'T RECORDED, SO IT'S NOT HAPPENING. ANOTHER WAY THEY COULD DO IT IS THEY COULD WRITE SUMMARIES 10 UP AT THE TIME AND GIVE US THE SUMMARIES THAT JUST SAID 11 "MR. SO-AND-SO SAID THIS, THAT, AND THE OTHER THING." 12 ANOTHER WAY THEY COULD DO IT IS THEY COULD PRODUCE 13 DR. MURPHY AND HE COULD TESTIFY FROM HIS MEMORY ABOUT WHAT 14 HAPPENED AT THE INTERVIEWS. 15 BUT THEY HAVE AN AFFIRMATIVE DUTY, UNDER RULE 26, TO TELL 16 US THIS INFORMATION, AND WHEN I ASKED DR. MURPHY ABOUT THIS AT 17 HIS DEPOSITION -- I'M GOING TOO FAST, I APOLOGIZE -- OVER AND 18 OVER AND OVER AGAIN HE SAID HE COULDN'T REMEMBER WHAT HAD BEEN 19 SAID OR WHO HAD TOLD IT TO HIM. 20 IMPRESSION FROM THESE INTERVIEWS HE'D DONE THAT THESE FOLLOWING 21 THINGS WERE TRUE ABOUT ALL THESE COMPANIES. 22 HE JUST HAD THIS GENERAL AND HE SPECIFICALLY TESTIFIED, I BELIEVE, THAT 23 MR. VIJUNGCO HAD TOLD HIM THINGS IN HIS INTERVIEW THAT WERE 24 DIFFERENT THAN WHAT MR. VIJUNGCO HAD TOLD DR. MURPHY -- OR THAT 25 WERE DIFFERENT THAN WHAT MR. VIJUNGCO SAID IN HIS DECLARATION. UNITED STATES COURT REPORTERS 294 133 1 AND SO THE OBLIGATION, IF THEY WANT TO HAVE AN EXPERT, IS 2 ON THEM TO PRODUCE THE MATERIAL ON WHICH HE'S RELIED, AND THIS 3 IDEA THAT THEY'RE GOING TO TAKE SECRET INTERVIEWS AND HAVE THEM 4 BE A BASIS FOR THE EXPERT'S OPINION IN SUCH A WAY THAT THAT 5 OPINION CANNOT ADEQUATELY BE TESTED, I REALLY HAVE A PROBLEM 6 WITH THAT. 7 THE COURT: SO WHAT IS YOUR BEST AUTHORITY FOR THE 8 PROPOSITION THAT MS. DERMODY MADE THAT IF A PARTY LISTS A 9 WITNESS ON THEIR RULE 26 DISCLOSURES, THAT AUTOMATICALLY MAKES 10 THEM A CUSTODIAN FOR WHOM THEY HAVE TO COLLECT DOCUMENTS AND 11 PRODUCE DOCUMENTS? 12 13 MR. GLACKIN: POINT? 14 THE COURT: 15 MR. GLACKIN: 16 WHAT'S OUR BEST AUTHORITY FOR THAT YEAH. I'M NOT AWARE OF ANY CASE AUTHORITY FOR THAT POINT OFFHAND, YOUR HONOR. 17 I MEAN, MY AUTHORITY FOR THAT POINT, I GUESS, WOULD BE 18 RULE 26 WHICH SAYS THAT YOU'RE REQUIRED TO IDENTIFY PEOPLE WITH 19 RELEVANT INFORMATION. 20 AND IF YOU'VE GONE SO FAR AS TO IDENTIFY A PERSON WITH 21 RELEVANT INFORMATION, IT SEEMS TO ME, PRACTICALLY SPEAKING, 22 THAT THEIR DOCUMENTS -- TO IMPLY THEIR DOCUMENTS ARE RELEVANT 23 IN THIS DAY AND AGE WHEN VIRTUALLY -- WHEN SO MUCH 24 COMMUNICATION NOW OCCURS ELECTRONICALLY, I WOULD SAY. 25 MR. MITTELSTAEDT: BUT, YOUR HONOR, ON THAT POINT, UNITED STATES COURT REPORTERS 295 134 1 THEY HAVE KNOWN WHO'S ON THE INITIAL DISCLOSURES AND THEY HAVE 2 KNOWN WHO THE CUSTODIANS ARE. 3 WE'VE TALKED ABOUT THAT. 4 THAT -- WE'VE NEGOTIATED THAT. SO IF THEIR POSITION WAS THAT IF YOU PUT SOMEBODY ON AN 5 INITIAL DISCLOSURE, AUTOMATICALLY THEY'RE A CUSTODIAN, THEY'VE 6 BEEN SITTING IN THE WEEDS ON THAT. 7 THAT'S AN AMBUSH. SO THAT ISN'T -- AND I -- IF THEY'RE SAYING THAT, THAT 8 CAN'T BE RIGHT. 9 WHEN WE PUT PEOPLE ON THE INITIAL DISCLOSURES AND THEY KNEW 10 11 THE TIME TO TALK TO US ABOUT THAT WAS LONG AGO THEY WEREN'T CUSTODIANS. SO THAT -- BUT -- YOUR HONOR, I KNOW THE HOUR IS LATE, BUT 12 GIVEN THE IMPORTANCE OF THE CLASS MOTION, COULD I BE HEARD FOR 13 TWO MINUTES? 14 THE COURT: 15 MR. MITTELSTAEDT: 16 MR. GLACKIN: 17 18 JUST TWO MINUTES. I WILL TALK FAST. CAN I GET TWO MINUTES, TOO, AFTER HE'S DONE? MR. MITTELSTAEDT: TO HELP YOUR HONOR WALK THROUGH 19 THE BOOKLET THAT I GAVE YOU, I WOULD SUGGEST LOOKING AT PAGE 20 25, WHICH HAS THE ANSWER TO YOUR HONOR'S QUESTION TO THE OTHER 21 SIDE AS TO WHETHER FIGURES 11 TO 14 ARE CORRELATED OVER TIME. 22 THAT'S A DEPOSITION ADMISSION THAT THEY ARE NOT CORRELATED. 23 PAGE 28 TO 31 SHOWS THAT THE CHARTS ARE NOT 24 REPRESENTATIVE. YOUR HONOR ASKED THE QUESTION, ARE THE CHARTS 25 REPRESENTATIVE? THE DEPOSITIONS AT PAGE 28 THROUGH 31 OF TAB 6 UNITED STATES COURT REPORTERS 296 135 1 GIVE MR. LEAMER'S ANSWER WHERE HE ADMITS THEY ARE NOT 2 REPRESENTATIVE. 3 PAGE 32 SHOWS THAT BECAUSE THOSE CHARTS ARE JUST AVERAGES, 4 THEY WOULD BE CONSISTENT WITH A NON-RIGID STRUCTURE, AS WELL AS 5 A RIGID STRUCTURE, AND THEREFORE, THEY DO NOT PROVE A RIGID 6 STRUCTURE, WHICH IS WHAT LEAMER SETS OUT TO DO IN HIS STEP 2. 7 HIS FIRST STEP IS TO SHOW AN AVERAGE OVERCHARGE. 8 SECOND STEP IS TO TRY AND SHOW THAT THERE WOULD HAVE BEEN A 9 SPREAD TO ALL OR NEARLY ALL OF THE EMPLOYEES. 10 THE COURT: 11 MR. MITTELSTAEDT: HIS UM-HUM. AND HE TOLD US THAT FIGURES 11 12 THROUGH 14 DID NOT DO THE TRICK BECAUSE THEY DID NOT SHOW 13 CORRELATION OVER TIME. 14 17." 15 HE SAID, "THAT'S WHY I NEED 15 THROUGH BUT WHEN WE GOT TO 15 TO 17, HE ADMITTED -- THIS IS AT 16 PAGE 32 IN THE BINDER -- THAT THEY WOULD BE CONSISTENT WITH A 17 NON-RIGID SYSTEM, MEANING THAT THEY DON'T SHOW RIGIDITY. 18 PAGE 28 IN THE BINDER, TAB 6, IS A DOCUMENT THEY OBJECT 19 TO, BUT WHAT IT SHOWS IS IF YOU TAKE THE INTEL JOB THAT THEY 20 CHERRY PICKED, FINANCIAL ANALYST 3 -- 21 MR. GLACKIN: I'M SORRY. 22 THE COURT: 23 MR. GLACKIN: 24 MR. MITTELSTAEDT: 25 THE COURT: WHICH PAGE ARE YOU ON? PAGE 28 OF TAB 6. OKAY. I'M SORRY, 37. OKAY. UNITED STATES COURT REPORTERS 297 136 1 MR. MITTELSTAEDT: THIS IS A CHART OF THE 2 COMPENSATION GROWTH FOR NINE INTEL EMPLOYEES WHO HOLD THE SAME 3 SMALL SLIVER OF A JOB, FINANCIAL ANALYST 3. 4 GENDER, THEY'RE THE SAME AGE, AND THEY HAVE THE SAME WORK 5 EXPERIENCE. 6 MR. GLACKIN: THEY ARE THE SAME I JUST WANT TO -- I APOLOGIZE FOR 7 INTERRUPTING, BUT I WANT TO POINT OUT THAT THIS IS YET ANOTHER 8 REHASHING OF THE SUPPLEMENTAL DATA THAT THE DEFENDANTS HAVE 9 MOVED TO HAVE, WE SAY IMPROPERLY, CONSIDERED BY THE COURT, AND 10 I COMPLETELY -- I -- WE HAVE NOT HAD THE OPPORTUNITY TO 11 VENTILATE IT WITH OUR EXPERTS. 12 13 I HAVE NO IDEA IF IT'S ACCURATE. TIME LAST NIGHT AT ABOUT 7:00 OR 8:00 O'CLOCK. 14 15 I SAW THIS FOR THE FIRST MR. MITTELSTAEDT: SO IT'S JUST -- YOUR HONOR, LET ME FINISH IF I COULD? 16 MR. GLACKIN: I'M SORRY. 17 MR. MITTELSTAEDT: YOUR HONOR, TAB -- OR PAGE 33 IS 18 THE LETTER THEY SENT TO THE COURT CORRECTING A STATEMENT THEY 19 HAD MADE IN THEIR BRIEF AND THAT DR. LEAMER HAD SAID IN HIS 20 BRIEF. 21 THEIR POINT WAS THE ORIGINAL SAID THAT THERE WERE ONLY 22 SEVEN INTEL GRADE 3 EMPLOYEES WHO HELD THAT TITLE, SAME OTHER 23 CHARACTERISTICS, AND THAT THE AVERAGE -- OR THAT THE DIFFERENCE 24 BETWEEN THE HIGHEST AND THE LOWEST PAID WAS ONLY $300. 25 AND THEY CITED THAT AS AN EXAMPLE OF SOMETHING SHOWING UNITED STATES COURT REPORTERS 298 137 1 THAT THERE IS NO VARIATION IN PAY AND, THEREFORE, A RAISE FOR 2 ONE WOULD BE A RAISE FOR EVERYBODY BECAUSE THEY WOULD ALL GO UP 3 TOGETHER. 4 THEY DID NOT SUBMIT THE DATA. BUT THEY LOOKED AT THE DATA AFTER SUBMITTING THEIR REPLY 5 AND WHAT THEY REALIZED WAS, ACTUALLY, THERE ARE 28 PEOPLE THAT 6 SHARE THOSE VERY NARROW CHARACTERISTICS, AND THE RANGE OF 7 SALARY WAS NOT 300, IT WAS 5300. 8 WHAT WE DID WITH DR. MURPHY WAS TO ACTUALLY SUBMIT THE 9 DATA, AND THEN WE CHARTED THE DATA, AND WHAT THE DATA SHOWS 10 IS -- THE FIRST CHART, 36, SHOWS ALL 28 OF THEM, AND YOU'LL SEE 11 THE LINES CROSSING. 12 AND THE IMPORTANT THING TO REMEMBER IN REVIEWING THESE 13 CHARTS IS WHEN THE LINES CROSS, THAT MEANS PEOPLE ARE NOT 14 MOVING THE SAME. 15 AND THEN THEY SAID, "WELL, 28 IS TOO MANY BECAUSE SOME OF 16 THOSE PEOPLE WERE PROMOTED TO DIFFERENT JOBS," AND WE SAID, 17 "EXACTLY. 18 PEOPLE ARE TREATED DIFFERENTLY. THAT'S OUR POINT." BUT WE SAID WE'LL JUST TAKE THE NINE PEOPLE WHO HELD THE 19 SAME JOB, STILL THEY WERE THE SAME GENDER, STILL THE SAME AGE, 20 STILL THE SAME TENURE, FOR THREE YEARS AND LOOK AT THAT VERY 21 SMALL SLICE, AND WHAT YOU SEE IS LINES CROSSING. 22 SOME PEOPLE GO UP, SOME PEOPLE GO DOWN. 23 24 25 PEOPLE -- AND, YOUR HONOR, WE'RE TALKING ABOUT WITHIN THE SAME VERY, VERY SMALL SLICE OF JOB CONTROLLED FOR THE OTHER FACTORS. THAT SINGLE DOCUMENT, YOUR HONOR, SHOWS THAT THEIR IDEA OF UNITED STATES COURT REPORTERS 299 138 1 A RIGID PAY STRUCTURE, WHATEVER IS IN THE DOCUMENTS, IS NOT 2 TRUE. 3 4 5 ON -- OKAY. SO THAT'S WALKING YOUR HONOR QUICKLY THROUGH THOSE. ON THE DOCUMENTS, I WOULD ASK YOUR HONOR TO TAKE A LOOK AT 6 SHAVER EXHIBIT 59 AND HARVEY EXHIBIT 30. 7 DOCUMENTS YOUR HONOR ASKED ME ABOUT WHEN I SAID THAT I THINK 8 THEY SHOW THE INDIVIDUALIZED NATURE OF THE IMPACT. 9 THOSE ARE TWO OF THE THEY ALSO, I THINK, READ CLOSELY SHOW THE OPPOSITE OF A 10 RIGID STRUCTURE. 11 DOCUMENT, THE OCTOBER 7TH ONE, IT SHOWS THAT GOOGLE WAS MAKING 12 COUNTEROFFERS TO PEOPLE AND THAT CAUSED WHAT THEY CALL 13 DISCONTINUITY AND UNFAIR BUMPS. 14 THE GOOGLE DOCUMENT, WHEN YOU READ THE FIRST THE MERITS OF THESE AGREEMENTS ASIDE, YOUR HONOR, WE'RE 15 NOT HERE TO TALK ABOUT THOSE, WHAT WE'RE HERE TO TALK ABOUT IS, 16 WHO WAS IMPACTED? 17 AND WHAT THIS DOCUMENT SHOWS IS AS OF OCTOBER 2010, 18 GOOGLE'S POLICY WAS TO MAKE COUNTEROFFERS TO SOME PEOPLE, BUT 19 NOT TO ADJUST EVERYBODY ELSE. 20 THAT IS THE OPPOSITE OF THEIR RIGID PAY STRUCTURE. 21 IT MEANS IS THAT TO FIGURE OUT IF SOMEBODY IS IMPACTED, YOU 22 NEED TO GO PERSON BY PERSON, JUST AS IN REED, JUST AS IN 23 JOHNSON. 24 25 WHAT THE OTHER POINT -- YOU ASKED HIM ABOUT LCD AND JUDGE ILLSTON'S OPINION. I ASK YOUR HONOR TO KEEP IN MIND, IN UNITED STATES COURT REPORTERS 300 139 1 REVIEWING THIS, THAT THE DIFFERENCE BETWEEN LCD AND THE JOHNSON 2 AND REED LINE OF CASES -- WHICH LCD IS A TRADITIONAL ANTITRUST 3 CASE. IT'S PRICE FIXING OF A COMMODITY. 4 AND IF THE DEFENDANTS FIXED THE PRICE OF A COMMODITY, 5 CHANCES ARE EVERYBODY -- AND IF THEY SELL THE COMMODITY FOR ONE 6 PRICE, YOU SHOW IMPACT ON ONE, YOU'VE GOT IMPACT ON EVERYBODY, 7 AND THAT'S WHY COURTS OFTEN, IN TRADITIONAL PRICE FIXING CASES 8 FOR COMMODITIES, FUNGIBLE COMMODITIES, CERTIFY A CLASS AND FIND 9 THAT IMPACT IS NOT HIGHLY INDIVIDUALIZED. 10 WE'RE NOT DEALING WITH COMMODITIES. WE'RE DEALING WITH 11 HUMAN BEINGS, AND HUMAN BEINGS' WAGES ARE SET INDIVIDUALLY IN 12 THESE COMPANIES. 13 AND THAT'S WHY, IN REED, THE COURT SAID THE NURSES' 14 SALARIES ARE SET INDIVIDUALLY, THEY CAN'T SHOW IMPACT ACROSS 15 THE BOARD, YOU HAVE TO GO NURSE BY NURSE. 16 OUR CASE OBVIOUSLY IS A LOT BIGGER, A LOT MORE COMPLICATED 17 THAN JUST ONE JOB CATEGORY, NURSES. 18 DEFENDANTS, IT INVOLVES 7,000 DIFFERENT JOB TITLES , AND IT 19 INVOLVES INDIVIDUALIZED PAY DECISIONS MADE BY THOUSANDS OF 20 MANAGERS. 21 IT INVOLVES SEVEN AND SO IF THE CLASSES WERE DENIED IN REED AND IN JOHNSON, 22 THEY SHOULD BE DENIED EVEN MORE SO HERE. 23 YOU KNOW, SETTING OF PRICES OF TV SCREENS WHERE WHEN YOU 24 OVERPRICE ONE, YOU OVERPRICE ALL OF THEM. 25 THIS IS NOT THE LCD, THE OTHER POINT IS ON THIS SMALLER CLASS, THAT CLASS IS UNITED STATES COURT REPORTERS 301 140 1 NOT DATA DRIVEN. 2 GOING TO LOOK AT THE COMPENSATION DATA, NOT COLD CALLING DATA, 3 THEY TOLD YOUR HONOR THEY WERE GOING TO LOOK AT COMPENSATION 4 DATA AND FIGURE OUT WHERE THE SPREAD WAS. 5 WHEN THE PLAINTIFFS TOLD YOUR HONOR THEY WERE DR. LEAMER DID NOT COME UP WITH THE TECHNICAL CLASS. THE 6 LAWYERS CAME UP WITH THAT. 7 RECEIVED THAT DEFINITION FROM THE LAWYERS, SO THAT'S NOT DATA 8 DRIVEN. 9 TWO LAST POINTS. DR. LEAMER TESTIFIED THAT HE YOUR HONOR HAS FOCUSSED, UNDERSTANDABLY, 10 ON THE SCOPE OF THE AGREEMENTS, THE UNLAWFULNESS OF THE 11 AGREEMENTS, SOME OF THE E-MAILS. 12 NONE OF THAT GOES TO THE QUESTION THAT I THINK IS CENTRAL 13 HERE, AND THAT IS, HOW DO THEY SHOW IMPACT? 14 THAT SOMEBODY'S WAGES WERE AFFECTED BY NOT GETTING A COLD CALL? 15 HOW DO THEY SHOW AND AS WE'VE SET FORTH IN THE PAPERS, THE ONLY WAY TO DO 16 THAT IS GO PERSON BY PERSON. 17 WOULD HAVE GOT A COLD CALL. 18 19 YOU CAN'T ASSUME THAT EVERYBODY YOU CAN'T ASSUME THAT EVERYBODY WHO GOT A COLD CALL -- WHO WOULD HAVE GOT A COLD CALL WOULD HAVE GOT A RAISE. 20 AND YOU CAN'T ASSUME THAT IF SOMEBODY GOT A RAISE FROM A 21 COLD CALL, THAT WOULD PROPAGATE OR CASCADE OR RIPPLE, WHATEVER 22 VERB THEY WANT TO USE, TO EVERYBODY ELSE. 23 I MEAN, YOU THINK ABOUT THE ABSURDITY OF THAT. WHY WOULD 24 A COMPANY GIVE A RAISE TO SOMEBODY IN A NEGOTIATION IF IT KNEW 25 THAT IT HAD TO TURN AROUND AND GIVE A RAISE TO EVERYBODY? UNITED STATES COURT REPORTERS I 302 141 1 MEAN, THAT WOULDN'T MAKE ANY SENSE. 2 AND THAT'S WHY, WHEN YOU LOOK AT THE DATA, WHEN YOU LOOK 3 AT THE DATA IN OUR FIRST FOUR OR FIVE TABS, IT SHOWS VARIATION 4 AMONG PEOPLE WHO ARE IDENTICAL IN EVERY CHARACTERISTIC. 5 BUT THERE'S VARIATION BECAUSE MANAGERS ARE MAKING THE 6 DISCRETIONARY JUDGMENT, AND IT SHOWS VARIATION FROM JOB TO JOB 7 IN A SNAPSHOT AND ACROSS TIME. 8 THAT'S WHY WHEN YOU LOOK AT THOSE CHARTS, IT SHOWS THE 9 DISTRIBUTION OF CHANGES. 10 11 12 13 JOBS MOVE DIFFERENTLY, AND SOME JOBS, THE TOTAL COMPENSATION OR AVERAGE COMPENSATION GOES UP, AND OTHER JOBS IT GOES DOWN. THEY'RE NOT CORRELATED OVER TIME, WHICH IS WHAT LEAMER HAS ADMITTED AND WHICH HE'S ADMITTED HIS CHARTS DON'T SHOW. AND THAT'S WHAT HE'S -- HE UNDERTAKES, IN HIS SECOND STEP, 14 TO SHOW THAT THIS AVERAGE OVERCHARGE WOULD -- OR UNDERPAYMENT 15 WOULD HAVE SPREAD TO EVERYBODY AND HE SAYS HE'S GOING TO DO 16 THAT BY SHOWING HOW CLOSELY CORRELATED ALL THESE JOBS ARE. 17 THAT'S WHEN HE SAYS IT'S A RIGID PAY STRUCTURE. 18 UNDER HIS OWN METHOD, HE'S GOT TO SHOW THAT THE PAY 19 STRUCTURE IS SO RIGID THAT A RAISE FOR ONE OR A RAISE FOR 20 ALL -- EXCUSE ME, A RAISE FOR ONE OR FOR SOME IN A DEPARTMENT 21 IS GOING TO PROPAGATE TO BE A RAISE FOR EVERYBODY IN THAT 22 DEPARTMENT, AND THEN SOMEHOW EVERY OTHER DEPARTMENT, EVERY 23 OTHER JOB TITLE, NO MATTER HOW DISPARATE, AND THEN ONCE IT DOES 24 THAT, IT'S GOING TO DO THE SAME THING AT ALL THE OTHER 25 COMPANIES. UNITED STATES COURT REPORTERS 303 142 1 AND IF YOU THINK -- IF YOU THINK ABOUT IT, WHATEVER THE 2 SCOPE OF THESE AGREEMENTS AFFECTING 1 PERCENT OF THE MARKET 3 THAT THESE COMPANIES OPERATED IN IN TERMS OF LABOR POOLS, 4 THERE'S NO WAY TO THINK THAT THAT WAS GOING TO HAVE A BROAD 5 IMPACT LIKE THEY'RE DESCRIBING, WHICH I THINK IS WHY, FROM THE 6 VERY START, YOUR HONOR SAID, "LOOK, IT CAN'T BE EVERYBODY. 7 LOOK AT THE COMPENSATION DATA AND SEE IF YOU CAN SEE WHERE THE 8 IMPACT WAS." 9 10 11 THAT'S WHAT THEY WERE SUPPOSED TO DO AND THAT'S WHAT THEY DIDN'T DO. THEY INSTEAD COME UP WITH LEAMER WITH THIS TWO-STEP 12 PROCESS. 13 WALKED UNDER THROUGH AND AS THESE CHARTS SHOW, THAT DOESN'T 14 SHOW AN AVERAGE OF ANYTHING. 15 TOGETHER, EVEN IF YOU PUT ASIDE ALL THE OTHER TECHNICAL 16 PROBLEMS WITH THE REGRESSION. 17 HIS FIRST STEP TO SHOW THE AVERAGE UNDERPAYMENT, AS I IT SHOWS EVERYBODY TAKEN BUT MORE THAN THAT, WHEN YOU DISAGGREGATE IT, AS HE DID 18 BUT AS HE WOULDN'T GIVE US, BUT HE SAID, "OKAY, PRESS A BUTTON 19 AND YOU CAN DO IT." 20 21 22 WHEN WE DID IT, IT SHOWS THAT THREE OR FOUR OF THE DEFENDANTS GO THE OPPOSITE DIRECTION. NOW, I'M NOT CITING THAT TO SAY THAT THAT PROVES THAT 23 THESE AGREEMENTS RESULTED IN OVERCOMPENSATION. 24 THAT FOR IS TO SHOW THAT WHEN YOU DO A SENSITIVITY TEST AND YOU 25 GET SOME PEOPLE GOING ONE WAY, SOME COMPANIES GOING THE OTHER UNITED STATES COURT REPORTERS WHAT WE CITE 304 143 1 2 WAY, THAT TELLS YOU SOMETHING IS WRONG WITH THE MODEL. BUT EVEN IF HE HAD A PERFECT SYSTEM -- 3 THE COURT: CAN YOU WRAP UP? 4 MR. MITTELSTAEDT: 5 THE COURT: 6 MR. MITTELSTAEDT: OKAY. JUST 15 SECONDS, PLEASE. TWO LAST POINTS. ONE IS IN THEIR 7 REPLY BRIEF, THEY SAY MURPHY CONCEDED THIS, MURPHY CONCEDED 8 THAT. 9 WE'VE SUBMITTED SUPPLEMENTAL EXCERPTS FROM MURPHY'S 10 TESTIMONY AND, IF ANY OF THAT MATTERS, WHEN YOU ACTUALLY READ 11 MURPHY'S TESTIMONY, HE DIDN'T COME CLOSE TO MAKING THE 12 CONCESSIONS THAT THEY SAY HE DID. 13 AND FINALLY, YOUR HONOR, YOU KNOW, THIS MATTER IS 14 COMPLICATED. 15 START AND YOUR HONOR DECLINED THAT. 16 WE HAD REQUESTED AN EVIDENTIARY HEARING AT THE I WOULD ASK YOUR HONOR TO JUST CONSIDER, AS YOU REVIEW 17 WHAT THEY'VE DONE AND THE ANSWERS YOU'VE RECEIVED TODAY ABOUT 18 WHAT THEY DID, AND THE CONSTANT REFRAIN WAS, "WELL, YOU KNOW, 19 WE REALLY NEED DR. LEAMER TO EXPLAIN THAT," GIVEN THAT YOUR 20 HONOR WILL BE MAKING A RIGOROUS ANALYSIS OF WHAT THE EXPERTS 21 DID, AND GIVEN THAT OUR POSITION IS THIS ISN'T A BATTLE OF 22 EXPERTS, THIS IS A CASE WHERE DR. LEAMER HAS ADMITTED THAT 23 HIS -- THAT WHAT HE TRIED TO DO WITH HIS TWO STEPS DON'T WORK 24 BECAUSE THEY DON'T STAND UP TO EVEN THE TEST THAT HE PROVIDED, 25 AND BY THAT WHAT I MEAN IS HE SAID IN HIS STEP TWO HE WAS GOING UNITED STATES COURT REPORTERS 305 144 1 TO SHOW THAT ANY OVERCHARGE WAS CORRELATED OVER TIME, AND HE'S 2 ADMITTED AT THE PAGES I CITED TO YOUR HONOR AT THE START HERE 3 THAT THEY DON'T DO THAT. 4 THEY DON'T DO THAT AT ALL. AND THEN INTEL 28 AND THE APPLE 4, WHICH IS THE SAME KIND 5 OF THING, SHOWS THAT EVEN WITHIN THE SAME JOB TITLE, THE 6 EMPLOYEES' COMPENSATION GOES DIFFERENT DIRECTIONS, THE OPPOSITE 7 OF THE RIGID SYSTEM THAT THEY SAY THEY NEED TO -- THAT IS THE 8 HEART OF THEIR METHOD OF PROVING COMMON IMPACT. 9 SO WHEN YOU GET DONE WITH ALL OF IT, WHERE YOU END UP IS 10 THE ONLY WAY TO DETERMINE WHO WAS IMPACTED BY THESE 11 AGREEMENTS -- AND I ADMIT AT THE START, WE ARE NOT SAYING THAT 12 NOBODY WAS IMPACTED. 13 TALK ABOUT "WE DON'T WANT SO-AND-SO TO BE COLD CALLED BECAUSE, 14 YOU KNOW, HE MIGHT LEAVE AND MIGHT GET SOME MORE MONEY." 15 PERSON MAY HAVE A CLAIM. 16 YOU LOOK AT SOME OF THESE DOCUMENTS THAT THAT BUT IF HE HAS A CLAIM, THAT DOESN'T MEAN THAT ANYBODY ELSE 17 WHO WORKED WITH HIM, ANYBODY ELSE IN ANOTHER DEPARTMENT, THE 18 SOU CHEF, ANYBODY ELSE IN ANY OTHER DEPARTMENT HAS A CLAIM, AND 19 IT DOESN'T MEAN THAT ALL THE OTHER COMPANIES WOULD HAVE GIVEN 20 RAISES TO THEIR PEOPLE IF THIS ONE PERSON HAD GOTTEN A RAISE. 21 THAT'S THEIR THEORY, THE RIPPLE EFFECT. 22 THE DATA SHOWS THAT THEY'RE -- EVEN IN THE BEFORE TIME 23 PERIOD -- 24 25 THE COURT: ALL RIGHT. I REALLY NEED YOU TO WRAP UP, OKAY. UNITED STATES COURT REPORTERS 306 145 1 2 3 4 5 MR. MITTELSTAEDT: LAST WORD. WHEN YOU LOOK AT THE DATA FROM THE -THE COURT: YOU'RE KILLING ME HERE. (LAUGHTER.) MR. MITTELSTAEDT: WHEN YOU LOOK AT THE DATA FROM 6 THE BEFORE PERIOD, IT SHOWS THAT THESE COMPANIES DID NOT HAVE 7 THE RIGID PAY STRUCTURE THAT IS, UNDER THEIR OWN METHOD, THE 8 CENTERPIECE, THE ESSENTIAL ELEMENT OF THEIR CLAIM, LEAVING US 9 WITH INDIVIDUALIZED INQUIRIES TO DETERMINE WHO WAS IMPACTED. 10 THE COURT: OKAY. 11 MR. MITTELSTAEDT: 12 THE COURT: 13 MR. MITTELSTAEDT: 14 THE COURT: THANK YOU, YOUR HONOR. THANK YOU. I APPRECIATE THE TIME. I'M GOING TO KEEP YOU TO TWO MINUTES 15 BECAUSE YOU HAD A LOT OF TIME FOR THIS HEARING AND DEFENDANTS 16 DIDN'T HAVE THAT TIME. 17 MR. GLACKIN: I UNDERSTAND, YOUR HONOR. 18 TO NOT RESPOND TO ALL OF THAT. 19 BUT I'LL LEAVE IT TO THE RECORD. 20 I'M GOING BEEN ADDRESSED IN THE RECORD. 21 22 23 24 25 I MEAN, I DON'T AGREE WITH IT, I THINK ALL THOSE POINTS HAVE I WANTED TO MAKE -- SO I WANTED TO DRAW THE COURT'S ATTENTION TO TWO CASES. MR. MITTELSTAEDT: BRANDON. I FORGOT TO SAY THE LAST THING I WAS LEADING UP TO, WHICH IS NOW THAT YOUR HONOR HAS LOOKED AT ALL OF THIS AND IS UNITED STATES COURT REPORTERS 307 146 1 STARTING TO STUDY IT, OR WHATEVER STAGE YOU'RE IN, I WOULD ASK 2 YOUR HONOR TO RECONSIDER WHETHER AN EVIDENTIARY HEARING WOULD 3 MAKE SENSE GIVEN WHAT THEY'VE SAID ABOUT -- DID I SAY THAT? 4 THE CLERK: YOU DID. 5 MR. MITTELSTAEDT: 6 MR. GLACKIN: 7 THE COURT: I DID SAY THAT? YOU SAID IT ALREADY. OKAY. I MEAN, IF THEY CAN'T PROVE IT, 8 THEY CAN'T -- IF THEY CAN'T PRESENT IT TODAY, I'M NOT GOING TO 9 GIVE DR. LEAMER ANOTHER OPPORTUNITY TO TRY TO CORRECT IT. 10 MR. MITTELSTAEDT: 11 MR. GLACKIN: OKAY. SO, YOUR HONOR, MR. MITTELSTAEDT SAID 12 THAT THE MOST IMPORTANT CASE YOU NEED TO UNDERSTAND IS THE REED 13 CASE, WHICH IS FROM THE NORTHERN DISTRICT OF ILLINOIS. 14 THEY'VE NEVER ADDRESSED KOHEN AND MESSNER, WHICH ARE THE 15 AUTHORITIES WE CITED FOR THE PROPOSITION THAT YOU DO NOT NEED 16 TO SHOW HARM TO EVERY INDIVIDUAL CLASS MEMBER. 17 THOSE ARE CASES FROM THE SEVENTH CIRCUIT COURT OF APPEALS 18 WHICH, BY THE WAY, OVERSEES THE NORTHERN DISTRICT OF ILLINOIS, 19 SO I THINK THAT THOSE ARE FAR BETTER AUTHORITY ON THIS POINT. 20 AND I WANTED TO CALL THE COURT'S ATTENTION TO THE FACT 21 THAT THERE -- I JUST FIGURED OUT YESTERDAY, AND I TOLD THEM I 22 WOULD RAISE THIS YESTERDAY, I FOUND TWO MORE CASES THAT SHOW 23 THAT THIS RULE OF KOHEN THAT YOU DO NOT NEED TO SHOW INJURY ON 24 AN INDIVIDUAL BY INDIVIDUAL BASIS TO EVERY SINGLE CLASS MEMBER 25 HAS BEEN ADOPTED IN TWO MORE CIRCUITS, THE TENTH CIRCUIT AND UNITED STATES COURT REPORTERS 308 147 1 THE FIFTH CIRCUIT, AND I'M JUST GOING TO READ THE CITATIONS 2 INTO THE RECORD. 3 THE FIRST CASE IS D.G. VERSUS DEVAUGHN, CITE 594 F.3D 4 1188, AND THAT'S IN THE TENTH CIRCUIT; AND THE SECOND 5 CIRCUIT -- EXCUSE ME -- THE SECOND CASE IS MIMS VERSUS STEWART 6 TITLE GUARANTEE COMPANY, THE CITATION IS 590 F.3D 298, AND 7 THAT'S IN THE FIFTH CIRCUIT. 8 9 10 11 AND IN BOTH THOSE CASES, BOTH OF THOSE COURTS SAY YOU DO NOT NEED TO SHOW INDIVIDUAL PROOF TO EVERY SINGLE MEMBER OF THE CLASS, AND THEY CITE AND QUOTE KOHEN FOR THAT PROPOSITION. I WANTED TO ADDRESS -- I WANTED TO SAY ALSO THAT WE HAD A 12 LOT OF QUESTIONS AND A LOT OF ARGUMENT TODAY ABOUT REGRESSION 13 ANALYSIS, AND I WOULD REALLY ENCOURAGE THE COURT TO READ 14 CLOSELY THE SUPREME COURT'S BAZEMORE DECISION. 15 FOR THE GENERAL PROPOSITION THAT IT'S CITED FOR IN EVERY CASE, 16 WHICH IS THAT IF YOU COVER THE MAJOR FACTORS, A REGRESSION 17 ANALYSIS IS NOT, FOR OTHER REASONS, INADEQUATE. 18 WE CITE THAT THERE'S TWO OTHER THINGS WE DIDN'T HAVE SPACE TO MENTION 19 IN THE BRIEFS, WHICH IS, ONE, BAZEMORE IS A WAGE SUPPRESSION 20 CASE, AND THE PLAINTIFFS IN BAZEMORE WERE SEEKING TO DO EXACTLY 21 THE SAME THING THAT WE ARE SEEKING TO DO HERE, AND THE COURT OF 22 APPEAL REJECTED THEIR REGRESSION ANALYSIS BECAUSE THEY DIDN'T 23 HAVE ALL OF THE VARIABLES THAT THE COURT OF APPEAL THOUGHT WAS 24 RELEVANT AND THE SUPREME COURT REVERSED. 25 THE COURT OF APPEAL ALSO REJECTED THEIR ANALYSIS BECAUSE UNITED STATES COURT REPORTERS 309 148 1 THEY FAILED TO DISAGGREGATE THE DATA ON A COUNTY BY COUNTY 2 BASIS. 3 SHOULD HAVE BEEN EXAMINED COUNTY BY COUNTY BY COUNTY IN ORDER 4 TO EXCLUDE THE POSSIBILITY THAT COUNTY BY COUNTY DIFFERENCES 5 WERE DRIVING THE RESULT OR BEING OBSCURED BY THE RESULT, AND 6 THE SUPREME COURT REJECTED THAT AS WELL AND REVERSED. 7 THE COURT OF APPEAL SAYS THAT THIS -- THAT THESE WAGES THE SUPREME COURT -- WHETHER OR NOT THIS WAS ADMISSIBLE 8 EVIDENCE WASN'T EVEN ON THE TABLE. 9 THE BENCH VERDICT THAT THE PLAINTIFFS HAD NOT MET THEIR 10 STANDARD OF BURDEN OF PROVING BY A PREPONDERANCE OF THE 11 EVIDENCE BECAUSE IT FOUND THAT THE SUPREME COURT -- EXCUSE 12 ME -- THE COURT OF APPEAL AND THE DISTRICT COURT HAD APPLIED 13 THE WRONG LEGAL STANDARD IN REJECTING THIS EVIDENCE AS 14 PROBATIVE. 15 THE SUPREME COURT REVERSED SO I THINK THAT A CLOSE READING OF THE BAZEMORE CASE WILL 16 REALLY HELP UNDERSTAND -- HELP ILLUSTRATE JUST HOW COMMON AND 17 ACCEPTED REGRESSION ANALYSIS IS, AND THAT ALL OF THESE POINTS 18 ABOUT SENSITIVITY AND DISAGGREGATION AND WHETHER OR NOT WE USE 19 THE RIGHT VARIABLES ARE -- THEY'RE AT GREAT RISK FOR 20 CROSS-EXAMINATION AND I'VE SEEN IT DONE. 21 AGAINST DR. LEAMER IN TRIAL. 22 23 24 25 I'VE SEEN IT DONE BUT IT'S NOT AN ISSUE THAT GOES TO THE ADMISSIBILITY OF THE EVIDENCE. AND ON THAT LAST POINT, THE ONE THING THAT I JUST HAVE TO SAY IS THAT WHEN -- IT'S REALLY EASY FOR MR. MITTELSTAEDT TO UNITED STATES COURT REPORTERS 310 149 1 STAND HERE AND SAY THAT LCD WAS A REAL EASY STANDARD PRICE 2 FIXING CASE AND IMPACT WAS PRACTICALLY PRESUMED. 3 NOTHING COULD BE FURTHER FROM THE TRUTH, FRANKLY. THE 4 DEFENDANTS CONTESTED IMPACT AT EVERY STEP OF THE CASE. THE 5 DEFENDANTS' ARGUMENT WAS ACTUALLY VERY SIMILAR TO THE ARGUMENT 6 IN THIS CASE. 7 PRODUCT MODELS EVERY YEAR. 8 DIFFERENT FEATURES. 9 INDIVIDUAL PRICE FOR EVERY SINGLE ONE OF THESE PRODUCT MODELS THEY SAID, "WE HAVE THOUSANDS OF DIFFERENT THESE PRODUCTS HAVE TONS OF WE SET IT -- WE NEGOTIATE A DIFFERENT 10 WITH OUR CUSTOMERS, SO HOW CAN YOU POSSIBLY SHOW THAT EVERY 11 CUSTOMER WAS INJURED UNLESS YOU LOOK AT EVERY INDIVIDUAL 12 TRANSACTION BETWEEN THAT CUSTOMER AND THE DEFENDANTS?" 13 AND THE LAW IS CLEAR THAT THAT IS NOT OUR BURDEN AND, 14 FRANKLY, THE TESTIMONY IN THIS CASE IS CLEAR THAT THAT 15 REGRESSION ANALYSIS IS NOT CAPABLE OF THAT KIND OF AN INQUIRY. 16 SO WHAT DID WE DO IN LCD? WE DID EXACTLY THE SAME THING 17 THAT'S BEEN PROPOSED HERE. 18 SHOW A STRUCTURE IN THE MARKET, AND WE OFFERED A REGRESSION 19 ANALYSIS TO SHOW BOTH IMPACT AND DAMAGES, AND THAT WAS 20 TESTIFIED TO AT TRIAL OVER A DAUBERT MOTION. WE DID A CORRELATION ANALYSIS TO 21 THAT REGRESSION MODEL PRODUCED AN AVERAGE EFFECT 22 COEFFICIENT FOR THE CONSPIRACY, JUST LIKE IN THIS CASE, THE 23 REASON BEING THAT WE COULD NOT POSSIBLY -- DR. LEAMER COULD NOT 24 POSSIBLY CONTROL FOR EVERY SINGLE DIFFERENT COMBINATION OF 25 PRODUCT FEATURES IN THIS, YOU KNOW, IN THIS MASSIVE MARKET. UNITED STATES COURT REPORTERS 311 150 1 SO INSTEAD THERE WAS A SINGLE -- THERE WAS A SINGLE 2 CONSPIRACY EFFECT VARIABLE FOR THE ENTIRE CONSPIRACY, JUST LIKE 3 HERE; AND THEN DR. LEAMER, JUST LIKE HERE, HE TOOK STEPS TO TRY 4 TO ALLOW THAT VARIABLE TO BE HETEROGENEOUS ACROSS DIFFERENT 5 SCREEN SIZES. 6 THERE WAS DATA ENOUGH TO DO THAT. SO WE ALLOWED -- JUST LIKE HERE WHERE HE'S ALLOWED TO VARY 7 DEFENDANT BY DEFENDANT BASED ON QUALITIES THAT ARE UNIQUE TO 8 EACH DEFENDANT, IN LCD, HE ALLOWED THE IMPACT OF THAT VARIABLE 9 TO DIFFER SCREEN SIZE BY SCREEN SIZE BASED ON DIFFERENT 10 11 FEATURES OF THOSE MARKETS. IT'S EXACTLY THE SAME EVIDENCE. AND THE DEFENDANTS MADE 12 THE SAME ARGUMENTS IN THAT CASE, THAT HIS REGRESSION ANALYSIS 13 WAS SENSITIVE. 14 IF YOU MOVE THE END DATE OF THE CONSPIRACY -- THE COURT: I NEED YOU TO WRAP UP. THIS IS CRUEL 15 AND UNUSUAL PUNISHMENT TO MS. SHORTRIDGE WHO'S BEEN 16 TRANSCRIBING FOR NEARLY FOUR HOURS, OKAY? 17 CONCLUDE HERE. 18 19 20 FIVE MINUTES. SO YOU NEED TO FIVE SECONDS. MR. GLACKIN: I DON'T EVEN NEED FIVE SECONDS. I DON'T HAVE ANY MORE TO ADD. 21 THANK YOU VERY MUCH. 22 THE COURT: 23 OKAY. I'M GOING TO GIVE MR. HINMAN -- RIGHT? -- THE LAST WORD. 24 MR. HINMAN: YES. THANK YOU, YOUR HONOR. 25 DON'T WANT TO ADD TO THE MISERY. AND I JUST VERY BRIEFLY. UNITED STATES COURT REPORTERS 312 151 1 WITH RESPECT TO THESE NOTES, TO THE EXTENT THAT THIS IS 2 STILL AN ISSUE AT ALL IN YOUR HONOR'S MIND, I THINK WE HEARD 3 SOME THINGS THAT, FRANKLY, AREN'T IN THE RECORD AND I DON'T 4 THINK ARE QUITE RIGHT. 5 6 7 SO WHAT I WOULD SAY IS THE ARGUMENT BOILS DOWN TO DR. MURPHY HAS GOT TO DISCLOSE WHAT HE RELIED ON. HE WAS ASKED IN HIS DEPOSITION WHAT HE RELIED ON, AND HE 8 SAID, "SPECIFICALLY I'M RELYING ON THOSE DECLARATIONS," SO THE 9 DECLARATIONS THAT ARE BEFORE THE COURT AND IN THE RECORD, 10 "THAT'S CONSISTENT WITH OTHER THINGS THAT, IN THE INTERVIEWS, 11 THAT PEOPLE SAID." 12 THAT'S AT PAGE 133 TO -34. AND THEN AT PAGE 122, HE SAID, "IN GENERAL, IT WAS RELYING 13 ON THE GENERAL BACKGROUND. 14 THINK IN THAT REGARD, I THINK THE INFORMATION FROM THE 15 INTERVIEWS AND THE INFORMATION FROM THE DECLARATIONS. 16 JUST AT THE END OF THE DAY, GIVEN THAT WE HAD THE DECLARATIONS, 17 IT MADE MORE SENSE TO RELY UPON THEM." 18 AS I'VE SAID NUMEROUS TIMES, AND I IT'S SO HE'S DISCLOSED THE DECLARATIONS, HE'S DISCLOSED THE 19 PEOPLE WHO HE INTERVIEWED, HE WAS ASKED MANY, MANY QUESTIONS 20 ABOUT THE INTERVIEWS HAVING TO DO WITH THE UNDERLYING FACTS 21 THAT HE LEARNED THERE, AND IF THE PLAINTIFFS THINK THAT IT'S A 22 PROBLEM THAT HE COULDN'T SPECIFICALLY REMEMBER WHAT EACH PERSON 23 TOLD HIM OR THAT HIS OPINIONS ARE BASED ON FACTS THAT ARE 24 INCORRECT, THEN I WOULD THINK THAT THEY WOULD HAVE COME IN AND 25 ARGUED THAT. UNITED STATES COURT REPORTERS 313 152 1 WELL, THEY HAVEN'T. 2 OR THEY COULD HAVE PURSUED IT FURTHER WITH HIM, AND THEY 3 4 DIDN'T. OR THEY COULD HAVE DEPOSED THOSE PEOPLE, MANY OF WHOM THEY 5 NEVER ASKED TO DO, NOTWITHSTANDING THAT THEY WERE FULLY 6 DISCLOSED, AND SAY, YOU KNOW, "WHAT DID YOU TELL DR. MURPHY?" 7 AND THEN TEST HIS OPINIONS AGAINST THAT. 8 9 SO THE POINT IS, HE DISCLOSED WHAT HE NEEDED TO DISCLOSE. THERE WERE MANY WAYS -- IF THEY WANT TO CHALLENGE WHAT THOSE 10 UNDERLYING FACTS ARE, THEY WERE ENTITLED TO DO THAT IN ALL OF 11 THE USUAL WAYS. 12 AND AS I SAID BEFORE, THERE'S NOTHING EITHER LEGALLY OR, 13 FRANKLY, LOGICALLY THAT GETS YOU TO THESE PRELIMINARY NOTES 14 THAT WERE TAKEN, ESPECIALLY WHEN WE HAVE THIS VERY BROAD 15 STIPULATION. 16 17 18 THE COURT: ALL RIGHT. WELL, THANK YOU ALL VERY MUCH. MARCH 13TH IS WHEN WE SET THIS, RIGHT? 19 THE CLERK: 20 MR. GLACKIN: 21 MR. MITTELSTAEDT: 22 MR. HINMAN: 23 MR. GLACKIN: 24 25 WE'LL SEE YOU, THEN, ON -- YES. THANK YOU VERY MUCH, YOUR HONOR. THANK YOU, YOUR HONOR. THANK YOU, YOUR HONOR. AND THANK YOU MEMBERS OF THE COURT STAFF. THE COURT: THANK YOU VERY MUCH FOR ALL OF YOUR UNITED STATES COURT REPORTERS 314 153 1 2 3 PRESENTATIONS. MR. MITTELSTAEDT: THANK YOU, YOUR HONOR. (THE PROCEEDINGS IN THIS MATTER WERE CONCLUDED.) 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 UNITED STATES COURT REPORTERS 315 1 2 CERTIFICATE OF REPORTER 3 4 5 6 7 I, THE UNDERSIGNED OFFICIAL COURT REPORTER OF THE UNITED 8 STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA, 9 280 SOUTH FIRST STREET, SAN JOSE, CALIFORNIA, DO HEREBY 10 11 CERTIFY: THAT THE FOREGOING TRANSCRIPT, CERTIFICATE INCLUSIVE, IS 12 A CORRECT TRANSCRIPT FROM THE RECORD OF PROCEEDINGS IN THE 13 ABOVE-ENTITLED MATTER. 14 15 17 _______________________________ LEE-ANNE SHORTRIDGE, CSR, CRR CERTIFICATE NUMBER 9595 18 DATED: 16 FEBRUARY 5, 2013 19 20 21 22 23 24 25 UNITED STATES COURT REPORTERS 316 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page1 of 81 IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA SAN JOSE DIVISION CONFIDENTIAL – TO BE FILED UNDER SEAL SUBJECT TO PROTECTIVE ORDER IN RE: HIGH-TECH EMPLOYEES ANTITRUST LITIGATION No. 11-CV-2509-LHK _____________________________________ THIS DOCUMENT RELATES TO: ALL ACTIONS EXPERT REPORT OF EDWARD E. LEAMER, PH.D. October 1, 2012 317 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page2 of 81 TABLE OF CONTENTS I.  Experience and Qualifications ...................................................1  II.  Introduction, Assignment, and Summary of Conclusions ..........2  III.  Case and Background ................................................................ 6  A.  Defendants..................................................................................... 6  B.  The Non-Compete Agreements .......................................................... 9  1.  Pixar-Lucasfilm ......................................................................... 12  2.  The Apple Non-Compete Agreements ........................................... 14  3.  The Google Non-Compete Agreements ......................................... 19  4.  Department of Justice Investigation and the End of the Collusion..... 22  C.  Named Plaintiffs ............................................................................ 22  D.  Background on Defendants’ Recruiting and Hiring Practices ................. 25  IV.  Common Evidence and Analysis Are Capable of Showing that the Non-Compete Agreements Artificially Reduced the Compensation of Defendants’ Salaried Employees ..................28  A.  Class-wide Evidence is Capable of Showing that the Non-Compete Agreements Suppressed Compensation Generally .............................. 29  1.  Economic Theory Offers a Classwide Basis for Linking Non-Compete Agreements to Suppressed Compensation Incurred by Members of the All-Employee Class and Technical Employee Class .................... 29  2.  Defendants’ Internal Documents Provide Additional Class-wide Evidence Capable of Showing that the Non-Compete Agreements Artificially Suppressed Compensation ........................................... 33  3.  Analysis of Defendants’ Compensation Data Is Additional Class-wide Evidence Capable of Showing that the Compensation of AllEmployee Class and Technical Employee Class Members Was Suppressed by the Non-Competition Agreements .......................... 35  4.  Common Evidence Confirms that the Non-Compete Agreements Coincided with Periods of Economic Expansion that Otherwise Would Have Increased Compensation to Class Members ................. 38  B.  Classwide Evidence is Capable of Showing that the Non-Compete Agreements Suppressed the Compensation of All or Nearly All Members of the All-Employee Class and Technical Employee Class ....... 42  i Expert Report of Edward E. Leamer, Ph.D. 318 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page3 of 81 1.  Defendants’ Internal Documents Constitute an Additional Form of Common Proof Capable of Showing that the Non-Compete Agreements Suppressed Compensation to All or Nearly All Members of the All-Employee Class and Technical Employee Class ... 45  2.  Econometric and Statistical Analysis of Defendants’ Compensation Data Is Also Capable of Demonstrating That the Compensation Suppressing Effects of the Non-Compete Agreements Would Be Broadly Experienced By Members of the All-Employee Class and Technical Employee Class .......................................................... 49  3.  Standard Econometric Analysis Is Capable of Showing That the Non-Compete Agreements Artificially Suppressed Compensation to the Members of Each Class Generally........................................... 62  V.  Conclusion............................................................................... 70  APPENDIX A.  Defendant Data Relied Upon ...................................72  A.  Description of Data Requested and Produced ..................................... 72  1.  Employment Data ..................................................................... 72  2.  Recruiting Data ........................................................................ 72  B.  Datasets Created for Analysis ......................................................... 73  APPENDIX B.  Definition of the Technical Employee Class .............74  ii Expert Report of Edward E. Leamer, Ph.D. 319 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page4 of 81 TABLE OF FIGURES Figure 1: Periods of the Alleged Collusive Agreements ................................................... 9  Figure 2: Relationships of the Alleged Agreements Among Defendants ........................... 10  Figure 3: Class Employee Summary .......................................................................... 23  Figure 4: Technical Employee Class Summary ............................................................ 23  Figure 5: Named Plaintiffs’ Employment Histories ....................................................... 25  Figure 6: Inter-firm Movement Results in Higher Base Compensation ............................ 37  Figure 7: Inter-firm Movement Results in Higher Total Compensation ............................ 38  Figure 8: Use of Equity Compensation ....................................................................... 40  Figure 9: Growth of Apple's Revenue and Compensation .............................................. 41  Figure 10: Use of Supplemental Compensation was Widespread ................................... 53  Figure 11: Common Factors Identify a Firmwide Compensation Structure....................... 54  Figure 12: Common Factors Explain Within-Firm Compensation Structure ...................... 56  Figure 13: Common Factors Identify a Firmwide Compensation Structure....................... 57  Figure 14: Common Factors Explain Within-Firm Compensation Structure ...................... 58  Figure 15: Constant Attribute Compensation of Major Apple Job Titles ........................... 59  Figure 16: Constant Attribute Compensation of Major Google Job Titles ......................... 60  Figure 17: Constant Attribute Compensation Ranking of Major Apple Job Titles is Generally Stable .................................................................................................................. 61  Figure 18: Growth Cycle Periods for the U.S. Economy ................................................ 62  Figure 19: Average Percent Change in Total Compensation .......................................... 63  Figure 20: Regression Estimate of Undercompensation to Class .................................... 66  Figure 21: Data Definitions ...................................................................................... 67  Figure 22: Estimated Impact on Class Total Compensation ........................................... 67  Figure 23: Regression Estimate of Undercompensation to Technical Employee Class ........ 69  Figure 24: Estimated Impact on Technical Employee Class Total Compensation............... 70  Figure 25: Adobe, Apple, Google, Intel, and Intuit Creative, Technical, and R&D Job Families ........................................................................................................................... 75  iii Expert Report of Edward E. Leamer, Ph.D. 320 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page5 of 81 CONFIDENTIAL I. 10/1/2012 Experience and Qualifications 1. I am the Chauncey J. Medberry Professor of Management, Professor of Economics and Professor of Statistics at the University of California at Los Angeles. I earned a B.A. degree in Mathematics from Princeton University in 1966, and a Masters in Mathematics and a Ph.D. degree in Economics at the University of Michigan in 1970. I was an Assistant and Associate Professor of Economics at Harvard University from 1970 to 1975, and joined the Economics Department at UCLA in 1975 as a Full Professor. I served as Chair of the Department of Economics from 1983 to 1987 and Area Head of Business Economics from 1990 to 1993. I had a tenured appointment in the Economics Department at Yale University in 1995 and I have been a Visiting Professor at several universities, including the University of Chicago. I have been a Guest Professor at the University of Basel in Switzerland, at the Central European University in Prague, Czech Republic, at the Institute for Advanced Studies in Vienna, Austria, and at the Universidad de San Andreas in Buenos Aires, Argentina. I have served as the Director of the UCLA Anderson Forecast since 2000 and Chief Economist of the Ceridian-UCLA Pulse of Commerce Index from 2010-2012. 2. I have published extensively in the fields of econometric methodology and statistical analysis, in international economics, and in macro-economic forecasting. I have written five books and over 90 academic articles, many of which deal with the subject of inferences that may appropriately be drawn from non-experimental data. My academic research in econometrics and international economics has been profiled in New Horizons in Economic Thought, Appraisals of Leading Economists, edited by Warren Samuels. My papers in econometrics have been republished in a volume in the Edward Elgar Series: Economists of the 20th Century. My research has been funded by the National Science Foundation, the Ford Foundation, the Sloan Foundation, and the Russell Sage Foundation. 3. I am an elected Fellow of two of the most important honorific societies in my field: the American Academy of Arts and Sciences and the Econometric Society. I have been a consultant for the Federal Reserve Board of Governors, the Page 1 Expert Report of Edward E. Leamer, Ph.D. 321 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page6 of 81 CONFIDENTIAL 10/1/2012 Department of Labor, the Department of Energy, the International Monetary Fund, the World Bank, the Inter-American Development Bank, and the Treasury of New Zealand. I have been a visiting scholar with the Federal Reserve Board and the International Monetary Fund. I have served as an expert in a variety of matters dealing with issues of interpretation of data. 4. My curriculum vita is incorporated in this report as Exhibit 1. My testimonial experience is incorporated in this report as Exhibit 2. My hourly rate for time spent working on this matter is $650. 5. I have in this report relied on the best information available to me at the time of its preparation. A list of documents on which I relied in the preparation of this report is provided in Exhibit 3. I understand that discovery in this matter is ongoing and that Defendants or third parties may produce additional information that has a bearing on my analysis. I reserve the right to supplement or amend my conclusions as necessary in light of such additional information. II. Introduction, Assignment, and Summary of Conclusions 6. The defendants in this matter are a group of well-known high-tech firms, namely Adobe, Apple, Google, Intel, Intuit, Lucasfilm, and Pixar (“Defendants”).1 7. The Plaintiffs’ Amended Complaint2 alleges that the Defendants agreed to limit or eliminate competition for workers amongst each other by refraining from Adobe Systems Inc. (“Adobe”) is a Delaware corporation with its principal place of business located at 345 Park Avenue, San Jose, California 95110, Apple Inc. (“Apple”) is a California corporation with its principal place of business located at 1 Infinite Loop, Cupertino, California 95014, Google Inc. (“Google”) is a Delaware corporation with its principal place of business located at 1600 Amphitheatre Parkway, Mountain View, California 94043, Intel Corp. (“Intel”) is a Delaware corporation with its principal place of business located at 2200 Mission College Boulevard, Santa Clara, California 95054, Intuit Inc. (“Intuit”) is a Delaware corporation with its principal place of business located at 2632 Marine Way, Mountain View, California 94043, Lucasfilm Ltd. (“Lucasfilm”) is a California corporation with its principal place of business located at 1110 Gorgas Ave., in San Francisco, California 94129, and Pixar is a California corporation with its principal place of business located at 1200 Park Avenue, Emeryville, California 94608. 1 Re: High-Tech Employee Antitrust Litigation, Consolidated Amended Complaint, September 2, 2011 (Consolidated Amended Complaint). 2 Page 2 Expert Report of Edward E. Leamer, Ph.D. 322 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page7 of 81 CONFIDENTIAL 10/1/2012 contacting each others’ employees to explore job offers (“Cold-Calling”3), limiting their actions in negotiating with their workers, and other restrictions. This was accomplished by means of a collection of express bilateral agreements among the Defendants. I will refer to these agreements, individually and collectively, as the “Non-Compete Agreements,” or as the “Agreements.” 8. I understand that the Plaintiffs are seeking certification of the following class of employees (the “All-Salaried Employee Class,” or, the “All-Employee Class”): All natural persons employed on a salaried basis (“salaried employees”) in the United States by one or more of the following: (a) Apple from May 2005 through December 2009; (b) Adobe from May 2005 through December 2009; (c) Google from March 2005 through December 2009; (d) Intel from March 2005 through December 2009; (e) Intuit from June 2007 through December 2009; (f) Lucasfilm from January 2005 through December 2009; or (g) Pixar from January 2005 through December 2009. Excluded from the All-Employee Class are: retail employees; corporate officers, members of the boards of directors, and senior executives of all Defendants. 9. I also understand that the Plaintiffs are seeking certification, in the alternative, of the following alternate class of employees (the “Technical, Creative, and Research & Development Class,” or, the “Technical Employee Class”): All natural persons employed on a salaried basis who work in the creative, research & development, and/or technical fields,4 in the United States by one or more of the following: (a) Apple from May 2005 through December 2009; (b) Adobe from May 2005 through December 2009; (c) Google from March 2005 through December 2009; (d) Intel from March 2005 through December 2009; (e) Intuit “Cold-Calling” refers to communicating directly in any manner (including orally, in writing, telephonically, or electronically) with another firm’s employee who has not otherwise applied for a job opening. 3 See Appendix B for a description of how I determined the members of the Technical and Creative Alternate Class. 4 Page 3 Expert Report of Edward E. Leamer, Ph.D. 323 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page8 of 81 CONFIDENTIAL 10/1/2012 from June 2007 through December 2009; (f) Lucasfilm from January 2005 through December 2009; or (g) Pixar from January 2005 through December 2009. Excluded from the Technical Employee Class are: retail employees; corporate officers, members of the boards of directors, and senior executives of all Defendants. 10. I have been asked to analyze the following questions with regard to the AllEmployee Class and Technical Employee Class defined above: (a) Is there proof common to each proposed class capable of showing that the Non-Compete Agreements artificially reduced the competition of its members? In order to answer this question, I have been asked to evaluate whether evidence common to each class is capable of showing that the Non-Competition Agreements artificially reduced the compensation of: (i) members of each class generally; and (ii) all or most members of each class? (b) Is there a reliable Class-wide or formulaic method capable of quantifying the amount of suppressed compensation suffered by each class? 11. Based upon my work to date, I have reached the following conclusions: (a) There is evidence common to the All-Employee Class and Technical Employee Class, respectively, capable of showing that the Non-Compete Agreements systematically reduced the compensation of the members of each class. Specifically, and as explained in the body of this report, I have concluded that evidence and economic analyses applicable to each class as a whole are capable of showing that compensation to the AllEmployee Class and Technical Employee Class was artificially suppressed generally due to the Non-Compete Agreements. Page 4 Expert Report of Edward E. Leamer, Ph.D. 324 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page9 of 81 CONFIDENTIAL 10/1/2012 (b) Classwide evidence capable of showing artificial generalized compensation suppression due to the agreements falls into three categories: (1) labor economic studies and theory explaining that by reducing or eliminating Cold-Calling and other active competition over employees, the Agreements were likely to have depressed compensation because they impair information flow about compensation and job offers, reduce negotiating leverage of employees, and minimize movement of employees between firms; (2) documents from Defendants’ files showing the link between “Cold-Calling” and increased compensation; and (3) multiple regression analyses, utilizing Defendants’ internal compensation and other data, showing that the Agreements artificially suppressed compensation at each Defendant. (c) I have further found that evidence and economic analysis applicable to each class as a whole are capable of showing that all or nearly all members of the AllEmployee Class and Technical Employee Class had their compensation suppressed due to the Agreements. Such classwide evidence falls into three categories: (1) economic studies and theory, especially regarding the interest of firms in preserving “internal equity,” demonstrating that the adverse effects on compensation due to a poaching ban would be felt not just by those who would have been poached, but by employees more generally due to the needs of firms to maintain a salary structure; (2) documentary evidence from Defendants’ files showing Defendants’ own concerns about preserving internal equity, as well as other documentary evidence; and (3) statistical evidence, including a multiple regression analysis, showing that All-Employee Class and Technical Employee Class member compensation at any point in time is governed largely by common factors. What this analysis means is that any generalized suppression of compensation due to the Agreements Page 5 Expert Report of Edward E. Leamer, Ph.D. 325 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page10 of 81 CONFIDENTIAL 10/1/2012 would be experienced by all or nearly all members of the All-Employee Class and Technical Employee Class. (d) Finally, I have concluded that standard economic methods are capable of reliably quantifying the aggregate amount of reduced compensation caused by the Agreements to the All-Employee Class and Technical Employee Class, respectively. 12. III. The analyses described in this report are performed for the purpose of demonstrating the availability of proof and statistical methodologies common to members of the All-Employee Class and the Technical Employee Class capable of showing that members of each class suffered suppressed compensation due to the Agreements, and capable of quantifying that harm. I understand that discovery has not yet been completed and that further evidence might emerge that is relevant to my analysis. I reserve the right to consider any such evidence and its impact, if any, on the analysis I have proposed. Case and Background A. Defendants 13. 5 Adobe, founded in 1982, is a technology company with its headquarters in San Jose, California.5 Adobe is well known for a number of software products including Acrobat, Photoshop, and Illustrator. It is also known for its Flash media platform which it acquired in late 2005 as part of its acquisition of Macromedia, which had been the publisher of Dreamweaver and the Flash media platform.6 In its 2009 fiscal year, Adobe had nearly $3 billion in revenues.7 Adobe, “Corporate Overview,” http://www.adobe.com/aboutadobe/pressroom/pdfs/profile.pdf. Adobe, “Adobe completes acquisition of Macromedia,” http://www.adobe.com/aboutadobe/invrelations/adobeandmacromedia_faq.html. 6 7 Adobe Systems Incorporated, “2009 Form 10-K,” January 22, 2010 at pp.52. Page 6 Expert Report of Edward E. Leamer, Ph.D. 326 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page11 of 81 CONFIDENTIAL 10/1/2012 14. Apple, founded in 1976, is a technology company that is headquartered in Cupertino, California.8 The company is a market leader in several consumer electronics market segments with its iPad, iPhone, and iPod product lines.9 Apple has been a leader in the digital music distribution market with its iTunes service.10 Apple’s 2011 total revenues exceeded $108 billion.11 15. Google, founded in 1998, is a technology company headquartered in Mountain View, California.12 The company is the leading internet search provider.13 The company went public in 2004. Google’s revenues reached nearly $38 billion in 2011.14 16. Intel is a technology company, headquartered in Santa Clara, California. The company was founded in 1968 and is the world’s largest semiconductor chip maker.15 Intel is most well known for its x86 series of microprocessors, found in most personal computers today16 but the company also markets other integrated Time, “Top 10 Apple Moments,” http://www.time.com/time/specials/packages/article/0,28804,1873486_1873491_1873530,00.html. 8 Reuters,“Company Profile for Apple Inc,” http://in.reuters.com/finance/stocks/companyProfile?symbol=AAPL.O. 9 Whitney, Lance,“ iTunes reps 1 in every 4 songs sold in U.S,” CNET News, August 18, 2009, http://news.cnet.com/8301-13579_3-10311907-37.html. 10 11 Apple Inc., “2011 Form 10-K,” October 26, 2011 at pp.24. 12 Google, “Our history in depth,” http://www.google.com/about/company/history/. Google, “Google Launches World’s Largest Search Engine,” June 26, 2000, McGee, Matt, “Google Still No. 1 Search Engine On Earth,” Searchengineland, August 31, 2009 and Google Inc., “2010 Annual Report,” February 11, 2011 at p.25. 13 Google, “2012 Financial Tables – Investor Relations – Google,” http://investor.google.com/financial/tables.html. 14 Intel, “Intel Company Information,” http://www.intel.com/content/www/us/en/companyoverview/company-facts.html. 15 Edwards, Benj, “Birth of a Standard: The Intel 8086 Microprocessor,” PCWorld, June 16, 2008, http://www.pcworld.com/article/146957-3/birth_of_a_standard_the_intel_8086_microprocessor.html. 16 Page 7 Expert Report of Edward E. Leamer, Ph.D. 327 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page12 of 81 CONFIDENTIAL 10/1/2012 circuits and devices related to communications and computing.17 Intel had revenue of $54 billion in 2011.18 17. Intuit is a technology company, headquartered in Mountain View, California.19 The company was founded in 1983 and is known for its QuickBooks, Quicken and TurboTax software products. In 2011 the company revenues exceeded $3.8 billion. 18. Lucasfilm is a film production company known for its computer animation expertise, headquartered in San Francisco, California. Founded in 1971, the company is best known for producing the Star Wars films, as well as other box office hits, including the Indiana Jones franchise. Lucasfilm has seven different divisions: Industrial Light & Magic, LucasArts, Lucasfilm Animation, Skywalker Sound, Lucas Licensing, Lucas Online and Lucasfilm Singapore. Lucasfilm Animation has studios both in Marin County, California and Singapore. 19. Pixar is a computer animation film studio headquartered in Emeryville, California.20 The company was founded in 1979 as Graphics Group and later renamed to Pixar in 1986.21 In 2006 the company was acquired by Disney for approximately $7.4 billion.22 Prior to the acquisition, in 2005 Pixar had annual revenues of nearly $290 million.23 17 Intel, “Intel Products,” http://www.intel.com/p/en_US/products/productsbyintel. 18 Intel Corporation, “2011 Annual Report,” February 23, 2012 at p.2. 19 Intuit, “Intuit: Corporate Profile,” http://about.intuit.com/about_intuit/profile/. 20 Pixar, “Pixar: Welcome,” http://www.pixar.com/about. 21 Pixar, “Pixar History: 1986,” http://www.pixar.com/about/Our-Story. Pixar, “Pixar History: 2006,” http://www.pixar.com/about/Our-Story and “Disney buying Pixar for $7.4 billion,”NBC News, 1/25/2006, http://www.msnbc.msn.com/id/11003466/ns/businessus_business/t/disney-buying-pixar-billion. 22 23 Pixar, “2005 10-K,” March 7, 2006 at p.37. Page 8 Expert Report of Edward E. Leamer, Ph.D. 328 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page13 of 81 CONFIDENTIAL 10/1/2012 B. The Non-Compete Agreements 20. I have studied the allegations of the Plaintiffs’ complaint and evidence of the Non-Compete Agreements. I have not been asked to form an opinion on the ultimate question of whether or not the Defendants reached anticompetitive agreements or should be liable under the law. However, I have reviewed evidence about the agreements and their enforcement to understand their scope and duration for purposes of my analysis, and to assure myself that certain assumptions I have made fit the circumstances. 21. Based on that review, I understand the time periods of the alleged NonCompete Agreements to have been as follows. Figure 1: Periods of the Alleged Collusive Agreements Defendants (1) End Date25 (3) Adobe-Apple Apple-Pixar Apple-Google Google-Intel Google-Intuit Lucasfilm-Pixar 22. Start Date24 (2) May 2005 April 2007 February 2005 March 2005 June 2007 Before 2000 March 2009 March 2009 March 2009 March 2009 March 2009 March 2009 I also understand that Defendants entered into several additional agreements. Those agreements include: (1) an agreement between Pixar and Intel that began in approximately October 2008,26 and (2) agreements Apple apparently had with See ADOBE_001096-097 and 231APPLE002145 (Adobe-Apple); PIX00003419 (Apple-Pixar); 231APPLE002140 and 231APPLE073139 (Apple-Google); GOOG-HIGH TECH-00008281-284 (GoogleIntel); GOOG-HIGH TECH-00008342-350 (Google-Intuit); and Deposition of James Morris, August 3, 2012 at p. 93 (Lucasfilm-Pixar). 24 These dates are based on the notice send to a party to the alleged agreement. I understand that Apple and Google each received a Civil Investigative Demand (“CID”) on March 13, 2009. Pixar received a CID on May 27, 2009. 25 See PIX00015306 (Intel agreed with Pixar that it “will not proactively pursue any Pixar employee going forward.”) The agreement also included a no-hire without permission provision that prohibited Intel from hiring Pixar employees, regardless of whether a Pixar employee contacted Intel first, unless the head of Pixar 26 Page 9 Expert Report of Edward E. Leamer, Ph.D. 329 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page14 of 81 CONFIDENTIAL 10/1/2012 Intel, Intuit, and Lucasfilm that mirrored Apple’s agreements with Adobe, Pixar, and Google.27 Figure 2: Relationships of the Alleged Agreements Among Defendants 23. All of the Non-Compete Agreements covered all employees of the respective companies, regardless of employee geography, job function, product group, or time period. Each of the Agreements prohibited cold-calling, meaning that the parties agreed not to solicit each other’s employees in any manner. This agreement applied to all recruiters who were either directly employed by or were approved the hire. See also, 76577DOC000464 (“We cannot recruit (including calling up, emailing, or enticing in any way) current Pixar employees to come work for Intel. If a Pixar employee applies without being recruited by Intel, contact Pat Gelsinger [a Senior VP at Intel] and explain to him a Pixar employee (provide the candidates [sic] name) has applied to Intel without being recruited and he will contact the CEO of Pixar for approval to hire.”). See 231APPLE041661 and 231APPLE041662 (Apple’s “Hands Off (Do Not Call List)” included every Defendant). 27 Page 10 Expert Report of Edward E. Leamer, Ph.D. 330 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page15 of 81 CONFIDENTIAL 10/1/2012 headhunters hired by the agreeing firms.28 Some of the agreements included additional terms, such as:   28 Pre-notify: The parties agreed to notify each other prior to making an offer to hire an employee at the other firm.30  24. Do not hire: The parties agreed not to make employment offers to employees of the other firm without specific approval from the current employer’s chief executive.29 No counteroffer. The initiating firm that makes an offer to an employee of the other firm agreed not to improve its initial offer if the offer was matched by the other firm.31 In other words, “no bidding wars.”32 The sections below describe each of the agreements among the seven Defendants as I understand them. See e.g., 231APPLE001164, GOOG-HIGH TECH-00023500-601 at 520-528., and PIX00000400. When present, this provision applied even when an employee initiated contact. See, e.g., 76577DOC000464. Even if certain agreements may not have begun with this express provision, they often operated in this manner in practice. For example, Pixar and Google sought Steve Jobs’s permission before making offers to Apple employees. See PIX00006025; 231APPLE002151. Apple refused to consider Adobe employees unless they first left employment with Adobe. See 231APPLE080776 (“This is a response I received from an ADOBE employee who applied for a position through our job posting site. I called him to ensure he is still an ADOBE employee, explained our mutual agreement / guidelines, and asked that he contact me should his employment with ADOBE terminate, but at this time I am unable to continue exploring with him. . . . I do not want anything in ‘writing’.”) Apple also attempted to enter into a “no hire” agreement with Palm, which Palm’s CEO Ed Colligan rejected. See PALM00005 – 008 at 006 and PALM00022 – 027 at 024. See also, 231APPLE002153 - 154, and 231APPLE002214. 29 30 See e.g., PIX00000400; GOOG-HIGH TECH-00056790. 31 See PIX00000400; LUCAS00009252. See PIX00004051 (“We just won’t get into bidding wars” for employees.); LUCAS00013507 (“We have agreed we want to avoid bidding wars.”). 32 Page 11 Expert Report of Edward E. Leamer, Ph.D. 331 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page16 of 81 CONFIDENTIAL 10/1/2012 1. Pixar-Lucasfilm 25. I understand that a Non-Compete Agreement existed between Pixar and Lucasfilm for many years, beginning well before the year 2000.33 In addition to not Cold-Calling each other’s employees, each company agreed to inform the other of any offer made to an employee of the other company pursuant to an unsolicited application made by the employee.34 The agreements further specified that in the case of such an unsolicited application the company making the job offer would make only one offer, and would not improve it in response to a counter-offer by the employee’s current employer.35 The agreement covered all employees.36 On May 27, 2009, the DOJ issued a Civil Investigative Demand (“CID”) to Pixar.37 I have been asked to assume the agreement ended on that date. 26. Jim Morris, Pixar’s General Manager and former head of Lucasfilm’s Industrial Light and Magic division, described the agreement as follows in a videotape created on December 9, 2008: “We have an anti-poach clause between the Lucas companies and -- and this company. We don’t -- we don’t recruit from one another, we don’t call -- if the people want to go from one company to the other, we, you know, find a way to let that happen. But we have a -- sort of a gentleman’s agreement that we’ve honored pretty well here for the last many years.”38 27. The “gentleman’s agreement” concerned all employees of the companies, had no geographic limit, and had no expiration date.39 Pixar and Lucasfilm provided See Deposition of Lori McAdams, August 2, 2012 at p. 127:4-16 (“Well, I was at Lucasfilm from 1984 through 1998, and that understanding was in place at that time.”); p. 132:15 (“[The agreement] had always been there.”) and Deposition of James Morris, August 3, 2012 at p. 931. 33 34 PIX00002328-329 at 328 and PIX00000038-039; PIX00000400 and PIX00006057. 35 PIX00002328-329 at 328; PIX00000400. 36 PIX00002328-329 at 328. 37 See PIX00001958. 38 See Deposition of Jim Morris, August 3, 2012 at p. 113:10-16. 39 See Deposition of Jim Morris, August 3, 2012 at pp. 126:20-127:10; Deposition of Lori McAdams, August Page 12 Expert Report of Edward E. Leamer, Ph.D. 332 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page17 of 81 CONFIDENTIAL 10/1/2012 the written terms of the agreement to management and certain senior employees with relevant hiring or recruiting responsibilities.40 28. It appears the companies abided by this agreement41 and viewed it as important to avoid competing for each other’s workers.42 29. The executives of these firms also clearly viewed containing labor costs as a major priority.43 30. Pixar’s President Ed Catmull clearly understood the structural effect of competition on wages. As he observed in an email to a Disney executive: “Every time a studio tries to grow rapidly, it seriously messes up the pay structure . . . by offering higher salaries to grow at the rate they desire, people will hear about it and leave. We have avoided wars up here in Northern California because all of the companies up here – Pixar, ILM [Lucasfilm], Dreamworks, and a couple of smaller places – have conscientiously avoided raiding each other.”44 2, 2012 at p. 160:23-25. See also, Deposition of Donna Morris, August 21, 2012 at pp. 226:22-227:5 and Deposition of Mark Bentley, August 23, 2012 at pp. 17:21-18:2. See Deposition of Lori McAdams, August 2, 2012 at p. 145:5-17; PIX00002262-64 (“I created it [summary of no-solicitation agreement] to give to the recruiting team so they would know what the gentleman’s agreement was.”). 40 Deposition of Lori McAdams, August 2, 2012 at pp. 149:17-151:17 (PIX0009416); pp. 135:12-137:1 (PIX00003640). 41 42 Deposition of Lori McAdams, August 2, 2012 at pp. 135:12-139:1; PIX00003640 (“[T]hey got really mad that we hired Rob Rieders.”). 43 PIX00009216-217 at 217. (“I know you are adamant about keeping a lid on rising labor costs”). 44 PIX00000229. Page 13 Expert Report of Edward E. Leamer, Ph.D. 333 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page18 of 81 CONFIDENTIAL 10/1/2012 2. The Apple Non-Compete Agreements a. Adobe 31. As of May 2005, the CEOs of Apple and Adobe had entered into an agreement that their respective companies would not recruit each other’s employees.45 This agreement covered all employees.46 Apple placed Adobe on its “Do Not Call” list and Adobe placed Apple on its “Companies that are off limits” list, both of which instructed recruiters not to solicit employees from the listed companies and to inform each other if senior executives of each company were actively seeking employment at the other.47 On March 13, 2009, the DOJ issued CIDs to Apple and Adobe.48 I have been asked to assume the agreement ended on that date. 32. On May 26, 2005, Steve Jobs complained to Adobe CEO Bruce Chizen that Adobe was recruiting Apple employees.49 Chizen responded, “I thought we agreed not to recruit any senior level employees … I propose we keep it that way. Open to discuss. It would be good to agree.”50 Jobs replied: “OK, I’ll tell our recruiters that they are free to approach any Adobe employee who is not a Sr. Director or VP. Am I understanding your position correctly?” Chizen appeared to recognize the threat and capitulated: “I’d rather agree NOT to actively solicit any employee from either company . . . If you are in agreement I will let my folks know.” The next day, Adobe HR Vice President Theresa Townsley announced to her recruiting team, “Bruce and Steve Jobs have an 45 231APPLE002145. 46 231APPLE002145. 47 See 231APPLE001164 -165 and ADOBE_001096-097. 48 See 231APPLE003695 and ADOBE_007392. 49 50 See 231APPLE002143. See 231APPLE002143. Page 14 Expert Report of Edward E. Leamer, Ph.D. 334 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page19 of 81 CONFIDENTIAL 10/1/2012 agreement that we are not to solicit ANY Apple employees, and vice versa.”51 Mr. Chizen forwarded Ms. Townsley’s email to Steve Jobs. 52 33. I understand that the two firms abided by the agreement.53 34. To ensure compliance with the agreement, Apple instructed its recruiting personnel to adhere to the agreement.54 Adobe, in turn, placed Apple on its “Companies that are off limits” list, which instructed Adobe employees not to cold call Apple employees.55 b. Google 35. 51 I understand that by February 2005 Apple and Google agreed that the two companies would not “cold call” each other’s employees.56 The agreement covered all employees.57 Apple placed Google on its “Do Not Call” list and Google placed Apple on its “Do Not Cold Call” list, both of which instructed recruiters not to solicit employees from the listed companies.58 On March 13, 2009, the DOJ issued CIDs to Apple and Google.59 I have been asked to assume the agreement ended on that date. See 231APPLE002145 (emphasis in original). 52 See 231APPLE002145. 53 See ADOBE_001095. 231APPLE002145 (“Please ensure all your worldwide recruiters know that we are not to solicit any Adobe employee.”); 231APPLE080776-777 (Apple recruiter tells Adobe applicant that she cannot consider him until he leaves Adobe, even though “the agreement is not to ‘poach’ candidates, that meaning that if you directly apply to Apple, there should be no issue.”); ADOBE_007186 (“Apple would be a great target to look into, unfortunately Bruce and Steve Jobs have a gentleman’s agreement not to poach each other’s talent . . . .”). 54 55 See ADOBE_00421-422. 56 See 231APPLE002140 and 231APPLE073139. See also, GOOG-HIGH TECH-00008002-005 at 004. 57 GOOG-HIGH TECH-00008002-005 at 004. 58 See GOOG-HIGH TECH-00008002-005 and GOOG-HIGH TECH-00023500-601 at 520-521. 59 See 231APPLE003695 and GOOG-HIGH TECH-00024585. Page 15 Expert Report of Edward E. Leamer, Ph.D. 335 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page20 of 81 CONFIDENTIAL 10/1/2012 36. On February 18, 2005, Intuit Chairman and Apple Board Member Bill Campbell reached out to Google CEO Eric Schmidt regarding Google’s recruitment of Apple employees.60 Mr. Campbell reported back to Steve Jobs: “Eric told me that he got directly involved and firmly stopped all efforts to recruit anyone from Apple.”61 That same day, Apple’s head of HR Danielle Lambert reported to her recruiting staff: “Please add Google to your ‘hands-off’ list. We recently agreed not to recruit from one another so if you hear of any recruiting they are doing against us, please be sure to let me know. Please also be sure to honor our side of the deal.”62 37. Later that year, Arnnon Geshuri, Google’s head of recruiting, was asked to create a formal “Do Not Cold Call” list regarding companies, including Apple, that had “special agreements” with Google to eliminate Cold-Calling. The draft was presented to Google’s Executive Management Group (“EMG”), a committee consisting of Google’s senior executives, including Eric Schmidt, Larry Page, Sergey Brin, and Shona Brown (Google’s head of HR). Mr. Schmidt approved the list.63 Mr. Geshuri added or removed a company from Google’s Do Not Call when instructed to do so by a member of the EMG.64 38. Once the EMG approved it, Mr. Geshuri formalized the “Special Agreement Hiring Policy: Protocol for ‘Do Not Cold Call’ and ‘Sensitive’ Companies,” and ensured that all of Google’s hundreds of recruiters adhered to its terms.65 60 See 231APPLE002140. 61 See 231APPLE002140. 62 See 231APPLE073139. See GOOG-HIGH TECH-00007725 (Mr. Geshuri sent the draft “Do Not Call” list to Ms. Brown, who responded: “I would like to finalize with you Monday AM, and then present in EMG . . . .”; GOOG-HIGH TECH-00007731 (Mr. Schmidt approved the list on October 4, 2005: “This looks very good.”); Deposition of Arnnon Geshuri, August 17, 2012 at pp. 161:2-167:8. 63 Deposition of Arnnon Geshuri, August 17, 2012 at p. 172:6-8 (Q: And who would tell you whether to put a company on or off of the do-not-call list? A: It was usually an EMG member.”) 64 GOOG-HIGH TECH 00008283 and GOOG-HIGH TECH-00008342 (example iterations of the Do Not Call list); Deposition of Arnnon Geshuri, August 17, 2012 at p. 170:19-22 (“I made sure the team was -- was definitely aware of this protocol”); Deposition of Arnnon Geshuri, August 17, 2012 at pp. 43:20-44:10 (from 65 Page 16 Expert Report of Edward E. Leamer, Ph.D. 336 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page21 of 81 CONFIDENTIAL 39. 10/1/2012 I have reviewed evidence of specific instances in which both firms adhered to the agreement.66 In one case, compliance meant terminating a Google recruiter who violated the agreement.67 Google referred to this kind of enforcement as an “Eric [Schmidt] firedrill.”68 c. Pixar 40. In April 2007 the directors of human resources for Apple and Pixar agreed to a Non-Compete Agreement that mirrored the terms of the agreement between Lucasfilm and Pixar.69 Apple placed Pixar on its “Do Not Call” list, which instructed recruiters not to solicit employees from the listed companies, and Pixar instructed its human resource personnel to abide by the agreement. 41. I understand that historically Pixar and Apple restricted employees from moving from one company to another during the period of time when Steve Jobs was an executive of Apple and a direct owner of Pixar. On March 13, 2009, the DOJ issued a CID to Apple.70 I have been asked to assume the agreement ended on that date. 42. Beginning no later than 2004, Pixar sought Steve Jobs’ permission before making an offer of employment to an Apple employee, regardless of whether 2004 to 2009, Mr. Geshuri grew Google’s recruiting operations from 40 recruiters to 900, which allowed Google to hire at a rate of “ people a week.”). 66 See 231APPLE002149; GOOG-HIGH TECH-0007574-576. GOOG-HIGH TECH-00009454; GOOG-HIGH TECH-00000107 (In an email in which Mr. Schmidt was copied: Mr. Geshuri: “the sourcer who contacted this Apple employee should not have and will be terminated within the hour. We are scrubbing the sourcer’s records to ensure she did not contact anyone else.” Ms. Brown: “Appropriate response. Please make a public example of this termination with the group. Please also make it a very strong part of new hire training for the group. I want it clear that we have a zerotolerance policy for violating our policies. This should (hopefully) prevent future occurrences.”); Deposition of Arnnon Geshuri, August 17, 2012 at pp. 214:7-215:20. 67 GOOG-HIGH TECH-00023106 and GOOG-HIGH TECH-0024458; Deposition of Arnnon Geshuri, August 17, 2012 at pp. 255:3-260:14. 68 At the time of these agreements Steve Jobs was the largest shareholder of Walt Disney, to which he had sold Pixar in 2006 and he sat on Disney’s board of directors. See PIX00003978. 69 70 See 231APPLE003695. Page 17 Expert Report of Edward E. Leamer, Ph.D. 337 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page22 of 81 CONFIDENTIAL 10/1/2012 the Apple employee applied to Pixar without being solicited. For example, on February 8, 2004, Rob Cook, Pixar’s Vice President of Software Engineering, wrote to Steve Jobs: “Steve, an Apple employee applied for the job of project coordinator, which is basically an administrative assistant to our project managers. . . . Would it be OK for us to make her an offer?” Steve Jobs responded: “Yea, it’s fine.” Mr. Cook forwarded Steve Jobs’s email to Mr. Catmull, who responded: “The key is to stay away from the engineers.”71 Ten days after this exchange, Mr. Catmull emailed Steve Jobs regarding entering into a no-recruit agreement to eliminate competition with Sony: “our people are become [sic] really valuable and we need to nip this in the bud.”72 The next year, in November 2005, Pixar recruiter Howard Look stated that Pixar was struggling to find candidates, but “of course cannot recruit out of Apple.”73 43. On April 30, 2007, Apple and Pixar formalized their understanding and expanded it to all employees with a call between Ms. McAdams of Pixar and Danielle Lambert, Apple’s head of HR. Apple and Pixar modeled their agreement on the “gentlemen’s agreement” Pixar had with Lucasfilm. Ms. McAdams told her recruiting team about the “Apple Gentleman’s agreement”: “I just got off the phone with Danielle Lambert, and we agreed that effective now, we’ll follow a gentlemen’s agreement with Apple that is similar to our Lucasfilm agreement. That is . . . we won’t directly solicit any Apple employee (including outside recruiters if we use them) . . . Danielle will ask her Recruiting team to follow the same procedure . . . .”74 44. After entering into the agreement, senior executives of both Pixar and Apple monitored compliance and policed violations. For example, Lori McAdams testified that Steve Jobs got angry if Pixar hired an Apple employee.75 When 71 See PIX00006025. 72 See PIX00006023. 73 See PIX0003600. 74 See PIX00004883; emphasis added; Deposition of Lori McAdams, August 2, 2012 at pp. 182:5-183:9. 75 See Deposition of Lori McAdams, August 2, 2012 at p. 159:4-9. Page 18 Expert Report of Edward E. Leamer, Ph.D. 338 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page23 of 81 CONFIDENTIAL 10/1/2012 asked whether Pixar would consider hiring an Apple employee who had expressed interest in Pixar, Ed Catmull replied, “[Steve] will want the name of the guy. My guess is that Steve will approve it if he knows that he is going to lose him, but we would have to go through the step of Apple knowing what was happening.”76 To ensure compliance with the agreement, Pixar instructed its human resources personnel to adhere to the agreement and to preserve documentary evidence establishing that Pixar had not actively recruited Apple employees.77 Apple, in turn, placed Pixar on its internal “Do Not Call List,” which instructed Apple employees not to cold call Pixar employees.78 3. The Google Non-Compete Agreements a. Apple 45. Google’s Non-Compete Agreement with Apple is described above. b. Intel 46. Effective March 6, 2005, Google and Intel entered into a Non-Compete Agreement.79 Multiple documents confirm this agreement.80 The agreement covered all Google and Intel employees. Google placed Intel on its “Do Not Cold Call” list, which instructed recruiters not to solicit employees from the listed companies, and Intel instructed its human resource personnel to abide by the agreement. On March 13, 2009, the DOJ issued a CID to Google.81 I have been asked to assume the agreement ended on that date. 76 PIX00002210. 77 PIX0003629-630. 78 See 231APPLE042669 and 231APPLE041662. 79 See GOOG-HIGH TECH-00008281-284 at 283. See 76556DOC000003, 76614DOC010212, 76526DOC000007, 76526DOC000011, and GOOG-HIGH TECH-00056879. 80 81 See GOOG-HIGH TECH-00024585. Page 19 Expert Report of Edward E. Leamer, Ph.D. 339 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page24 of 81 CONFIDENTIAL 10/1/2012 47. On April 16, 2007, Intel C.E.O. Paul Otellini wrote to an Intel recruiter, “I have an unofficial no poaching policy with [Google.]”82 On June 4, 2007, Eric Schmidt wrote Otellini re “hiring”: “I checked as to our recruiting policy with Intel. ‘Intel has been listed on the Do Not Call List since the policy was created. No one in staffing directly calls, networks, or emails into the company or its subsidiaries looking for talent.’ Hopefully there are no exceptions to this policy and if you become aware of this please let me know immediately!”83 Otellini forwarded the email to Patty Murray, Intel’s Senior Vice President and Director of HR: “FYI . . . . Do not fwd.”84 48. Google’s formal “Do Not Cold Call” list included Intel along with Apple, as “companies [that] have special agreements with Google,” and states the same “Effective” date for both Apple and Intel: “March 6, 2005.”85 49. The agreement was enforced by the chief executives of the two companies. Intuit’s Chairman, Bill Campbell, was also apparently involved in the agreement between Google and Intel. For example, in August of 2006, Campbell reached an agreement with Google’s Jonathon Rosenberg (Google’s Senior Vice President of Product Management) that Google should impose additional restrictions beyond no solicitation: they agreed that Google would call Otellini before making an offer to an Intel employee, regardless of whether the Intel employee first approached Google.86 82 See 76526DOC000007. 83 See 76614DOC010212. Two days later, in an email titled “global gentleman agreement with Google,” an Intel recruiter asked Otellini and another senior executive, “Are either of you aware of any agreement with Google that prohibits us from recruiting Google’s senior talent?” See 76526DOC000011. Otellini replied, “Let me clarify. We have nothing signed. We have a handshake ‘no recruit’ between eric and myself. I would not like this broadly known.” See 76526DOC000011. 84 GOOG-HIGH TECH-00008281-284 at 283; GOOG-HIGH TECH-00056879 (“Since the beginning of the Do Not Call List, Intel has been listed.”). 85 GOOG-HIGH TECH-00056790 (Rosenberg: “Campbell and I already discussed this [talking to Intel before making an offer to an Intel employee] and agreed that either way [whether Intel was treated as a “Do Not Call” company, or a “sensitive” company] I should give a courtesy call to Paul Otellini. I’m meeting with 86 Page 20 Expert Report of Edward E. Leamer, Ph.D. 340 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page25 of 81 CONFIDENTIAL 10/1/2012 c. Intuit 50. In June 2007, Google and Intuit entered into a Non-Compete Agreement between Google and Intuit.87 The agreement also covered all employees. Google placed Intuit on its “Do Not Cold Call” list, which instructed recruiters not to solicit employees from the listed companies, and Intuit instructed its human resource personnel to abide by the agreement. On March 13, 2009, the DOJ issued a CID to Google.88 I have been asked to assume the agreement ended on that date. 51. On June 6, 2007, Google Recruiting Director Arnnon Geshuri wrote Eric Schmidt: “During a brief conversation with Shona and Bill Campbell, Bill requested that Intuit be added fully to the Do Not Call list. Currently, our nonsolicit policy only covers 18 Intuit employees . . . The change to our Do Not Call policy will make our hands-off approach to Intuit explicit and ensure clarity.”89 By June 12, 2006, Intuit was added fully to the list.90 52. I have reviewed specific evidence of enforcement of the agreement, including enforcement by Campbell himself.91 [the Intel candidate] tomorrow and I will ask him how he wants to handle communication to Intel management before we even get to the stage of specifically discussing an offer.”). See GOOG-HIGH TECH-00009764. There is some indication an agreement may have existed earlier. In May 2006, Google employees discussed possibly contacting a candidate from Intuit, finally deciding that “would effectively be a cold call, so I’ll ask martha j not to contact him.” GOOG-HIGH TECH-00007696 – 697 at 696. 87 88 See GOOG-HIGH TECH-00024585. 89 GOOG-HIGH TECH-00009764. GOOG-HIGH TECH-00007715; GOOG-HIGH TECH-00009391 (“please update the DNC list to now include Intuit 100% do not call.”). 90 GOOG-HIGH TECH-00057458. See also, GOOG-HIGH TECH-00058235 (email from Bill Campbell to Google HR Director Lazlo Bock asking “Can we please not target Intuit”). 91 Page 21 Expert Report of Edward E. Leamer, Ph.D. 341 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page26 of 81 CONFIDENTIAL 10/1/2012 4. Department of Justice Investigation and the End of the Collusion 53. On June 3, 2009, the New York Times published an article indicating that the DOJ had begun an investigation into the Defendants’ hiring practices and the alleged Non-Compete Agreements in particular.92 I understand that by the end of March 2009, the DOJ had informed the defendants of the investigation. I have assumed for this analysis that, as of that date the agreements between the defendants ceased to have an effect on their recruiting and hiring activities. C. Named Plaintiffs 54. As described above, I have been asked to consider the effect of the NonCompete Agreements on the All-Employee Class of salaried employees (and the Technical Employee Class). The members of each proposed class worked for a Defendant at a time when that Defendant was a party to at least one such Agreement (excluding retail employees, corporate officers, members of the boards of directors, and senior executives). Helft, Miguel, “Unwritten Code Rules Silicon Valley Hiring,” The New York Times, June 3, 2009, http://www.nytimes.com/2009/06/04/technology/companies/04trust.html?_r=1. 92 Page 22 Expert Report of Edward E. Leamer, Ph.D. 342 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page27 of 81 CONFIDENTIAL 10/1/2012 Figure 3: Class Employee Summary Defendant Agreement Period Number of Class Members Total Class Compensation (1) (2) (3) (Dollars) (4) Adobe Apple Google Intel Intuit Lucasfilm Pixar 05/05-03/09 02/05-03/09 02/05-03/09 03/05-03/09 06/07-03/09 01/01-03/09 01/01-03/09 7,056 $ 3,035,176,142 2,081,658,505 109,048 TOTAL 7,186 $ 52,047,039,447 Note: Columns (3) and (4) are calculated using the Class Periods described in Paragraphs 8 and 9, above. Source: Defendants' employee compensation data; SEC filings. Figure 4: Technical Employee Class Summary Defendant Agreement Period Number of Class Members Total Class Compensation (1) (2) (3) (Dollars) (4) Adobe Apple Google Intel Intuit Lucasfilm Pixar 05/05-03/09 02/05-03/09 02/05-03/09 03/05-03/09 06/07-03/09 1 3,601 $ 1,740,210,006 3,236 1,006,035,578 59,550 $ 32,848,992,686 01/01-03/09 01/01-03/09 TOTAL Note: Columns (3) and (4) are calculated using the Class Periods described in Paragraphs 8 and 9, above. 1 Missing job title information for 2005. Source: Defendants' employee compensation data; SEC filings. 55. I understand the following named plaintiffs are seeking to serve as class representatives for the proposed All-Employee Class or Technical Employee Class : Page 23 Expert Report of Edward E. Leamer, Ph.D. 343 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page28 of 81 CONFIDENTIAL 10/1/2012 a. b. Mark Fichtner who worked for Intel as a software engineer from May of 2008 through May 2011; c. Siddharth Hariharan who worked for Lucasfilm as a software engineer from January 8, 2007 through August 15, 2008; d. Brandon Marshall, who worked for Adobe as a software production quality specialist from July 2006 through December 2006; and e. 56. Michael Devine who worked for Adobe from October 2006 through July 7, 2008 as a computer scientist for Adobe Systems; Daniel Stover, who worked for Intuit as a Web Marketing Representative, Web Developer, and Software Engineer from July 2006 through December 2010. I have summarized the employment histories of these individuals as contained in Defendants’ data. The employment histories of the five named plaintiffs are reported in Figure 5. Page 24 Expert Report of Edward E. Leamer, Ph.D. 344 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page29 of 81 CONFIDENTIAL 10/1/2012 Figure 5: Named Plaintiffs’ Employment Histories Name Plaintiff's Employment Profile Summary Separation Base Annual Supplemental Name Year Employer Title Hire Date Date Salary Compensation1 (1) (2) (3) (4) (5) (6) (7) 2006 2007 2008 2009 INTUIT INTUIT INTUIT INTUIT WEB MARKETING REP 2 WEB DEVELOPER 2 SOFTWARE ENGINEER SW ENGINEER 2 Brandon Marshall 2006 ADOBE Mark Fichtner 2001 2002 2003 2004 2005 2006 2008 2009 2010 2011 2006 2007 2008 (Dollars) Daniel Stover Michael Devine Siddharth Hariharan 1 10/30/2006 10/30/2006 10/30/2006 10/30/2006 12/3/2009 75,000 83,500 91,300 94,000 SW PROD QUALITY SPEC 1 7/31/2006 12/9/2006 68,000 5,895 INTEL INTEL INTEL INTEL INTEL INTEL INTEL INTEL INTEL INTEL SOFTWARE ENGINEER, SR SOFTWARE ENGINEER, SR SOFTWARE ENGINEER, SR SOFTWARE ENGINEER SOFTWARE ENGINEER SOFTWARE ENGINEER SOFTWARE ENGINEER SOFTWARE ENGINEER SOFTWARE ENGINEER SOFTWARE ENGINEER 7/12/1993 7/12/1993 7/12/1993 7/12/1993 7/12/1993 7/12/1993 7/12/1993 7/12/1993 7/12/1993 7/12/1993 6/1/2011 84,250 84,250 84,250 86,782 95,132 100,362 108,000 108,000 110,160 111,290 67,461 40,176 25,101 36,592 38,299 48,189 14,013 30,501 42,078 35,973 ADOBE ADOBE ADOBE COMPUTER SCIENTIST, SW DEV 4 9/25/2006 COMPUTER SCIENTIST, SW DEV 4 9/25/2006 COMPUTER SCIENTIST, SW DEV 4 9/25/2006 7/8/2008 110,000 113,135 118,226 21,222 33,405 3,445 8/15/2008 85,000 88,335 17,000 - 2007 LUCASFILM SOFTWARE ENGINEER 2008 LUCASFILM SOFTWARE ENGINEER 1/8/2007 1/8/2007 $ (8) 11/8/2006 $ 4,129 19,765 83,877 38,553 Supplemental compensation includes bonus, overtime compensation, options values and restricted stock values Source: Defendants' employee compensation data; SEC filings D. Background on Defendants’ Recruiting and Hiring Practices 57. Defendants classified potential job candidates as either “passive” or “active.”93 Active candidates were searching for employment and could be expected to discover posted opportunities (e.g., an active candidate might apply through the company’s website). Passive candidates were not searching for new 76550DOC000014-095 at 024, LUCAS00013673-703 at 683, GOOG-HIGH TECH-00039446-581 at 451 and 76566DOC000005-026 at 010. 93 Page 25 Expert Report of Edward E. Leamer, Ph.D. 345 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page30 of 81 CONFIDENTIAL 10/1/2012 opportunities but might be interested if the candidate learned of a good job opportunity.94 58. 59. Many companies, including the Defendants, actively pursue Cold-Calling strategies. For example, the Competitive Intelligence Group at Google created a “Product Matrix,” profiling competitors and highlighting areas in which these competitors have employees that would be useful to Google, naming ColdCalling as a method to “strategically reach, engage and close the best talent in the world.”97 60. Intuit recruiters were expected to use Cold-Calling as a recruiting technique.98 Google identified Cold-Calling as an activity of its recruiters (“sourcers”).99 61. 94 The Defendants used several types of methods for uncovering (or “sourcing”95) passive candidates, including referrals.96 The initial contact to a passive candidate is called “Cold-Calling.” In preparation for Cold-Calling, the Defendants profiled their competitors, looking for job categories and titles that corresponded to the positions to be filled.100 Cold-Calling recruiters would then approach employees who fit into those categories to determine their potential interest, which could be followed Deposition of Donna Morris, August 21, 2012 at pp. 106:22-107:19 and Exhibit 212. Intel defined sourcing as, “the identification and uncovering of candidates through proactive recruiting techniques.” Sourcing channels included complex internet searches, networking, job fairs and searching through previous applications. Companies can also use external recruiting agencies to find potential candidates 76550DOC000014-095 at 19 and 23 and 76545DOC000021-051 at 23. 95 96 76550DOC000014-095 at 023 and LUCAS00004690 at 692-694. 97 GOOG-HIGH-TECH-00054775. 98 See INTUIT_001661-664 at 663. 99 See GOOG-HIGH TECH-00007950-973 at 971. 100 See GOOG-HIGH-TECH-00055116 and GOOG-HIGH-TECH-00055413-414. Page 26 Expert Report of Edward E. Leamer, Ph.D. 346 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page31 of 81 347 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page32 of 81 CONFIDENTIAL 10/1/2012  IV. Some employers may have failed to anticipate improvements in market conditions and may have left valuable employees with compensation packages far below what they could get elsewhere. This can create clusters of low-hanging fruit. Common Evidence and Analysis Are Capable of Showing that the Non-Compete Agreements Artificially Reduced the Compensation of Defendants’ Salaried Employees 63. Methods and evidence, common to each Class as a whole, are capable of demonstrating that the Non-Compete Agreements reduced the compensation of All-Employee Class and Technical Employee Class members employed by the Defendants. This Class-wide proof of impact comes in two steps. First, there is abundant evidence, common to All-Employee Class and Technical Employee Class members, capable of showing that the Non-Compete Agreement suppressed the compensation of the members of the All-Employee Class and Technical Employee Class, generally. Such Class-wide methods and evidence include, without limitation: (a) standard economic theory regarding the effects of information asymmetries on labor market contracts, which work to the disadvantage of the less informed party, and (b) standard economic theory regarding the effects of movement of employees between firms enticed by better compensation, and the consequent interest of firms in peremptory increases in compensation to employees when poaching by key rivals occurs regularly; (c) multiple regression analyses, using extensive compensation data, showing that compensation was reduced for Class and Technical Employee Class members; and (d) documentary evidence, including documents from Defendants’ own files, describing, e.g., the Non-Compete Agreements, Defendants’ enforcement of those Agreements, the importance of the Agreements, and the effects of poaching on movement between firms and compensation. 64. I have found further that Class-wide methods and evidence are capable of demonstrating that the Non-Compete Agreements suppressed the compensation of all or virtually all members of the All-Employee Class and Technical Employee Class. In addition to the Class-wide evidence described in Page 28 Expert Report of Edward E. Leamer, Ph.D. 348 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page33 of 81 CONFIDENTIAL 10/1/2012 the previous paragraph, such common proof that the effects of the NonCompete Agreements was broadly felt also includes (a) economic theory regarding the interest of firms in fostering a concept known in the economic literature as “internal equity,” such that compensation tracks the success of the firm’s most highly compensated employees; (b) additional evidence that compensation of employees tended to move together over time, such that the effects of Non-Compete Agreements are likely to be broadly felt; and (c) evidence from Defendants’ own files showing their respective concerns about preserving internal equity, as well as other documentary evidence, when Agreements were not in place, that some Defendants responded to periods of intense poaching by close rivals with across the board salary increases to all employees. 65. I describe these methods and evidence in greater detail below. A. Class-wide Evidence is Capable of Showing that the Non- Compete Agreements Suppressed Compensation Generally 1. Economic Theory Offers a Classwide Basis for Linking Non- Compete Agreements to Suppressed Compensation Incurred by Members of the All-Employee Class and Technical Employee Class 66. There are three economic frameworks106 that are particularly useful for evaluating the likely impact on employees of illegal agreements to suppress Cold-Calling. These frameworks--each well-accepted in the economics literature--explain various mechanisms by which anti-Cold-Calling agreements can suppress worker compensation generally. 67. The frameworks for considering the effect of the alleged non-compete agreements discussed below are (1) price discovery, (2) worker compensation equity and (3) profit-sharing. Each framework has different implications regarding the way in which the effects are spread across firms, across job “Frameworks” refers to general views regarding how labor markets function and “model” refers to a specific example of a framework. A framework is usually communicated in words, while a model is expressed with either graphs or mathematical formulae. 106 Page 29 Expert Report of Edward E. Leamer, Ph.D. 349 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page34 of 81 CONFIDENTIAL 10/1/2012 categories within firms and across time. The frameworks are not mutually exclusive in that effects of the Agreements can arise through multiple channels. In this section, I will focus here on frameworks “(1)” and “(3)” as they pertain mainly to the general linkage between the Non-Compete Agreements and suppressed compensation. I will elaborate on framework “(2)” regarding internal equity when I discuss the Class-wide evidence capable of showing widespread harm to the either class later in my Report. 68. For all three frameworks, Cold-Calling is part of the information gathering that reveals the nature of outside opportunities both to workers and to employers. Anti-Cold-Calling agreements suppress compensation by limiting this flow of information about attractive outside opportunities. 69. Cold-Calling is an especially important source of information about outside opportunities under two circumstances: (a) uneven growth (i.e., firms are growing at different rates), which requires reallocation of the workforce in favor of the firms which can offer workers the best contracts, and (b) even growth (firms are growing at a generally equal rate), which doesn’t necessitate any reallocation of the workforce but which creates greater competition for the scarce workforce. 70. Under either condition, Cold-Calling contributes to economic efficiency. With uneven growth, Cold-Calling helps to assure that workers are assigned to their most valued tasks. With even growth, Cold-Calling helps to assure that workers receive a proper scarcity premium which signals to other workers which skills are most needed. In both circumstances, economic theory predicts that agreements restricting Cold-Calling would suppress worker compensation for all or nearly all employees of the Defendants who agreed to them. a. Price Discovery Framework 71. The market equilibrium models that economists often use presume that market forces are powerful enough and work rapidly enough that virtually all transactions occur at approximately the same price – the “market price” which equilibrates supply and demand. In reality, in the face of changed market conditions, the actual transactions’ prices can deviate from the market Page 30 Expert Report of Edward E. Leamer, Ph.D. 350 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page35 of 81 CONFIDENTIAL 10/1/2012 equilibrium sometimes by large amounts for long periods of time. The process by which actual transactions prices move to market equilibrium values is called “market price discovery.” 72. The speed at which the price discovery process operates is determined by the frequency at which buyers and sellers get together to haggle over the price, and by the rate at which information about the outcomes of those bargains, consummated or not, is dispersed among other potential buyers and sellers. Non-Compete Agreements that limit the bargaining between employers and employees thus slow down the price discovery process and affect each and every labor contract in the markets. 73. In some settings the price discovery process is so slow and imperfect that the concept of a “market equilibrium” is of limited value for understanding the sequence of actual transactions.107 Labor markets that involve infrequent bargains and limited information flows can have very sluggish price discovery. High transaction costs and weak information flows create very illiquid labor services which are transferred via bilateral bargains, not via markets.108 The expensive and time-consuming task of uncovering and valuing the unique features of workers slows down the price discovery process and allows many transactions to occur at prices far from market equilibrium levels. 74. High-tech jobs involve high costs for transactions including time, money and personal dislocation. These high transaction costs make transactions very infrequent and limit the number of workers actively seeking new employers. 75. The labor market also has weak information flows about specific jobs. Employees may rely mostly on “water-cooler talk” perhaps supplemented by Internet sources. Employers, on the other hand, often hire private consulting firms to provide aggregated information about “market” compensation. For Stiglitz, Joseph, “Information and the Change in the Paradigm in Economics,” The American Economic Review, Vol.92, No. 3 (June 2002), pp. 460-501. 107 For related effects in a financial context, see e.g., Green, Richard C., Dan Li and Norman Schürhoff, “Price Discovery in Illiquid Markets: Do Financial Asset Prices Rise Faster Than They Fall?,” Journal of Finance, Volume 65, Issue 5, pp. 1669–1702, October 2010. 108 Page 31 Expert Report of Edward E. Leamer, Ph.D. 351 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page36 of 81 CONFIDENTIAL 10/1/2012 employees, Cold-Calling is an important channel of information about outside opportunities. Absent Cold-Calling, many labor contracts are negotiated in unequal bargains between informed employers and uninformed employees. 76. Agreements that reduce the number of bilateral bargains further slow the price discovery process and affect the whole sequence of actual transactions.109 NonCompete agreements do not change the value of the work; they only help employers keep more of that value. b. Relationship Framework: Firm-Specific Assets 77. Net revenues of high-tech intellectual service firms accrue to one of the two assets that drive value: the “brand” (the firm) or the workers. The division of the net revenues between the firm and the workers is determined by outside competition for workers, which pressures firms to pay their workers at least as much as the best outside offer.110 78. When firm-specific knowledge assets reside within the brains of workers, the movement of workers between firms is a form of “creative destruction” meaning that the increased value of the worker at the new job is offset by destruction of value at the old. This is economically inefficient unless the value of the asset created exceeds the value of the asset destroyed. If neither party to the new employment contract is incented to worry about the destruction, there will be too much destruction, the consequence of which is too little creation. A new employer is unconcerned about the “destruction” of the previous employer’s asset, or likes it if it impairs a competitor. It is therefore essential for firms to form relationships that make workers sensitive to the asset destruction that would occur if they switched employees. This can be done by making them joint owners of the intellectual assets of the firm, through stock option plans See Tappata, Mariano, “Rockets and Feathers Understanding Asymmetric Pricing,” UCLA Job Market Paper, January 2006 and Yang, Huanxing and Ye, Lixin, “Search with learning: understanding asymmetric price adjustments,” Ohio State University, August 2006. 109 GOOG-HIGH-TECH-00193377-382, GOOG-HIGH TECH-00038103-128 at 125, PIX00000038-039 and LUCAS00004446-452 at 451-452. 110 Page 32 Expert Report of Edward E. Leamer, Ph.D. 352 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page37 of 81 CONFIDENTIAL 10/1/2012 and restricted stock grants. These plans can help limit movement of critical workers. 79. If firms have not created adequate incentives to assure worker loyalty, ColdCalling can seriously threaten loss of the critical intellectual assets. In periods when demand for the critical workforce is weak, firms may feel little threat of loss of workers, and may let grants of stock options and restricted stocks recede. Firms may be surprised when the market starts to heat up again and they start to lose critical workers. A legal countermeasure to limit loss of the critical workers would be increased use of stock options and restricted stock grants. Management which prefers not to share ownership with their workforce may instead choose the countermeasure of anti-Cold-Calling agreements, even if it may be illegal. 80. Economic theory therefore predicts that agreements such as the Non-Compete Agreements artificially suppress employee compensation on a widespread basis. Furthermore, evidence common to all potential class members in this case can be used to confirm this predicted effect. 2. Defendants’ Internal Documents Provide Additional Class-wide Evidence Capable of Showing that the Non-Compete Agreements Artificially Suppressed Compensation 81. The Defendants’ internal documents can be used to confirm that company-wide prohibitions on recruiting would tend to artificially suppress the compensation of the members of the All-Employee Class and Technical Employee Class. 82. Documents reveal that the defendants would otherwise have been competing for employees.111 In the absence of these agreements, Defendants would have cold called one another’s employees.112 See e.g., ADOBE_005950 - 967 at 966 (“list of [nine] companies Adobe’s Board of Directors benchmarks against from a compensation standpoint” include Google, Apple, and Intel; with regard to benefits, Adobe is in a “six horse race” with Google, Apple, Intel and two other companies); PIX00006023 (“Our people are becoming really desirable and we need to nip this in the bud.”); GOOG-HIGH TECH-00023206-212 at 209 (“The Recruiting Wars: How To Beat Google To Tech Talent”). 111 112 See GOOG-HIGH TECH-00056840 (“Cold-Calling into companies to recruit is to be expected unless Page 33 Expert Report of Edward E. Leamer, Ph.D. 353 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page38 of 81 CONFIDENTIAL 10/1/2012 83. Prior to the Agreements the Defendants were concerned with successful poaching by other firms—and particularly other Defendants. In an email discussing Adobe’s policy toward Apple under the Agreements, Adobe’s Bruce Chizen wrote, “… Knowing Steve, he will go after some of our top Mac talent like Chris Cox and he will do it in a way in which they will be enticed to come (extraordinary packages and Steve wooing).”113 84. Thus Defendants recognized that Cold-Calling and other forms of poaching had the potential to drive up the cost of specific employees. They also recognized that the effects of poaching would extend well beyond the employees directly approached by a cold-call. Pixar’s top executive Ed Catmull noted, “we learned that the company that Zemeckis is setting up in San Rafael has hired several people away from Dreamworks at a substantial salary increase… every time a studio tries to grow rapidly… it seriously messes up the pay structure.”114 they’re on our ‘don’t call’ list.”); GOOG-HIGH TECH-00053679-681 at 680 (“Over the 8 years of my executive search experience, I’ve worked with hundreds of clients. And for every search assignment, the first thing we do is to target the direct competitors of the respective clients.”); ADOBE_001092-093 at 092 (“Apple would be a great target to look into. Unfortunately, Bruce and Steve Jobs have a gentleman’s agreement not to poach each other’s talent.”); GOOG-HIGH TECH-00023132 (as soon as eBay and PayPal were removed from Google’s Do Not Call list, “staffing is ready to pursue several hundred leads and candidates”); 76506DOC000773-990 at 845 (in an Intel presentation titled “Intel’s Complete Guide to Sourcing,” on the slide regarding “Cold-Calling”: “Calling candidates is one of the most efficient and effective was to recruit.”); LUCAS00005403-446 at 405 (“The Recruiting Strategy for LucasArts for the next 2-3 years must be focused on the passive candidate.”); ADOBE_002773-788 at 775 (Adobe presentation regarding sourcing focused on “passive” candidates:” “top performers tend to be entrenched, ‘heads down.’”); GOOGHIGH TECH-00024149-218 at 152 (in a Google “Sourcing Diagnostic”: “Passive sourcing will play an increasingly large role in recruiting as we move forward as a company.”); and GOOG-HIGH TECH00007729 (a year before entering into its first no-solicit agreement with Apple, Shona Brown wrote: “We have historically always allowed recruiters to find talent wherever it is – even when it is with key partners . . . or sensitive competitors . . . Which is the right answer.”). In response to one of Mr. Geshuri’s “periodic reminders” to his recruiters regarding the “Do Not Call list,” a Google recruiter remarked in frustration: “I guess the candidates I have been sourcing from Burger King, Jiffy Lube and Der Wienerschnitzel are still fair game.” See GOOG-HIGH TECH-00008249 and Deposition of Arnnon Geshuri, August 17, 2012 at pp. 262:4-264:13. 113 ADOBE_001096-001097 at 097. PIX00000229. Also noting, “I know that Zemeckis’ company will not target Pixar, however, by offering higher salaries to grow at the rate they desire, people will hear about it and leave. We have avoided wars up in Northern California because all of the companies up her – Pixar, ILM, Dreamworks, and a couple of smaller places- have conscientiously avoided raiding each other.” 114 Page 34 Expert Report of Edward E. Leamer, Ph.D. 354 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page39 of 81 CONFIDENTIAL 10/1/2012 85. These documents indicate defendants saw a significant potential benefit from reducing or limiting this competition for employees (e.g., relating to the perceived impact of actual and potential poaching on compensation). 86. In contexts not covered by the non-compete agreements, the defendants regularly and openly used Cold-Calling to find new employees. For example, in an Intuit email, Intuit officials looking to fill a position discuss “good target companies to go after.”115 87. Even during the period of agreements, the Defendants considered Cold-Calling a useful tool in recruiting employees from companies other than those participating in the Agreements.116 88. In November 2007, after agreement between Adobe and Apple was officially terminated, a Hiring Analysis from Adobe’s Competitive Intelligence Group reported, “recruiting and retaining top talent will likely be more competitive to the extent that the high tech sector remains economically healthy… As Microsoft, Google and Apple dial-up the volume on attracting Adobe resources, what changes or new approaches would assist Adobe in retaining top talent?”117 3. Analysis of Defendants’ Compensation Data Is Additional Class-wide Evidence Capable of Showing that the Compensation of All-Employee Class and Technical Employee Class Members Was Suppressed by the Non-Competition Agreements 89. 90. 115 My analysis of Defendants’ compensation data is additional common evidence capable of showing that restricting Cold-Calling would artificially suppress employee compensation by impeding the price discovery process. Compensation of new recruits compared with existing employees can reveal the price discovery process at work. If compensation of current workers were close INTUIT_002372. See e.g., PIX00003610-00003611 at 610; GOOG-HIGH TECH-00008233 (6/21/2008 email’ “actively recruiting key Yahoo! Employees was a recommended course of action given current industry dynamics”). 116 117 ADOBE_004964 – 004997 at 975. Page 35 Expert Report of Edward E. Leamer, Ph.D. 355 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page40 of 81 CONFIDENTIAL 10/1/2012 to a “market equilibrium” level, the new recruits would be paid similarly to existing employees, net of “moving costs.” If the market value of the workers were then to increase, that would set in motion a price discovery process during which new recruits were paid distinctly more than current employees with similar skills and experience. In the early phases of the price discovery process, the salaries of these new recruits might also be below equilibrium levels, and the compensation packages offered new recruits can improve over time in search of the higher equilibrium. As firms become aware of the increased external competition, compensation packages of current employees may be improved to bring them more in line with outside opportunities. It can take considerable time for this complicated price discovery process to find a new equilibrium in which new recruits and existing employees are paid about the same. It can take much longer if information about superior opportunities is suppressed by NonCompete Agreements. 91. Thus, a symptom of price discovery at work would be better compensation packages for those who moved between Defendants than for those who stayed. In Figure 6 and Figure 7 below I compare on a year-by-year basis the percent changes in compensation of the movers versus the stayers--those who moved between Defendants and those who didn’t. As Figure 6 shows, the increase in base salary of the movers was almost always above the stayers. But in 2006, the movers received almost 16 percent increases in base salary compared with about 5 percent for the stayers. That gap is a symptom of the price discovery process at work in search of higher wages, a process that was the apparent target of the anti-Cold-Calling agreements put in place at that time. Page 36 Expert Report of Edward E. Leamer, Ph.D. 356 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page41 of 81 357 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page42 of 81 358 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page43 of 81 CONFIDENTIAL 10/1/2012 95. Cold-Calling is likely to be most active during the industry expansions in which the industry overall is enjoying rapid growth and facing supply constraints of workers at every level of experience. 96. During much of the class period, the Defendants collectively were experiencing a phase of rapid economic expansion and exhibited strong financial performance. Google grew from a startup with just eight employees in 1999 to a publicly traded company with over 30,000 employees in 2012. Apple tripled its revenue between 2005 and 2010 with widespread success of its consumer electronic products including the iPhone, iPod Touch and iPad. Adobe generated about $980 million in owner earnings in 2007, up from $580 million and $540 million in 2006 and 2005, respectively.118 Between 1998 and 2011, Pixar released 11 blockbuster feature films resulting in more than $6 billion at the worldwide box office.119  97. ‘It’s surreal in the Valley, compared to the rest of the country,’ said Harj Taggar, a partner at startup incubator Y Combinator [in 2011]. ‘It’s so hard to hire people here – and salaries for engineers are going through the roof.’120 Equity distributions are especially important for retaining critical employees during expansions when many firms are actively recruiting talent. The normal vesting periods of three or four years align compensation with stock market performance, and create a loss for workers who leave. This makes them share in the loss of firm-specific knowledge assets that their departure creates. Equity grants and profit-sharing are used to promote employee loyalty and retain firmspecific knowledge assets,121 as that term is understood in economic literature. Ponzio, Joe, “With Adobe, Growth and Value are Joined at the Hip,” Seeking Alpha, February 4, 2008, http://seekingalpha.com/article/62919-with-adobe-growth-and-value-are-joined-at-the-hip. 118 Pixar, “Corporate Overview,” http://www.pixar.com/companyinfo/about_us/overview.htm [Accessed 04/06/2012]. 119 Wagner, Alex, “As National Employment Stalls, Job Market Booms In Silicon Valley,” Huffington Post, July 8, 2011. 120 121 See e.g., Grant, R. M., “Toward a Knowledge-Based Theory of the Firm,” Strategic Management Journal, 17 Page 39 Expert Report of Edward E. Leamer, Ph.D. 359 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page44 of 81 360 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page45 of 81 CONFIDENTIAL 99. 10/1/2012 Revenues are required to support salary increases, and a surge in profits over time is likely to be spent partly on raising wages and retaining key employees. Figure 9 illustrates the growth in revenue per worker at Apple and the average total compensation per worker. Apple revenues per worker doubled from around $500,000 in 2001 around $1,000,000 in 2005, but The Apple Non-Compete Agreements went into effect when Apple revenues surged, and when the risk of sharing the gains with the workforce was a threat to the firms’ high levels of profits. Figure 9: Growth of Apple's Revenue and Compensation Apple's Revenue and Average Total Compensation Per Employee Source: Defendants' employee compensation data; SEC Filings. Page 41 Expert Report of Edward E. Leamer, Ph.D. 361 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page46 of 81 CONFIDENTIAL 100. 10/1/2012 Following a period of industry weakness122 in which the forces for increases in compensation were weak, normal market forces in 2005 and subsequently would have resulted in a distribution of some of that net revenue to the workforce. It is not surprising that the anti-Cold-Calling agreements were put in place in 2005 and subsequently, when employment and revenues began to grow substantially and when competition for critical workers was likely more intense. The agreements were formed when they were most likely to be effective and to matter. B. Classwide Evidence is Capable of Showing that the Non-Compete Agreements Suppressed the Compensation of All or Nearly All Members of the All-Employee Class and Technical Employee Class 101. Common evidence can likewise be used to demonstrate that the artificial suppression of employee compensation would have been widespread, extending to all or nearly all members of the All-Employee Class and Technical Employee Class. This Class-wide evidence includes all of the evidence set forth above capable of showing the link between the Non-Compete Agreements and suppressed compensation plus three additional categories of evidence: (a) economic theory implicating firm incentives to maintain worker loyalty by adhering to principles of internal equity through a rigid salary structure; (b) Defendants’ documents reflecting their recognition and implementation of internal equity principles and more specifically demonstrating the broad effects on compensation of the Non-Compete Agreements; and (c) multiple regression analyses capable of showing both that compensation of All-Employee Class and Technical Employee Class members is governed largely by common factors and that Defendants maintained rigid salary structures such that one would expect Non-Compete Agreements to have widespread effects on compensation of AllEmployee Class and Technical Employee Class members. Luo, Tian and Mann, Amar, “Crash and Reboot: Silicon Valley high-tech employment and wages, 200008,” Monthly Labor Review, January 2010, p.61-65 and NOVA Workforce Board, “Silicon Valley in Transition,” July 2011. 122 Page 42 Expert Report of Edward E. Leamer, Ph.D. 362 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page47 of 81 CONFIDENTIAL 10/1/2012 102. One key economic framework (introduced above) is built on the concept of firms’ incentives to maintain and promote worker loyalty. Although economists often refer to the labor “market,” most labor services are mediated not by commodity markets but by committed long-term relationships built on trust and understanding and mutual interests. If it were literally a commodity market the compensation paid to any particular employee would have to be both the highest that the employee could find and also the lowest that the employer could find at any particular point in time. If workers were commodities, every small change to external or internal conditions would lead to recontracting, separation, or termination. This would create enormous uncertainty and disruption and insecurity for employer and employee. Both sides of the bargain thus seek ways to turn the market transaction into a long-term relationship. A secure long-term relationship can come either from commitment (emotional or financial) to the mission of the organization, or from jointly owned firm-specific assets.123 103. Firms attempt to create loyalty by getting buy-in to the firm’s mission and by making the place of work as appealing as possible.124 If these intangibles are insufficient, firms also have employee stock options (ESOPs) that give employees a stake in their firm.125 104. One foundation of employee loyalty is a feeling of fairness that can translate into a sharing of the rewards with more equality than a market might otherwise produce. “Equitable” compensation practices spread wage increases or reductions across broad categories of workers.126 This implies that when Becker, Gary, “Nobel Lecture: The Economic Way of Looking at Behavior,” The Journal of Political Economy, Vol. 101, No.3 (June 1993), pp. 385-409. 123 124 See GOOG-HIGH TECH-00038364-395 at 368-369. 125 Oyer, Paul and Schaefer, Scott, “Why Do Some Firms Give Stock Options To All Employees?: An Empirical Examination of Alternative Theories,” March 26, 2003. See e.g., Rees (1993) who describes the role of demand and the impact of market forces on salary structures of university faculty. (Rees, A. "The Role of Fairness in Wage Determination," Journal of Labor Economics, 1993, Vol. 11, No. 1, pt. 1.) See also, Mas, “Pay, Reference Points, and Police Performance,” The Quarterly Journal of Economics, August 2006. 126 Page 43 Expert Report of Edward E. Leamer, Ph.D. 363 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page48 of 81 CONFIDENTIAL 10/1/2012 outside opportunities put pressure at one point in the wage structure calling for higher wages for a few, firms tend to maintain the overall firm wage structure, rewarding everyone for the improved outside opportunities of some workers.127 105. To maintain loyalty, it is usually better for a firm to anticipate rather than to react to outside opportunities, since if a worker were to move to another firm at a much higher level of compensation, coworkers left behind might feel they have not been fairly compensated. That can have an adverse effect on worker loyalty, reducing productivity and increasing interest in employment elsewhere. To avoid this reduction in loyalty in the face of competition, firms may make preemptive improvements in their compensation packages.128 106. As discussed throughout this Report, Class-wide evidence is capable of showing that Cold-Calling--as well as just the threat of Cold-Calling--puts upward pressure on compensation. Economic theory describes factors that drive firms, like the Defendants, toward equitable pay practices that would be expected to spread the impact of an agreement to suppress Cold-Calling across all or almost all workers in a firm. Non-compete agreements allow firms to be more relaxed in maintaining competitive compensation packages because such agreements 1) suppress competition directly; 2) reduce the risk of employees becoming aware of pay practices elsewhere; and 3) otherwise eliminate competition for “passive” employees. 127 Concerns about fairness are observed within the defendants and in public discussions relating to salaries at firms like the defendants. See e.g., 76512DOC000638-677 at 644 and 656-658 (“Use benchmark salary surveys to create criteria on which to evaluate jobs across Intel… supports consistence and equity within and across business groups.”). See also, ADOBE_008047-049 at 047 and GOOG-HIGH-TECH-00193377-382 at 380-381. 128 See e.g., GOOG-HIGH-TECH-00194945 –946. Page 44 Expert Report of Edward E. Leamer, Ph.D. 364 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page49 of 81 365 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page50 of 81 366 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page51 of 81 CONFIDENTIAL 10/1/2012 bonus of $1,000 for every salaried employee.142 Google referred to this project as the “Big Bang,” and discussed it extensively beforehand with Intuit’s Bill Campbell and Intel’s Paul Otellini.143 These discussions provide a powerful illustration of the common impact of Defendants’ Agreements. 111. 112. This is an illustration of all three frameworks: (1) Price Discovery; (2) Equity and Loyalty; and (3) Firm-Specific Assets. 113. First, when employees discover information regarding their labor’s value by receiving an offer from a competing employer, those employees use that information to negotiate higher salaries at their current employer, and so on, in an iterative process. 114. 142 On October 8, 2010, Jonathan Rosenberg emailed Google’s senior executives (and Bill Campbell) summarizing concerns from the “broader population” at Google regarding Google’s counteroffer strategy. Employees who heard about other “Googlers” receiving counteroffers were upset: “It’s impossible to keep something like this a secret. The people getting counter offers talk, not just to Googlers and Ex-Googlers, but also to the competitors where they received their offers (in the hopes of improving them), and those competitors talk too, using it as a tool to recruit more Googlers.”144 “And for the time that the person remains, there will be serious resentment among his/her peers for what seems like an unfair jump.”145 Second, those individuals tell others at their employer, who then “resent[]” the perceived “unfair jump” in pay, increasing pressure to match compensation GOOG-HIGH-TECH-00193377-382 at 380. 143 See GOOG-HIGH-TECH-00195005 – 007, GOOG-HIGH-TECH-00196108, GOOG-HIGH-TECH00196687, GOOG-HIGH-TECH-00196689, and GOOG-HIGH-TECH-00194945 –946. 144 INTUIT_039098-100 at 098. 145 INTUIT_039098-100 at 098. See also, GOOG-HIGH-TECH-00194721-722. Page 47 Expert Report of Edward E. Leamer, Ph.D. 367 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page52 of 81 CONFIDENTIAL 10/1/2012 increases broadly.146 This is often experienced in emotional terms: “it feels like my loyalty is being punished.”147 115. Third, 148 116. Alan Eustace, a Senior VP of Google, confirmed these frameworks in the same document (again, in an email also sent to Bill Campbell): “every time an employee has a better offer, a company is forced to decide how badly they want the employee, and what they are ultimately worth. . . . You can’t afford to be a rich target for other companies.”149 117. Eustace also explained why many employee candidates will not learn “what they are ultimately worth” without Cold-Calling by a competing company: actively seeking out such offers and using them to negotiate for higher compensation “is a high risk strategy” that “seriously questions your loyalty and character, which could have long-term consequences to your career that offset any financial gain.”150 The “right approach” to respond to such recruiting efforts by a labor market competitor “is to not deal with these situations as one-off’s but have a systematic approach to compensation that makes it very difficult for anyone to get a better offer.”151 118. Google’s announcement did not escape the attention of other Defendants. First, the same executives at Intuit and Intel who entered into the Agreements 146 See INTUIT_039098-100 at 099. 147 INTUIT_039098-100 at 099. 148 INTUIT_039098-100 at 099. 149 INTUIT_039098-100 at 098. 150 INTUIT_039098-100 at 098. 151 INTUIT_039098-100 at 098. Page 48 Expert Report of Edward E. Leamer, Ph.D. 368 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page53 of 81 CONFIDENTIAL 10/1/2012 with Google were sent them directly.152 Other Defendants paid close attention as well.153 119. 155 2. Econometric and Statistical Analysis of Defendants’ Compensation Data Is Also Capable of Demonstrating That the Compensation Suppressing Effects of the Non-Compete Agreements Would Be Broadly Experienced By Members of the All-Employee Class and Technical Employee Class 120. A firm’s commitment to principles of “internal equity” is evidenced by the imposition and maintenance of a somewhat rigid salary structure. What that means is that Cold-Calling and related practices would be expected to increase compensation across the board rather than be narrowly focused on the skills that are most in demand at any point in time.156 As a result, analysis of the application of standard economic labor theory to this case constitutes common evidence bolstering Plaintiffs’ proof that the Non-Compete Agreements would broadly affect members of the All-Employee Class and Technical Employee Class. Moreover, economic analysis of Defendants’ salary structures and compensation data reveal that each Defendant had a rigid salary structure, 152 See, e.g., INTUIT_039098. (Campbell); 76616DOC005974 and “Google,Board of Directors,” http://investor.google.com/corporate/board-of-directors.html (Paul Otellini at Intel, who was a Google Board Member throughout the conspiracy period). See, e.g., ADOBE_025894-898 at 898 (internal discussion in which Adobe considers whether its employees will want a raise similar to the one Google announced). 153 154See 155 GOOG-HIGH TECH-00193377-382. See GOOG-HIGH-TECH-00193406-411 at 406 .”). See eg. GOOG-HIGH TECH-00042588-640 at 633 (Talking about the equity program, “In special cases and with VP approval, we can exceed target if supported by sound business rationale. In practice, we rarely deviate from the guidelines given our philosophy around internal equity.”). 156 Page 49 Expert Report of Edward E. Leamer, Ph.D. 369 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page54 of 81 CONFIDENTIAL 10/1/2012 where compensation of employees within specific positions and within each company tended to move together over time through the relevant periods. 121. The Class-wide evidence I have reviewed and analyzed shows that Defendants had highly structured compensation systems built on a two dimensional matrix with several grades and many titles. In many firms, compensation is first and foremost linked to the grades, each of which encompasses diverse kinds of activities which nonetheless receive roughly the same level of compensation.157 For example, Defendants Adobe, Apple, Google, Intel, and Intuit used grades explicitly and Defendants Pixar and Lucasfilm may have done so as well (though their data in this regard was unclear at the time of this Report). The titles identify specific activities and defined career paths, as in Software Engineer Step 1, Software Engineer Step 2, and so on. 122. Typically, high level management established ranges of salaries for grades and titles which left relatively little scope for individual variation.158 Defendants established and regularly updated compensation levels with the following aims: a. b. Providing specific relative compensation levels for employees in different, hierarchically ordered, employment categories, or “salary grades,”160 c. Retaining employees,161 and d. 157 Providing similar compensation for all employees in the same employment category,159 Maintaining employee productivity and contentment. See e.g., 76512DOC000638-677 at 643 and 656-660. See e.g., 76512DOC000638-677 at 644 (“Use benchmark salary surveys to create criteria on which to evaluate jobs across Intel”) and GOOG-HIGH TECH-00042588-640 at 612 and 632. 158 159 PIX00006026-6036 at 034 and GOOG-HIGH TECH-00042588-640 at 643. See e.g., 76512DOC000638-677 at 671 (“ HIGH TECH-00028981- 9027 at 9007. 160 161 ”). See also, GOOG- GOOG-HIGH-TECH-00036781-839 at 785. Page 50 Expert Report of Edward E. Leamer, Ph.D. 370 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page55 of 81 371 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page56 of 81 CONFIDENTIAL 10/1/2012 loss of employees to Facebook (described above). The ten percent increase in base salary across the board was said to “attract new recruits and preempt defections.”166 “Reporting from San Francisco — Google Inc.'s decision to give all of its 23,300 employees a 10% pay raise next year — and a $1,000 bonus to boot — is just the latest volley in what has become a full-fledged war for top Silicon Valley talent.”167 126. All Defendants offered stock grants or options, and/or bonuses. While inequity in this form of compensation could offset pay equity in base compensation, stock options and bonuses may be calculated formulaically based on individual and company performance in a way that maintains an equitable total compensation structure.168 Indeed, stocks or bonuses were granted to the majority of employees at all of the Defendants. As shown in Figure 10, 93 percent of the employee-year169 compensation records included these salary supplements. Amir Efrati and Pui-Wing Tam "Google Battles to Keep Talent" Wall Street Journal, November 11, 2010, http://online.wsj.com/article/SB10001424052748704804504575606871487743724.html 166 167 Guynn, Jessica, “War heats up for top Silicon Valley talent,” Los Angeles Times, November 10, 2010. See e.g., 76512DOC000638-677 at 668 (“Option run rates typically non-negotiable”). See also, 76512DOC000638-677 at 644, and 656-667. 168 An employee employed in December of a particular year. An employee of a firm for five years (each of which he was present for December), would have five employee-years. 169 Page 52 Expert Report of Edward E. Leamer, Ph.D. 372 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page57 of 81 CONFIDENTIAL 10/1/2012 Figure 10: Use of Supplemental Compensation was Widespread Fraction of Employee-years with Bonus or Equity Grants Employer (1) Mean (2) Number of Observations (3) Adobe Apple Google Intel Intuit Lucasfilm Pixar 0.84 50,862 0.88 0.51 0.74 63,700 9,118 12,654 All 0.93 985,428 Source: Defendants' employee compensation data. 127. Evidence of the structure of compensation in each of ten years from 2001 to 2011 is reported in the ten regression equations in Figure 11 below. 128. Each equation explains the total compensation inclusive of stock grants of each salaried employee in terms of a number of basic observable employee characteristics such as age, number of months in the company, gender, location, title, and employer.170 What these analyses show is that about 90 percent of the variability in a class member’s compensation can be explained by these variables.171 This and the additional fact that the coefficients in these regressions vary slowly over time (meaning the role played by these factors is 170 These types of regressions can be found in many academic studies of wage structure. See e.g., MenezesFilho, N. A., Muendler, M., and Garey Ramney. "The Structure of Worker Compensation in Brazil, With A Comparison To France And The United States." The Review of Economics and Statistics, May 2008, 90(2): 324346. Other variables that would have been known to the employee and employer but where not available at all or for large numbers of employees in the data (such as education) would likely explain substantially more of the variation. 171 Page 53 Expert Report of Edward E. Leamer, Ph.D. 373 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page58 of 81 CONFIDENTIAL 10/1/2012 relatively stable), are symptoms of firmwide compensation structures, and the formulaic way in which total compensation was varied over time. Figure 11: Common Factors Identify a Firmwide Compensation Structure Hedonic Regressions Of Wage Structure All-Salaried Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation) Variable Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male Employer Indicators Location (State Indicators) Title Indicators Constant Observation R-square Dec-01 Estimate St. Error T-Value 0.72 -0.10 -0.07 0.00 0.00 YES YES YES YES 0.08 0.01 0.00 0.00 0.00 9.60 -9.66 -17.28 9.38 1.15 64,264 0.95 Observation R-square 0.77 -0.09 0.08 -0.01 0.01 YES YES YES YES 0.08 0.01 0.00 0.00 0.00 9.93 -8.74 38.46 -27.73 9.18 71,768 0.928 Observation R-square 1.10 -0.15 0.04 0.00 0.01 YES YES YES YES 73,722 0.922 0.08 0.01 0.00 0.00 0.00 13.26 -13.06 -29.45 20.40 3.60 Dec-06 Estimate St. Error T-Value 0.96 -0.12 -0.03 0.01 0.02 YES YES YES YES 0.09 0.01 0.00 0.00 0.00 11.54 -11.59 9.35 -3.14 7.59 0.09 0.01 0.00 0.00 0.00 11.28 -10.69 -9.31 13.28 9.57 78,673 0.898 0.74 -0.09 -0.02 0.00 0.01 YES YES YES YES 0.08 0.01 0.00 0.00 0.00 9.29 -8.62 -4.88 1.70 4.49 Dec-07 Estimate St. Error T-Value 1.25 -0.17 -0.03 0.00 0.01 YES YES YES YES 0.10 0.01 0.00 0.00 0.00 9.57 -9.29 6.33 -3.29 8.17 Dec-04 Estimate St. Error T-Value 1.23 -0.16 0.01 0.00 0.01 YES YES YES YES 0.08 0.01 0.00 0.00 0.00 15.16 -14.38 4.99 -6.04 6.81 62,645 0.93 0.10 0.01 0.00 0.00 0.00 12.71 -12.53 -9.55 9.36 4.97 71,804 0.909 Dec-10 Estimate St. Error T-Value 0.95 -0.12 0.02 0.00 0.02 YES YES YES YES Dec-03 Estimate St. Error T-Value 60,764 0.94 72,380 0.923 Dec-09 Estimate St. Error T-Value Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male Employer Indicators Location (State Indicators) Title Indicators Constant 1.03 -0.14 -0.12 0.01 0.01 YES YES YES YES 61,768 0.94 Dec-05 Estimate St. Error T-Value Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male Employer Indicators Location (State Indicators) Title Indicators Constant Dec-02 Estimate St. Error T-Value Dec-08 Estimate St. Error T-Value 1.13 -0.15 0.02 0.00 0.01 YES YES YES YES 0.09 0.01 0.00 0.00 0.00 13.06 -12.59 6.84 -3.89 8.73 73,897 0.916 Dec-11 Estimate St. Error T-Value 0.97 -0.13 0.05 0.00 0.01 YES YES YES YES 0.08 0.01 0.00 0.00 0.00 11.54 -11.19 17.99 -7.39 8.79 88,431 0.918 Note: (1) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, value of equity compensation granted. (2) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. Source: Defendants' employee compensation data; SEC Filings. Page 54 Expert Report of Edward E. Leamer, Ph.D. 374 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page59 of 81 CONFIDENTIAL 10/1/2012 129. The regressions reported in the figure above are based on data from all defendants and presume that each defendant had a similar internal compensation system although the “employer effect” allows compensation to differ by a fixed percent across firms. Figure 12 shows a summary of the Rsquared statistic for hedonic regressions performed separately for each defendant and year. The R-squared statistic measures the percentage of the variability in compensation that is explained by the variables in the model. The majority of the R-squared statistics are around 90 percent demonstrating that almost the entire variation in salaries within each firm at each point in time can be explained by a common set of employee characteristics. 130. The fact that nearly all variability in class member compensation at any point in time can be explained by common variables means there was a systematic structure to employee compensation at each of the Defendant firms. As a result, one would expect that significant exogenous factors like the imposition of Non-Compete Agreements would be expected to have effects that would be felt across a broad swathe of employees. Furthermore, the fact that the coefficients in my regressions did not vary substantially over time suggests that compensation structures were relatively stable over time. The systematic structure and the formulaic way in which compensation changed over time is consistent with internal equity considerations as discussed in the economic literature. In other words, my regression analyses are capable of showing that the compensation of class members tended to move together over time and in response to common factors. Accordingly, this evidence, along with my other analysis of the economics of Defendants’ compensation, is capable of showing that the effects on compensation from the Non-Compete Agreements would be expected to be broadly experienced by all or nearly all members of the AllEmployee Class and Technical Employee Class. Page 55 Expert Report of Edward E. Leamer, Ph.D. 375 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page60 of 81 CONFIDENTIAL 10/1/2012 Figure 12: Common Factors Explain Within-Firm Compensation Structure Summary of R-squared From Yearly Hedonic Regressions By Defendant All-Salaried Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation) Year ADOBE APPLE GOOGLE INTEL INTUIT PIXAR LUCASFILM (1) (2) (3) (4) (5) (6) (7) (8) 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 0.91 0.93 0.92 0.94 0.87 0.94 0.92 0.93 0.88 0.91 0.93 0.89 0.87 0.91 0.91 0.91 0.89 0.87 0.87 0.87 0.86 0.86 0.93 0.94 0.79 0.89 0.80 0.79 0.75 0.80 0.86 0.77 0.83 0.96 0.95 0.96 0.96 0.97 0.97 0.96 0.97 0.96 0.96 0.97 0.88 0.90 0.90 0.89 0.89 0.89 0.88 0.88 0.88 0.88 0.88 0.84 0.71 0.85 0.83 0.90 0.92 0.93 0.94 0.93 0.95 0.88 0.87 0.92 0.94 0.94 0.94 Note: Hedonic regressions performed separately for each defendant and year by using log(Total annual compensation) as a dependant variable and the following independent variables: log(age), log(age)2, log(company tenure), log(company tenure)2, male indicator, location indicators, and title indicators. Pixar's R-squared in 2001 is missing due to insufficient observations. Regressions for Lucasfilm were not performed for 2001-2005 due to absence of employee titles in the data. Source: Defendants' employee compensation data; SEC Filings. 131. The Technical Employee Class also has a compensation structure that is captured by the regression equations reported in Figure 13 that apply to employees at all firms and also R-squared statistics for the regressions defendant by defendant as reported in Figure 14. Page 56 Expert Report of Edward E. Leamer, Ph.D. 376 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page61 of 81 CONFIDENTIAL 10/1/2012 Figure 13: Common Factors Identify a Firmwide Compensation Structure Hedonic Regressions Of Wage Structure Technical, Creative, and R&D Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation) Variable Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male Employer Indicators Location (State Indicators) Title Indicators Constant Observation R-square Dec-01 Estimate St. Error T-Value 0.41 -0.06 -0.07 0.00 0.00 YES YES YES YES 0.12 0.02 0.01 0.00 0.00 3.40 -3.84 -13.28 6.38 1.46 33,993 0.89 Observation R-square 0.62 -0.07 0.10 -0.01 0.01 YES YES YES YES 0.11 0.02 0.00 0.00 0.00 5.57 -4.84 33.58 -26.68 5.33 39,736 0.879 Observation R-square 1.28 -0.18 0.04 0.00 0.02 YES YES YES YES 44,839 0.885 0.12 0.02 0.01 0.00 0.00 7.96 -8.19 -23.33 15.50 2.32 Dec-06 Estimate St. Error T-Value 0.95 -0.13 -0.03 0.00 0.02 YES YES YES YES 0.12 0.02 0.00 0.00 0.00 10.56 -10.84 8.83 -3.39 6.50 0.12 0.02 0.00 0.00 0.00 8.16 -7.88 -6.07 7.72 7.93 48,401 0.841 0.70 -0.09 0.01 0.00 0.00 YES YES YES YES 0.12 0.02 0.00 0.00 0.00 5.94 -5.70 2.69 -5.57 1.54 Dec-07 Estimate St. Error T-Value 1.47 -0.20 -0.03 0.00 0.01 YES YES YES YES 0.13 0.02 0.00 0.00 0.00 8.45 -8.45 4.98 -2.31 7.21 Dec-04 Estimate St. Error T-Value 1.28 -0.17 0.04 -0.01 0.01 YES YES YES YES 0.12 0.02 0.00 0.00 0.00 10.62 -10.24 10.75 -12.58 4.23 32,999 0.88 0.13 0.02 0.00 0.00 0.00 10.89 -11.02 -6.12 5.52 3.05 41,862 0.848 Dec-10 Estimate St. Error T-Value 1.08 -0.15 0.02 0.00 0.02 YES YES YES YES Dec-03 Estimate St. Error T-Value 33,072 0.88 40,458 0.870 Dec-09 Estimate St. Error T-Value Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male Employer Indicators Location (State Indicators) Title Indicators Constant 0.95 -0.13 -0.13 0.01 0.01 YES YES YES YES 33,431 0.89 Dec-05 Estimate St. Error T-Value Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male Employer Indicators Location (State Indicators) Title Indicators Constant Dec-02 Estimate St. Error T-Value Dec-08 Estimate St. Error T-Value 1.34 -0.18 0.04 0.00 0.02 YES YES YES YES 0.11 0.02 0.00 0.00 0.00 11.86 -11.65 9.42 -6.98 7.24 43,643 0.859 Dec-11 Estimate St. Error T-Value 1.03 -0.14 0.05 0.00 0.02 YES YES YES YES 0.11 0.01 0.00 0.00 0.00 9.79 -9.69 13.42 -5.61 7.89 54,695 0.878 Note: (1) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, value of equity compensation granted. (2) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. Source: Defendants' employee compensation data; SEC Filings. Page 57 Expert Report of Edward E. Leamer, Ph.D. 377 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page62 of 81 CONFIDENTIAL 10/1/2012 Figure 14: Common Factors Explain Within-Firm Compensation Structure Summary of R-squared From Yearly Hedonic Regressions By Defendant Technical, Creative, and R&D Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation) Year ADOBE APPLE GOOGLE INTEL INTUIT PIXAR LUCASFILM (1) (2) (3) (4) (5) (6) (7) (8) 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 0.86 0.91 0.89 0.92 0.89 0.92 0.88 0.90 0.86 0.87 0.91 0.83 0.84 0.87 0.87 0.87 0.84 0.81 0.81 0.80 0.79 0.76 0.79 0.87 0.66 0.83 0.62 0.68 0.66 0.68 0.81 0.68 0.76 0.92 0.90 0.91 0.90 0.94 0.93 0.93 0.94 0.93 0.94 0.95 0.78 0.84 0.86 0.85 0.86 0.85 0.82 0.85 0.86 0.85 0.84 0.64 0.52 0.67 0.65 0.75 0.83 0.86 0.86 0.87 0.87 0.86 0.83 0.90 0.92 0.92 0.93 Note: Hedonic regressions performed separately for each defendant and year by using log(Total annual compensation) as a dependant variable and the following independent variables: log(age), log(age)2, log(company tenure), log(company tenure)2, male indicator, location indicators, and title indicators. Pixar's R-squared in 2001 is missing due to insufficient observations. Regressions for Lucasfilm were not performed for 2001-2005 due to absence of employee titles in the data. Source: Defendants' employee compensation data; SEC Filings. 132. The compensation structure around a common baseline can also be seen by looking at compensation trends of some of the major titles at Defendants. These data use the regressions reported in Figure 12 to control for changes within each title in age, tenure, and location. We refer to these as “constant attribute” compensation. Page 58 Expert Report of Edward E. Leamer, Ph.D. 378 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page63 of 81 CONFIDENTIAL 10/1/2012 Figure 15: Constant Attribute Compensation of Major Apple Job Titles Base Salary Source: Defendants' employee compensation data. Total Compensation Source: Defendants' employee compensation data; SEC filings. Page 59 Expert Report of Edward E. Leamer, Ph.D. 379 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page64 of 81 CONFIDENTIAL 10/1/2012 Figure 16: Constant Attribute Compensation of Major Google Job Titles Base Salary Source: Defendants' employee compensation data. Total Compensation Source: Defendants' employee compensation data; SEC filings. Page 60 Expert Report of Edward E. Leamer, Ph.D. 380 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page65 of 81 CONFIDENTIAL 133. 10/1/2012 To illustrate this further, Figure 17 depicts salary trends of top titles for Apple. Each line represents a single year. The collection of lines indicates that, Figure 17: Constant Attribute Compensation Ranking of Major Apple Job Titles is Generally Stable Source: Defendants' employee compensation data; SEC filings 134. These charts reveal a persistent salary structure across employees consistent with important elements of equity in the Defendants’ compensation practices. The non-compete-agreements which might tend to focus on subsets of workers would nonetheless have effects that would spread across all or almost all employees at the firm in order to maintain the overall salary structure. Page 61 Expert Report of Edward E. Leamer, Ph.D. 381 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page66 of 81 CONFIDENTIAL 10/1/2012 3. Standard Econometric Analysis Is Capable of Showing That the Non-Compete Agreements Artificially Suppressed Compensation to the Members of Each Class Generally 135. I have concluded that standard forms of econometric analysis are capable of computing the aggregate amount of compensation suppression to the AllEmployee Class and Technical Employee Class caused by the Non-Compete Agreements. 136. An estimate of the effect of the Non-Compete Agreements on employee compensation can be found by contrasting compensation during the periods when the Agreements were in effect with compensation before and after the Non-Compete Agreements. 137. A search for comparison periods needs to be sensitive to the economic cycle. The interval of time for which all the Defendants have produced compensation data extends from 2001 to 2011. This ten-year interval includes a mild U.S. recession, a severe global recession, two tepid U.S. recoveries and a brief period of housing-led high growth. Roughly speaking, we can divide the 2001 to 2011 period as shown in Figure 18. Figure 18: Growth Cycle Periods for the U.S. Economy Period Growth (1) (2) 2001 2002 - 2003 2004 - 2005 2006 - 2007 2008 - 2009 2010 - 2011 138. Mild US recession Tepid recovery Housing led growth Weakening  growth from weakening  housing Severe global recession Tepid recovery Figure 19 reports the average percent change by year in total compensation for all seven Defendants.172 Total compensation is the sum of December base In addition to the mean, the table includes the median, the 90th percentile, the standard deviation and the number of observations. 172 Page 62 Expert Report of Edward E. Leamer, Ph.D. 382 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page67 of 81 CONFIDENTIAL 10/1/2012 salary bonuses, overtime and equity compensation. Observations are restricted to cases in which there was no change in employer. 139. The year 2002 in the wake of the 2001 recession has a large 4.7 percent decline in average total compensation and that was followed by another 2.3 percent decline in 2003. Circumstances for employees improved dramatically in 2004 with an average 10.3 percent increase in total compensation. Next comes the out-of-place small 0.5 percent increase in 2005, coincident with the start of the Non-Compete Agreements. Subsequently the average gains in compensation fluctuated between 6 percent and 9 percent, with the value of 6.8 percent in 2008 in the midst of the severe global recession. Figure 19: Average Percent Change in Total Compensation Change in Total Compensation Estimated Underpayment Number of Employees Median 90th Percentile Std. Dev. Initial1 Cumulative (2) (3) (4) (5) (6) (7) (4.7)% (2.3) 10.3 0.5 9.1 7.4 6.8 7.4 6.5 9.7 (1.5)% (0.0) 11.5 0.2 8.8 4.3 8.9 2.8 8.0 7.6 10.2 % 13.2 22.9 14.7 24.7 26.8 23.1 34.9 22.9 29.4 19.5 % 19.9 18.7 20.3 23.3 26.0 25.7 24.4 22.7 23.5 5.1 % 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Mean (1) Year 5.1 % 22.3 % 22.4 % 58,465 58,176 57,835 59,494 64,620 64,680 66,055 69,178 69,727 74,989 Average (9.5)% (0.9) (2.6) 0.0 0.0 (9.5)% (10.3) (12.9) (12.9) (12.9) 1 Calculated as the average change in total compensation for the year minus the average changes in total compensation in 2004 and 2011. Notes: (1) Change in compensation measured only on employees that did not switch jobs from previous year (2) Total compensation measured as base salary as of December plus annual bonuses, overtime compensation, and stock options and restricted stock awards. Source: Defendants' employee compensation data; SEC filings. 140. Before undertaking a formal regression analysis of damages, we can use these annual numbers to do a preliminary informal impact assessment. The impact is suggested by comparing what was happening during the agreement period with Page 63 Expert Report of Edward E. Leamer, Ph.D. 383 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page68 of 81 CONFIDENTIAL 10/1/2012 what was happening in relevant periods before and after. The years 2004 and 2011 arguably are useful before and after comparisons since these reveal the kind of compensation increases that occur in expansion periods that were similar to 2005-2007. The “during” years 2008 and 2009 were severe recession years for which there may be no relevant direct comparisons. The column labeled “Estimated Underpayment” has values in 2005-2007 equal to the difference between the percent increase in total compensation that actually occurred minus the average of total compensation in 2004 and 2011. This same column has zero values for 2008 and 2009, built on the idea that the weak economy would not have resulted in increases in those periods. The last column cumulates these effects to find the total impact year by year. A large impact on compensation comes in 2005 since that 0.5 percent actual change in average total compensation translates into a 9.5 percent undercompensation. The under-compensation cumulates to 12.9 percent in 2009. 141. While the results in Figure 19 are suggestive, they rely on informal choices of comparison period, and they do not make any distinctions among the defendants. Regression analysis is a better approach because it allows the choice of comparison period to be “constructed” statistically, and it allows for differences among defendants as well as for employees. Figure 20 reports a regression equation which explains the logarithm of total compensation at the individual level with a variety of individual, firm and temporal effects. The variables are defined in Figure 21 and the implied effects of the agreements on total compensation are recorded in Figure 22. 142. The variables in the regression in Figure 20 are divided by solid borders into five principle categories:  Conduct Effects: How the Agreements affected total compensation and how the effects vary across time, firms and individuals,  Persistence: How the effects linger over time,  Worker Effects: How compensation normally varies across workers,  Industry Effects: How compensation normally varies over time, and Page 64 Expert Report of Edward E. Leamer, Ph.D. 384 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page69 of 81 CONFIDENTIAL 10/1/2012  Employer Effects: How compensation normally varies across firms. 143. The worker variables are age, company tenure, and gender. The variables that drive the temporal changes are rate of growth of payroll jobs in information in Santa Clara County, the number of new employees hired by all defendants, the number of workers who moved between Defendants and a time trend. The effects that vary across employers are global revenue relative to the global workforce and the rate of growth thereof, the number of new workers hired relative to the previous year’s workforce, and indicators that allow for distinct differences in compensation for each employer. 144. The persistence variables are the levels of total compensation in the previous year and the year before that, two for each employer. The fact that these numbers sum to around 90 percent indicates very persistent effects, meaning when a worker gets a bump up in compensation in some year that makes him or her better off than comparable coworkers, that effect lingers on for many years. 145. The CONDUCT variable measures the fraction of months in each year during which the employer was involved in one or more of the agreements. The conduct variable is interacted with three variables to allow for the possibility that the agreements had effects that varied over time, across firms and across individuals. 146. This regression model can be used to estimate the undercompensation year by year, employer by employer, reported in Figure 22. The part of the estimated regression that involves the CONDUCT variable is used to estimate the immediate impact of the illegal CONDUCT. These immediate impacts are propagated over time as implied by the dynamic structure of the model determined by the coefficients on the once-lagged and twice-lagged total compensation explanatory variables that follow the CONDUCT variables in the regression. The totals of the direct and secondary effects of the agreements on total compensation by year and by defendant are reported in Figure 22. Page 65 Expert Report of Edward E. Leamer, Ph.D. 385 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page70 of 81 CONFIDENTIAL 10/1/2012 Figure 20: Regression Estimate of Undercompensation to Class All-Salaried Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation/CPI) Variable Conduct * Age Conduct * Age^2 Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1)) Conduct ADOBE * Log(Total Annual Compensation/CPI) (-1) APPLE * Log(Total Annual Compensation/CPI) (-1) GOOGLE * Log(Total Annual Compensation/CPI) (-1) INTEL * Log(Total Annual Compensation/CPI) (-1) INTUIT * Log(Total Annual Compensation/CPI) (-1) PIXAR * Log(Total Annual Compensation/CPI) (-1) LUCASFILM * Log(Total Annual Compensation/CPI) (-1) ADOBE * Log(Total Annual Compensation/CPI) (-2) APPLE * Log(Total Annual Compensation/CPI) (-2) GOOGLE * Log(Total Annual Compensation/CPI) (-2) INTEL * Log(Total Annual Compensation/CPI) (-2) INTUIT * Log(Total Annual Compensation/CPI) (-2) PIXAR * Log(Total Annual Compensation/CPI) (-2) LUCASFILM * Log(Total Annual Compensation/CPI) (-2) Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Year (trend) Log(Number of New Hires In the Firm/Number of Employees(-1)) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Revenue Per Employee/CPI) (-1) APPLE GOOGLE INTEL INTUIT LUCASFILM PIXAR Location (State) Indicators Constant R-Square Observations St. Error T-Value (1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. Estimate (2) (3) (1)/(2) 0.0067 *** -0.0001 *** 0.0028 *** -0.1647 *** 0.6949 *** 0.7404 *** 0.4945 *** 0.6690 *** 0.7090 *** 0.6944 *** 0.8131 *** 0.2963 *** 0.2610 *** 0.3732 *** 0.3001 *** 0.2551 *** 0.1983 *** 0.1779 *** -0.3591 *** 0.0394 *** 0.0107 ** -0.0012 ** 0.0027 *** 1.4353 *** 0.0961 *** -0.0038 *** 0.0154 *** -0.2485 *** -0.1070 *** 0.2170 *** 0.0627 *** 1.0364 *** 0.1522 *** 0.1462 *** 0.1352 *** 0.7251 *** YES YES 0.0005 0.0000 0.0008 0.0100 0.0054 0.0027 0.0017 0.0024 0.0058 0.0069 0.0363 0.0053 0.0027 0.0016 0.0023 0.0056 0.0067 0.0367 0.0415 0.0056 0.0050 0.0006 0.0005 0.0147 0.0015 0.0003 0.0009 0.0021 0.0035 0.0033 0.0162 0.0174 0.0146 0.0193 0.0481 0.0422 14.1138 -14.0235 3.6947 -16.5007 127.9743 278.6889 291.4208 282.4408 123.0243 100.1556 22.4035 55.9130 95.3635 228.3877 130.2277 45.7056 29.5094 4.8520 -8.6468 6.9805 2.1371 -2.1619 4.9116 97.4954 63.7243 -14.3189 16.6057 -116.9807 -30.1447 66.3627 3.8765 59.6506 10.4453 7.5835 2.8127 17.1808 0.926 504,897 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted. (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources. (5) Observations are restricted to cases in which there was no change in employer in the previous two years. Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; PrivCo and public sources. Page 66 Expert Report of Edward E. Leamer, Ph.D. 386 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page71 of 81 CONFIDENTIAL 10/1/2012 Figure 21: Data Definitions Variable 1. Description (1) (2) Total Annual Compensation Sum of base annual salary as of December, total bonuses, overtime amount and equity compensation received in the year 2. CPI U.S. Consumer Price Index (St. Louis Federal Reserve) 3. Conduct Indicator defined as a fraction of the year the defendant had an active cold-calling agreement 4. Age Age of the employee in years 5. Number of New Hires In the Firm Number of employees newly hired in the year (i.e. not counting individuals who might have been previously employed in the company) 6. Company Tenure Number of months an employee has been affiliated with the company 7. Male Indicator for male employees 8. Information Sector Employment in San Jose Employment in San Jose/Santa Clara Valley in the Information Sector (St. Louis Federal Reserve) 9. Total Number of Transfers Among Defendants Total number of employees who moved from one defendant to another in the year 10. Total Number of New Hires Total number of original employees hired by all defendants in the year 11. Firm Revenue Per Employee Global revenue of the company divided by global employment in the company (SEC Filings; PrivCo; and public sources) Figure 22: Estimated Impact on Class Total Compensation Annual Undercompensation Percentages All-Salaried Employee Class ADOBE 2005 2006 2007 2008 2009 APPLE GOOGLE INTEL -1.61% -4.28% -6.64% -9.08% -9.15% -1.59% -4.43% -6.94% -9.56% -9.73% -1.78% -4.44% -6.39% -8.40% -7.51% -1.67% -4.70% -7.46% -10.05% -9.95% INTUIT LUCASFILM PIXAR -3.24% -5.64% -5.70% -12.13% -14.63% -17.24% -19.94% -20.12% -10.56% -12.44% -14.28% -15.76% -14.65% Source: Regression Estimates of Undercompensation to All-Salaried Employee Class. Page 67 Expert Report of Edward E. Leamer, Ph.D. 387 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page72 of 81 CONFIDENTIAL 147. 10/1/2012 I performed the same analysis for the set of employees in the Technical Employee Class. The regression model for this Technical Employee Class is reported in Figure 23 and the corresponding damage estimates in Figure 24. Page 68 Expert Report of Edward E. Leamer, Ph.D. 388 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page73 of 81 CONFIDENTIAL 10/1/2012 Figure 23: Regression Estimate of Undercompensation to Technical Employee Class Technical, Creative and R&D Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation/CPI) Variable Conduct * Log(Age) Conduct * Log(Age)^2 Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1)) Conduct ADOBE * Log(Total Annual Compensation/CPI) (-1) APPLE * Log(Total Annual Compensation/CPI) (-1) GOOGLE * Log(Total Annual Compensation/CPI) (-1) INTEL * Log(Total Annual Compensation/CPI) (-1) INTUIT * Log(Total Annual Compensation/CPI) (-1) PIXAR * Log(Total Annual Compensation/CPI) (-1) LUCASFILM * Log(Total Annual Compensation/CPI) (-1) ADOBE * Log(Total Annual Compensation/CPI) (-2) APPLE * Log(Total Annual Compensation/CPI) (-2) GOOGLE * Log(Total Annual Compensation/CPI) (-2) INTEL * Log(Total Annual Compensation/CPI) (-2) INTUIT * Log(Total Annual Compensation/CPI) (-2) PIXAR * Log(Total Annual Compensation/CPI) (-2) LUCASFILM * Log(Total Annual Compensation/CPI) (-2) Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Year (trend) Log(Number of New Hires In the Firm/Number of Employees(-1)) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Revenue Per Employee/CPI) (-1) APPLE GOOGLE INTEL INTUIT LUCASFILM PIXAR Location (State) Indicators Constant R-Square Observations St. Error T-Value (1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. Estimate (2) (3) (1)/(2) 0.0079 *** -0.0001 *** -0.0121 *** -0.2196 *** 0.6744 *** 0.7234 *** 0.4367 *** 0.6401 *** 0.6703 *** 0.6491 *** 0.8462 *** 0.3053 *** 0.2538 *** 0.3659 *** 0.3179 *** 0.2857 *** 0.1045 *** 0.1448 ** -0.5894 *** 0.0696 *** 0.0297 *** -0.0025 *** 0.0065 *** 1.4378 *** 0.0973 *** -0.0008 ** 0.0240 *** -0.2720 *** -0.0661 *** 0.2068 *** 0.1220 *** 1.3682 *** 0.1569 *** 0.1393 *** 0.0127 1.5864 *** YES YES 0.0007 0.0000 0.0010 0.0140 0.0073 0.0037 0.0022 0.0030 0.0085 0.0106 0.0692 0.0071 0.0038 0.0021 0.0029 0.0082 0.0097 0.0693 0.0588 0.0080 0.0068 0.0008 0.0008 0.0204 0.0020 0.0004 0.0013 0.0029 0.0049 0.0044 0.0245 0.0259 0.0219 0.0315 0.1037 0.0771 11.6667 -11.4844 -11.5872 -15.6471 92.4832 197.6595 200.6585 215.3504 79.1708 61.3919 12.2257 42.7525 67.0286 174.3271 110.4491 34.8914 10.8013 2.0884 -10.0182 8.7006 4.3581 -3.3821 7.8837 70.3710 47.5566 -2.1643 18.6766 -92.8937 -13.4914 46.8319 4.9879 52.7958 7.1705 4.4202 0.1226 20.5741 0.874 292,489 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted. (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources. (5) Observations are restricted to cases in which there was no change in employer in the previous two years. Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; PrivCo and public sources. Page 69 Expert Report of Edward E. Leamer, Ph.D. 389 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page74 of 81 CONFIDENTIAL 10/1/2012 Figure 24: Estimated Impact on Technical Employee Class Total Compensation Annual Undercompensation Percentages Technical, Creative and R&D Class ADOBE APPLE GOOGLE INTEL -1.56% -4.29% -6.48% -8.80% -8.44% -1.90% -4.96% -7.79% -10.64% -10.51% -3.07% -7.23% -9.36% -11.20% -9.00% -1.64% -3.06% -3.38% -4.76% -4.19% 2005 2006 2007 2008 2009 INTUIT LUCASFILM PIXAR -3.41% -5.21% -4.96% -10.80% -14.77% -18.08% -20.44% -20.54% -9.28% -10.47% -10.61% -11.87% -9.62% Source: Regression Estimates of Undercompensation to Technical, Creative, and R&D Class. 148. V. Accordingly the undercompensation figures resulting from the estimation of this econometric model of employee compensation (as reported in Figure 22 and Figure 24 can be used in a straightforward formulaic fashion in conjunction with the All-Employee Class and Technical Employee Class compensation data (as reported in Figure 3 and Figure 4) to calculate damages for employees in either the All-Employee Class or the Technical Employee Class. Conclusion 149. I therefore conclude that common proof, in the form of documents, data, economic theory, and statistical methodologies, is capable of demonstrating that the Non-Compete Agreements artificially suppressed compensation of all or nearly all members of the All-Employee Class and Technical Employee Class. I conclude further that reliable econometric methods are capable of computing Page 70 Expert Report of Edward E. Leamer, Ph.D. 390 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page75 of 81 391 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page76 of 81 CONFIDENTIAL 10/1/2012 APPENDIX A. Defendant Data Relied Upon A. Description of Data Requested and Produced 150. Defendants produced two types of data: employee compensation and hiring and recruiting data. Employee compensation data contains compensation information for salaried employees that were active during the period of January 1, 2001 through February 1, 2012 at each defendant.173 Hiring and recruiting data contains job applicant information for all potential candidates during the period of January 1, 2001 through February 1, 2012 for each defendant. 1. Employment Data 151. Plaintiffs requested each defendant produce compensation histories for all salaried employees that were active during the period of January 1, 2001 through February 1, 2012. The information requested includes personal information (an encrypted social security number allowing employees to be matched across defendants, hire date, previous employer information, birth year, gender, education level, and channel of hiring) and on-going job information (job title and level, salary, bonus awards, benefits, stock option grants, office location, and manager ID). Additionally plaintiffs requested employee information that identifies drivers of compensation (information regarding changes in titles or jobs within a company) and exit information for employees that were terminated. 2. Recruiting Data 152. Plaintiffs requested each defendant produced recruiting data for the period of January 1, 2001 through February 1, 2012. The information contained in the recruiting data should consist of application date, applicant’s resume information (employer, job title, and education level), the source through which Employees can be “exempt” or “non-exempt”. See e.g., 76512DOC000638-677 at 641. Exempt workers are salaried and generally not entitled to overtime pay. They generally have advanced professional training or a degree. Class members are salaried and so are generally exempt. 173 Page 72 Expert Report of Edward E. Leamer, Ph.D. 392 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page77 of 81 CONFIDENTIAL 10/1/2012 the application originated (cold called by recruiter, applied on website, etc.), and outcome (hired, rejected, etc.). 153. Additionally, plaintiffs requested that defendants provide detailed Cold-Calling data for the period of January 1, 2001 through February 1, 2012. The information contained in the Cold-Calling recruiting data should consist of a unique identifier for each candidate contacted, date of contact, and candidate’s resume information (employer, job title, education level, experience), the source through which the application originated (cold called by recruiter, applied on website, etc.), and outcome (hired, rejected, etc.). Though some defendants have produced some of their candidate tracking information, they have yet to produce enough information to determine Cold-Calling activities. B. Datasets Created for Analysis 154. Compensation data from all defendants was cleaned and processed in order to generate a Master Employee dataset with monthly compensation and employee information for 2001 - 2012. The information included in the master dataset includes each person’s hashed SSN, employer and job title for each month in 2001-2012 for which a person is employed by one of the defendants, person’s information (age, gender), original and current hire dates, termination dates, tenure of employment, annual performance evaluation score, dates of changes in salary and title, previous employer information, department, job grade and job family information, leave of absence dates, annualized base compensation, bonus compensation, stock options and equity compensation,174 overtime compensation for non-exempt employees, and employee status identifiers (FLSA status, part time and full time identifiers, temporary employee identifiers, etc.). To compute employee stock compensation, the ‘Weighted average grant date fair value’ for stock options and restricted stock as reported by the defendants in their annual SEC filings was multiplied by the number of options or restricted stock units granted to the employee. 174 Page 73 Expert Report of Edward E. Leamer, Ph.D. 393 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page78 of 81 CONFIDENTIAL 10/1/2012 APPENDIX B. Definition of the Technical Employee Class 155. I was asked to identify employees that fit with in Technical Employee Class, defined to include all full-time salaried employees of Defendants during the period of the alleged agreements (see Figure 1) that worked in technical, creative, and research & development positions. The following job descriptions were included within this Technical Employee Class : 1. Software Engineers, 2. Hardware Engineers and Component Designers, 3. Application Developers, 4. Programmers, 5. Product Developers, 6. User Interface or User Experience Designers, 7. Quality Analysts, 8. Research and Development, 9. Animators, Digital Artists, Creative Directors and Technical Editors, 10. Graphic Designers and Graphic Artists, 11. Web developers, 12. IT professionals, 13. Systems engineers and administrators, and 14. Employees classified as technical professionals by their employers. The Technical Employee Class does not include the following types of employees: 1. Non-technical employees (marketing, accounting, finance, operations, etc.) 2. Senior executives, Page 74 Expert Report of Edward E. Leamer, Ph.D. 394 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page79 of 81 CONFIDENTIAL 10/1/2012 3. 4. Network administrators, 5. Systems support/maintenance personnel, 6. Facilities maintenance employees, or 7. 156. Non-US employees, Manufacturing technicians. Several defendants provided a “Job Family” designation with their employment data. The majority of class members fall under the job families listed in Figure 25 below. Figure 25: Adobe, Apple, Google, Intel, and Intuit Creative, Technical, and R&D Job Families Adobe Apple Google Intel RSCH & DEV IS&T R&D ADSALES_CSE ENG_DEV_ADV ENG_MEMBER ENG_PROG ENG_RES ENG_SOFT ENG_SOFT_MGR ENG_SQAE ENG_SRE_SWE ENG_SRE_SYSADMIN ENG_TECH_WRITERS ENG_TECHPROG ENG_UI ENG_USAB ENT_ESO ENT_SE MKTG_CREATIVE ONLINE_SALES_TECH_OPS OPS_DCFAC_ENG OPS_NET OPS_SYS OPS_TECH SALES_ENG SALES_TSE Intuit CAD ENGINEERING COMPONENT DES ENGINEERING ELECTRONIC ENGINEERING ENGINEERING ENGINEERING MANAGEMENT HARDWARE ENGINEERING INFORMATION DATA ANALYSES INFORMATION NETWORKS INFORMATION SERVICES INFORMATION TECH MANAGEMENT MASK DESIGN MECHANICAL ENGINEERING MKTG ENGINEERING MANAGEMENT PROCESS ENGINEERING PRODUCT ENGINEERING PROGRAMMING PROJ/PROG MANAGEMENT QUALITY ENGINEERING RESEARCH & DEVELOPMENT RESEARCH ENGINEERING SOFTWARE ENGINEERING SYSTEMS ENGINEERING SYSTEMS SUPPORT TECH TECH MARKETING ENGINEERING TECHNICAL TECHNICAL WRITING TEST ENGINEERING APPLICATIONS CREATIVE DESIGN DATA ADMIN-ANALYST DATABASE ADMINISTRATION DESKTOP SYSTEMS DEVELOPMENT MANAGEMENT DOCUMENTATION INFORMATION SECURITY INFORMATION TECHNOLOGY INTERACTION DESIGN IT IT MANAGEMENT NETWORK ADMINISTRATION NETWORK ENGINEERING PRODUCT DEVELOPMENT MGMT PRODUCT MANAGEMENT QA ENGINEERING SCM ENGINEERING SOFTWARE ENGINEERING SOFTWARE QA ENGINEERING SYSTEMS USER INTERFACE DESIGN WEB DEVELOPMENT WEB ENGINEERING WEB PRODUCTION Source: Defendants' employee compensation data 157. There are additional Technical Employee Class members who fall under other categories. Additional criteria were taken to select class titles: Page 75 Expert Report of Edward E. Leamer, Ph.D. 395 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page80 of 81 CONFIDENTIAL 10/1/2012 a. Adobe Employees classified by Adobe as “Technical Professionals” based on the field “AAP Code Description” in its compensation data as well as the “Business Unit” and “Function Name” fields were included in the Technical Employee Class.175 b. Apple Non-facilities engineers, web developers, graphic designers, and other technical titles not classified as part of the R&D or IS&T job families were included in the Technical Employee Class. All R&D and IS&T support titles (librarian, technicians, etc.) were excluded. c. Google Google identifies technical employees by job grade levels beginning with “T”.176 Additionally, technical employees in operating and support fields such as IT, Systems, as well as web designers, application developers and other creative and technical roles were included in the Technical Employee Class. Excluded from the Technical Employee Class were support roles (e.g., tech support and desktop support). d. Intel Intel identifies technical employees through their job families. Additional job families included in the Technical Employee Class were all non-facilities engineering job families, as well as graphic and web design and developer families. Excluded were nontechnical roles as well as manufacturing technicians and machinery operators. 175 See Adobe compensation data (FY2001_HighlyConfidentialAEO-FY2012_HighlyConfidentialAEO). 176 GOOG-HIGH TECH-00057189. Page 76 Expert Report of Edward E. Leamer, Ph.D. 396 Case5:11-cv-02509-LHK Document518-1 Filed10/07/13 Page81 of 81 CONFIDENTIAL 10/1/2012 e. Intuit Intuit identifies technical employees through their job families. Additional job families included in the Technical Employee Class were all software engineering and application developer families, non-facilities engineering job families, as well as graphic and web design and developer families. Excluded were nontechnical roles as well system support and technician roles. f. Lucasfilm and Pixar Neither Lucasfilm nor Pixar provided job families to identify creative, R&D, and technical employees. For both cases, class members were selected on the basis of their job titles.177 Employees were identified as Technical Employee Class members if their titles identified them as Animators, Artists, Software Engineers, Engineers, Scientists, Researchers, R&D professionals, Technical Directors, Designers, Modelers, or IT and Systems staff. Excluded from the list were videographers, camera operators, technicians and system support employees. Lucasfilm employees prior to 2006, for whom we are missing job title information, are identified as being in the Technical Employee Class if their titles in the 20062012 compensation data are flagged as Technical Employee Class titles. Pixar did provide department information that groups technical roles such as the Studio Tools group, the Systems group, and others as well. 177 Page 77 Expert Report of Edward E. Leamer, Ph.D. 397 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page1 of 66 IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA SAN JOSE DIVISION CONFIDENTIAL – TO BE FILED UNDER SEAL SUBJECT TO PROTECTIVE ORDER IN RE: HIGH-TECH EMPLOYEES ANTITRUST LITIGATION No. 11-CV-2509-LHK _____________________________________ THIS DOCUMENT RELATES TO: ALL ACTIONS REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D. December 10, 2012 398 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page2 of 66 TABLE OF CONTENTS I.  Introduction, Assignment, and Summary of Conclusions .............................................1  II.  Dr. Murphy Has No Sound Basis for His Conclusion that the Agreements Did Not Materially Limit Information about Outside Opportunities ..................................3  A.  Dr. Murphy Has No Basis to Support His Assertion That Other Channels of Information Are More Important than Cold Calling......................................................3  B.  Dr. Murphy Incorrectly Assumes that Inter-Defendant Hiring Produces Information that is Equivalent to Cold-Calling .............................................................7  C.  Dr. Murphy Does Not Understand the Important Difference between Movement and Mobility ...................................................................................................................8  D.  Dr. Murphy Understates the Information Provided by Cold Calling...........................10  E.  Dr. Murphy’s Analysis of Defendants’ Hiring Is Irrelevant and His Conclusion from It of No Effect on Compensation Is Unsupported ...............................................11  F.  Dr. Murphy Has Not Disputed that the Agreements Reduced Cold-Calling and Competition Among the Defendants for Employees ...................................................13  G.  Dr. Murphy Incorrectly Argues that Interference in the Information Flow Would Not Affect Compensation At All .................................................................................14  III.  Contrary to Dr. Murphy’s Opinion Under-Compensation Would Have Impacted All or Almost All Class Members ...................................................................................16  A.  There is Ample Evidence in the Defendants’ Documents and Depositions that Internal Equity Played a Key Role in Wage Setting. ...................................................18  B.  There is Abundant Economics Literature on the Role of Fairness in Wage Setting ...19  C.  Class-Wide Evidence That Includes Google’s “Big Bang” Response to Facebook Demonstrates How Competitive Pressure From One Peer Firm Can Move An Entire Pay Structure Overnight ....................................................................................23  D.  Dr. Murphy is Incorrect that the Defendants’ Data Do Not Indicate that Fairness and Internal Equity Matter ...........................................................................................27  E.  Dr. Murphy is Incorrect that My Hedonic Analysis of Named Plaintiffs’ Compensation Performed Poorly .................................................................................31  IV.  My Conduct Regressions Are Reliable Class-Wide Evidence That the Agreements Suppressed Compensation on a Widespread Basis .................................33  A.  Calculation of Standard Errors Assumes Statistical Independence .............................35  i Reply Expert Report of Edward E. Leamer, Ph.D. 399 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page3 of 66 1.  Dr. Murphy Relies on a “Somewhat” Rigid Wage Structure in his Adjustment of the Standard Errors. ...........................................................................................36  2.  The Best Solution is to Include Variables that Eliminate the Correlation Problem ..................................................................................................................37  3.  Dr. Murphy’s Employer-Year Fixed Effects Proves too much as it would Invalidate Any Before-During-and-After Model ...................................................37  B.  Dr. Murphy’s “Sensitivity Analysis” is Flawed ..........................................................38  1.  Dr. Murphy’s Study of Data Subsets Typifies What Happens When a Model is Overloaded .............................................................................................................45  2.  Dr. Murphy's Partial Disaggregation by Defendant is Improperly Implemented in a Manner Designed to Make the CONDUCT Variable Perform Poorly ...........46  3.  Firm-Wide Data Can Correct for the Correlation Problem ...................................48  C.  Both Dr. Murphy’s and My Conduct Regression Analyses Demonstrate the Feasibility of the Regression Approach .......................................................................53  V.  Conclusion ........................................................................................................................53  ii Reply Expert Report of Edward E. Leamer, Ph.D. 400 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page4 of 66 CONFIDENTIAL I. 12/10/2012 Introduction, Assignment, and Summary of Conclusions 1. I have been asked by counsel for Class Plaintiffs in this matter to review the Report and Deposition of Defendants' expert Dr. Murphy and reply to his comments that bear on the conclusions in my Original Report. A list of materials I have relied upon (in addition to those listed in my original report) is provided in Exhibit 1. 2. Dr. Murphy lists five opinions in his summary that can be combined into three principal categories:1 In this report I explain why each of these opinions of Dr. Murphy is in error. I stand by the conclusions in my original report, namely that common theoretical, documentary and quantitative evidence can be used to prove the common impact of the agreements on class members. 3. My summaries of Dr. Murphy’s three central opinions and summaries of my rebuttal arguments are as follows: 4. Murphy Opinion:2 As a matter of economic theory, the agreements are too limited and too inconsequential to matter at all, given the multiple methods by which firms recruit workers, and given the small fraction of overall hiring that was covered by the agreements, and given the small number of inter-defendant transfers from 2001 to 2011. 5. Rebuttal: (1) The market equilibrium models to which Dr. Murphy refers are not applicable to Defendants’ agreements because these models assume perfect knowledge, whereas the direct effect of the agreements was to reduce the information available about outside opportunities. While models of market equilibrium which assume perfect information imply that the agreements might be inconsequential, models with imperfect information allow for the possibility or even the likelihood that small changes in the information flow have large consequences. (2) The cold calling that was suppressed in principle would have provided better information in a more timely way than any other information channel. (3) For wages to respond to outside competition what matters is mobility, not movement of workers. The amount of hiring and the amount of inter-defendant movement is an 1 Expert Report of Kevin M. Murphy, November 12, 2012 (the “Murphy Report”), pp.6-13. 2 Murphy Report, pp.6-8. Page 1 Reply Expert Report of Edward E. Leamer, Ph.D. 401 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page5 of 66 CONFIDENTIAL 12/10/2012 unreliable indictor of mobility, since there can be mobility without movement and there can also be movement without mobility, for example, when a worker is fired. 6. 7. Rebuttal: (1) The fact that “fairness” and internal equity can affect compensation is clearly established in the economics literature. (2) The fact that fairness and internal equity actually did affect compensation at the seven Defendants is clearly established by the HR documents and depositions of the Defendants, and also by Google’s decision in 2010 to do an across-the-board increase in base salaries by 10 percent in response to a relatively small loss of workers to Facebook. (3) My common factor regressions are consistent with a “somewhat rigid” compensation system but are not by themselves a proof of fairness effects. These regressions confirm the hierarchical title/grade method of determining compensation that all of the Defendant firms used. This hierarchical compensation structure allows the force of fairness to play a role in setting compensation levels, something that is established in the economics literature.4 8. Murphy Opinion:5 Neither Leamer’s conduct regression model nor any other similar regression model based on data from the proposed classes can be relied upon to determine the effects of the agreements because the regression model has residuals and because the estimates change “too much” when new variables are added into the equation. 9. 3 Murphy Opinion:3 Whatever impact there might have been on a few individuals, this effect was not spread across all or most members of the proposed classes because these firms do not allow internal equity concerns (fairness and revenue sharing) to play a role in the determination of compensation of employees. In particular, the “common factor” regressions that Leamer reports do not establish that internal equity mattered. Rebuttal: (1) The method of regression is a completely standard way of carrying out a damage analysis. (2) The existence of unexplained residuals, large or small, Murphy Report, p.10. 4 See e.g., Rees, A. "The Role of Fairness in Wage Determination," Journal of Labor Economics, 1993, Vol. 11, No. 1, pt. 1. 5 Murphy Report, p. 11. Page 2 Reply Expert Report of Edward E. Leamer, Ph.D. 402 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page6 of 66 CONFIDENTIAL 12/10/2012 does not in any way invalidate the method of regression. (3) Estimated regression models will almost always change when new variables are added. (4) Dr. Murphy’s modifications to my conduct regression (defendant disaggregation, and regression with subsets) more than exhaust the information in the data set and are predetermined to produce wild results. (5) The other variable that Murphy explores (the S&P 500) illustrates that nonsense variables can also produce wild results. Dr. Murphy uses the S&P index’s annual closing value in his estimation, as opposed to the annual average of the S&P index. By making this choice, he implies that compensation decisions throughout the year depend only on the end-of-year level of the index, nothing in between, and do so with perfect foresight. More importantly, this variable doesn’t belong in this equation because the link between the S&P index and compensation at the seven Defendants is very remote, given the other control variables in my equation. II. Dr. Murphy Has No Sound Basis for His Conclusion that the Agreements Did Not Materially Limit Information about Outside Opportunities 10. Dr. Murphy’s conclusion that information about outside opportunities was not limited by the agreements is based on an unsupported assumption and an irrelevant fact. Absent any data regarding the breadth or frequency of cold calling, or any way of measuring the amount of information provided by cold calls compared with other sources, Dr. Murphy merely assumes either that the cold calls provided redundant information because of the amount of hiring not covered by the agreements or he assumes that the prevented cold calls were replaced with other information flows. Absent any evidence about the effects of the agreements on mobility of the affected workers, Dr. Murphy uses an unreliable proxy for mobility, the level of inter-Defendant hiring.6 A. Dr. Murphy Has No Basis to Support His Assertion That Other Channels of Information Are More Important than Cold Calling 11. 6 Dr. Murphy’s first proposition, that “cold-calling” accounted for a small amount of Defendants’ hiring activity is founded on little more than an irrelevant anecdote collected in an unscientific and unrepresentative “survey” of Defendants’ HR Murphy Report, ¶ 27. Page 3 Reply Expert Report of Edward E. Leamer, Ph.D. 403 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page7 of 66 CONFIDENTIAL 12/10/2012 employees hand-picked by lawyers, and it reveals nothing about the importance of cold calling in the provision of information. 12. Cold-calling is a distinct and special channel of information that accesses job candidates who otherwise would be left unaware of attractive opportunities. The record does not indicate that there are close substitutes for cold calling, and Dr. Murphy’s unscientific surveys of a group of Defendant HR employees has produced nothing to the contrary. What he has learned is only that there are other means of recruiting: “But nonetheless, I think a number of the individuals from the various companies gave some quantitative assessments in their declarations and in their discussions. They talked about the fraction of people hired through various means.” 7 13. Dr. Murphy’s reference to vague information about the fractions of people hired by various methods tells us nothing about what was irretrievably lost when the anticold-calling agreements were put in place, if anything. By relying on a few interviews to conclude that the anti-cold-calling agreements had little or no impact on the information flow, Dr. Murphy effectively assumes that the information conveyed by Google’s hiring activities at a college job fair, for example, is a perfect substitute for cold-calls by Google to Apple employees.8 As I describe below, this unlikely hypothesis would need to be tested, which Dr. Murphy has not done. 14. Dr. Murphy says that the data do not exist to test his hypothesis.9 Instead, Dr. Murphy’s basis seems little more than that Defendants’ employees told him that referrals account for a much larger percentage of hiring than “cold-calling.” One of the many problems with this approach is that Dr. Murphy redefines the alleged conduct covered by the agreements to exclude referrals and to apply only to “totally passive candidate[s]” who had not in any way expressed interest in new 7 Murphy Deposition, pp. 61-62. 8 Deposition of Kevin M. Murphy, Ph.D., December 3, 2012 (Murphy Deposition), p. 127. 9 Murphy Report, p. 17, fn. 31. Page 4 Reply Expert Report of Edward E. Leamer, Ph.D. 404 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page8 of 66 CONFIDENTIAL 12/10/2012 employment.10 But, as I described in my report, the agreements are alleged to have prohibited cross-solicitation of the parties’ employees in any manner, whether as a result of a referral or not and whether recruiters identified potential candidates via networking websites such as LinkedIn or not.11 As I understand it, these agreements applied to all recruiters who were either directly employed by or were headhunters hired by the agreeing firms.12 Some of the agreements apparently went further, prohibiting hiring, requiring notification of hires, and prohibiting counteroffers.13 15. 10 The agreements also applied to employee referrals. Adobe senior executives made their understanding clear at the time. When the question arose “if an Adobe employee refers an Apple employee through our employee referral program are you okay with that?” the answer that Bruce Chizen, CEO of Adobe agreed with was, “I think the spirit has to be that we don’t initiate contact with Apple employees even Murphy Report, pp. 3-4, fn. 8. 11 See Expert Report of Edward E. Leamer, Ph.D., October 1, 2012 (“Leamer Report” or “my Report”), ¶ 23. 12 See e.g., 231APPLE001164, GOOG-HIGH TECH-00023500-601 at 520-528, and PIX00000400. 13 When present, this provision applied even when an employee initiated contact. See, e.g., 76577DOC000464. Even if certain agreements may not have begun with this express provision, they often operated in this manner in practice. For example, Pixar and Google sought Steve Jobs’s permission before making offers to Apple employees. See PIX00006025; 231APPLE002151. Apple refused to consider Adobe employees unless they first left employment with Adobe. See 231APPLE080776 (“This is a response I received from an ADOBE employee who applied for a position through our job posting site. I called him to ensure he is still an ADOBE employee, explained our mutual agreement / guidelines, and asked that he contact me should his employment with ADOBE terminate, but at this time I am unable to continue exploring with him. . . . I do not want anything in ‘writing’.”) Apple also attempted to enter into a “no hire” agreement with Palm, which Palm’s CEO Ed Colligan rejected. See PALM00005 – 008 at 006 and PALM00022 – 027 at 024. See also, 231APPLE002153 - 154, and 231APPLE002214. See also, PIX00000400; GOOG-HIGH TECH-00056790 and PIX00004051 (“We just won’t get into bidding wars” for employees.); LUCAS00013507 (“We have agreed we want to avoid bidding wars.”). Page 5 Reply Expert Report of Edward E. Leamer, Ph.D. 405 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page9 of 66 CONFIDENTIAL 12/10/2012 through our employees.”14 [emphasis added] Google and Pixar documents also show this to be the case.15 16. 14 The agreements affected the recruiting of even “non-passive candidates” i.e. those who were actively searching and who submitted applications in response to job postings or posted their resumes on the companies’ websites. Notice was given regardless of who initiated contact, as Google did before making an offer to an Intel employee who had not been cold-called.16 Notice also had to be given to Apple by Pixar before making an offer to an Apple employee (“My understanding was in order for us to consider an Apple employee as a candidate, we couldn’t make an offer without letting Steve Jobs know”).17 The same arrangement existed between Pixar and Intel.18 See ADOBE_001096-97 at 96. 15 Google enforced its “Do Not Call” agreements in the same way. “The key is the DNC candidate is initiating the ‘I am looking’ and there is written proof.” This included employee referrals: “All Googlers fall under the same DNC rules.” “If the Googler did reach out and initiate first contact (e.g., at a cocktail party) then we should walk away and not pursue the lead.” GOOG-HIGH TECH-00009270-276 at 270. See also Deposition of Arnnon Geshuri, August 17, 2012 at 187:25-189:1. Also see PIX00009271-72 at71 “You could check in, invite her over for coffee, see if she offers up any opening. If she did, we could talk to her, If not, we’d have to respect the truce.” 16 In August of 2006, Campbell agreed with Google’s Jonathon Rosenberg (Senior Vice President of Product Management) that Google should call Otellini before making an offer to an Intel employee, regardless of whether the Intel employee first approached Google. Shaver Decl., Ex. 37 [GOOG-HIGH TECH-00056790] (Rosenberg: “Campbell and I already discussed this [talking to Intel before making an offer to an Intel employee] and agreed that either way [whether Intel was treated as a “Do Not Call” company, or a “sensitive” company] I should give a courtesy call to Paul Otellini. I’m meeting with [the Intel candidate] tomorrow and I will ask him how he wants to handle communication to Intel management before we even get to the stage of specifically discussing an offer.”). 17 Deposition of Pamela Zissimos, November 13, 2012 at 125:6-8. 18 “We cannot recruit (including calling up, emailing or enticing in any way) current Pixar employees to come work for Intel. If a Pixar employee applies to Intel without being recruited by Intel, contact Pat Gelsinger [a Senior VP at Intel] and explain to him a Pixar employee (provide the candidates [sic] name) has applied to Intel without being recruited and he will he will [sic] contact the CEO of Pixar for approval to hire.” 76577DOC000464-466 at 466. Page 6 Reply Expert Report of Edward E. Leamer, Ph.D. 406 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page10 of 66 CONFIDENTIAL 12/10/2012 17. Hence, Dr. Murphy fails to acknowledge the full scope of the agreements and does not recognize that these agreements directly affected more than just “totally passive” employees. He therefore has no basis for the first thing he says we need to know to understand the agreements. 18. Moreover, debating or defining the scope of the agreements is not a proper exercise for an economist. I studied the agreements to have a factual background for statistical methods that I used to measure their effects empirically. Their actual meaning or scope will presumably be determined someday in a court of law. If Dr. Murphy’s opinion depends on his own evaluation of the true meaning of the agreements based on self-serving interviews with Defendant employees, then the first step in his formation of an opinion is not based on economic expertise. B. Dr. Murphy Incorrectly Assumes that Inter-Defendant Hiring Produces Information that is Equivalent to Cold-Calling 19. Dr. Murphy’s attempt to determine the effect of the agreements based on the level of inter-Defendant hiring is similarly unfounded. Dr. Murphy asserts that: If hiring by one Defendant of employees from another Defendant were economically important in the pricediscovery process, then employee movement between Defendants should account for a substantial part of the overall movement of workers.19 20. Dr. Murphy’s support for this assertion is in footnote 35: Hiring should be a reasonable proxy for the price discovery process given that information on compensation is most commonly provided to candidates only at the later stages of the recruiting process (once the number of candidates has been reduced to a small group that then is interviewed for a job or job opening). Both Adobe and Intuit clearly state that they do not discuss compensation until the later stages of the recruiting process.20 19 Murphy Report, ¶ 31. 20 See Declaration of Jeff Vijungco, November 9, 2012 at pp. 5-6 and Declaration of Chris Galy Page 7 Reply Expert Report of Edward E. Leamer, Ph.D. 407 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page11 of 66 CONFIDENTIAL 12/10/2012 21. This is Dr. Murphy’s key justification for using inter-Defendant hiring to evaluate the agreements. It has no foundation in economic theory or fact. 22. As Dr. Murphy acknowledged at his deposition a cold-call can transmit information about compensation to a candidate regardless of whether the recruiter makes a concrete salary offer.21 If the recruiter assesses the market value of the position, this conveys information; if the recruiter provides feedback about the candidate’s salary expectations, this conveys information; if the recruiter even calls the candidate back after he or she has stated salary expectations, this conveys information. Most recruiters are well aware of salary levels and ranges at competing firms since companies routinely survey compensation levels at their labor market competitors. Employees on the other hand aren’t equally aware of salary distributions or of the precise skill sets valued in other firms. That asymmetric information is partly remedied by the cold call alone. The very fact that a recruiter initiated contact and expressed interest in an employee provides a signal to the employee that he may be under-placed or that his skills may be under-valued at the current employer and that there are might be better opportunities elsewhere. C. Dr. Murphy Does Not Understand the Important Difference between Movement and Mobility 23. Dr. Murphy’s opinions indicate he has little or no understanding of the important difference between movement and mobility. As opposed to actual movement, i.e., an employee leaving one firm and joining another, mobility is a reflection of employees’ satisfaction or lack thereof with compensation at their current firms and recognition or understanding of the availability of other employment opportunities. Cold calling enhances mobility, without necessarily creating movement. Contrary to what seems the basis for Dr. Murphy’s opinions, movement is a very imperfect and unreliable symptom of mobility because while one possible result of increased mobility is more movement, another involves firms’ enhancing compensation to prevent movement. In other words, evidence of a lack of movement is entirely consistent with my findings that class-wide evidence is capable of showing that in the absence of Defendants’ agreements, Class member compensation would have November 9, 2012 (Galy Declaration) at pp. 3-4. 21 Murphy Deposition, pp. 135-136. Page 8 Reply Expert Report of Edward E. Leamer, Ph.D. 408 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page12 of 66 CONFIDENTIAL 12/10/2012 been broadly higher. Thus, Dr. Murphy’s first three opinions are speculations, lacking empirical support. 24. The important elements in the distinction between movement and mobility are: a. Movement refers to the departures and arrivals of workers at firms. Mobility is the credible threat of movement if a better offer were to materialize. b. Mobility between firms puts pressure on each firm to offer compensation packages that are attractive enough to retain employees. If workers were completely immobile, potential external competition for existing workers could not materialize as a force for higher compensation. If workers were perfectly and instantaneously mobile, then firms would be compelled to match outside opportunities on a day by day basis in order to retain employees. Normal, unimpeded mobility lies somewhere between these two extremes, greater for some kinds of workers and less for others. c. Mobility is impaired by lack of information. Recruiters target the socalled “passive” candidates with cold-calling because that passivity is likely to leave the workers under-informed about outside opportunities. By providing information to under-informed workers cold-calling increases mobility. d. Movement is evident in the payroll records but mobility is not directly observable. Movement is a possible correlate of mobility, but not reliably so because most swings in movement come from other sources. Not surprisingly the anti-cold-calling agreements were put in place in 2005 when the market for tech workers was heating up again after the 2001 tech bust.22 Whatever suppressive impact the agreements had on mobility was masked by the coincident unpredictable rise in movement. e. There can be mobility without movement. Indeed, in response to outside offers, firms routinely counteroffer to try to retain valuable employees. If the response is adequate, there is mobility without movement and a wage response without movement as well. f. There can be changes in movement without changes in mobility. 22 Luo, T. and A. Mann, “Crash and Reboot: Silicon Valley high-tech employment and wages, 2000-08,” Monthly Labor Review, January 2010, pp. 61-65 . Page 9 Reply Expert Report of Edward E. Leamer, Ph.D. 409 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page13 of 66 CONFIDENTIAL 12/10/2012 1. Involuntary separations create movement with or without mobility. Separations initiated by a firm either because of substandard performance of the individual or because of reductions-in-force are not likely to create upward pressure on wages of the workers who stay behind. These separations are obviously not symptoms of mobility of the affected workers. 2. There are also a variety of worker-chosen separations that have nothing to do with getting a better job. Health problems and retirement are obvious instances. Family matters like a spouse getting an attractive job offer in a different city or the desire to be closer to aging parents can also create separations. 25. The agreements had their effect by reducing the information flow about outside opportunities, and thus reducing the mobility of workers as well as their perceptions of the equitable wage within their firm. Dr. Murphy has provided no reliable support for his apparent opinion that the agreements did not substantially reduce the information flow to passive experienced workers who were satisfied with their jobs and not actively engaged in a search for alternatives. D. Dr. Murphy Understates the Information Provided by Cold Calling 26. Dr. Murphy’s factual assertion—that recruiters do not discuss compensation with candidates until late in the recruitment process23—also has no empirical support. He relies on two declarations and conversations with Defendant employees for which there are no notes.24 But even these information sources are contradictory: the Galy Declaration he relies on states that recruiters do discuss compensation with recruits.25 Even Dr. Murphy admitted at his deposition that this happens.26 27. This is the problem with relying on sources such as these and “casual empiricism” to draw empirical conclusions. An economist qualified and trained in survey-based research could have designed and administered a survey of recruiters at the 23 Murphy Report, fn. 35. 24 Id. 25 Galy Declaration, ¶ 15. 26 Murphy Deposition, p. 136. Page 10 Reply Expert Report of Edward E. Leamer, Ph.D. 410 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page14 of 66 CONFIDENTIAL 12/10/2012 Defendants, like the survey administered in one of Dr. Murphy’s sources.27 Such work might have been informative, if properly executed. However, there is little or no useful economic evidence on which to base empirical conclusions in unstructured conversations with interested persons. Some economists use interviews with industry participants to frame exercises in symbolic theory; they expressly disclaim using them as a basis for empirical conclusions and they admit their “methodology…moves beyond the boundary of economics itself into the realm of anthropology and the territory of hermeneutics[.]”28 E. Dr. Murphy’s Analysis of Defendants’ Hiring Is Irrelevant and His Conclusion from It of No Effect on Compensation Is Unsupported 28. Dr. Murphy also argues that “my claim that average compensation at these firms was suppressed is implausible because of the high level of hiring by Defendants during the class period.”29 The only support offered by Dr. Murphy for this opinion is the rate of movement of workers to the Defendants: “Collectively, between 2005 and 2009, Defendants hired an average of over 8,000 new workers per year – equal to 11 percent of their combined workforces.”30 29. This single fact is irrelevant to his sweeping conclusion. There is no inconsistency between the levels of hiring by Defendants during the class period and my conclusion that there is reliable class-wide evidence capable of showing that Defendants’ under-compensated employees as a result of the agreements. 27 Honoree, A. I. and D. E. Terpstra. “The Relative Importance of External, Internal, Individual and Procedural Equity to Pay Satisfaction,” Compensation & Benefits Review, November/December 2003. Dr. Murphy was apparently unacquainted with any written standards for survey design or mixed methods (qualitative and quantitative) research prior to undertaking it. See, e.g., Creswell, J. W., and V. L. Plano Clark, Designing and Conducting Mixed Methods Research, SAGE Publication: 2007, Chapter 6.; Creswell, J. W., Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, SAGE: 2009, Chapter 9. 28 Piore, M. J., “Qualitative Research: Does It Fit In Economics?,” European Management Review, (2006) 3, 17-23. 29 Murphy Report, p. 6. 30 Id. Page 11 Reply Expert Report of Edward E. Leamer, Ph.D. 411 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page15 of 66 CONFIDENTIAL 30. 12/10/2012 Dr. Murphy appears to miss or misunderstand the following key facts about hiring and cold-calling: a. Much of the Defendants’ hiring volume was at entry levels. The information conveyed by the hiring of an entry level employee at the entry level rate in the firm’s compensation structure is not comparable to the information conveyed in a cold call of an experienced worker by a competitor. b. When firms hire a new employee they have control over the internal disruption that a new employee with exceptional compensation might cause. This disruption can be minimized by slotting a new employee into an appropriate title-compensation combination in the firm’s hierarchy, and by offering one-time signing bonuses, thus leaving the new employees appropriately located in the hierarchy going forward. Defendants’ new employees could be slotted into a “comfortable” place in the internal hierarchy with compensation comparable to other employees. c. Although firms can exercise control over the contracts offered to new employees, they do not have control over cold-calls and departures to better positions, unless they enter into illegal agreements. Thus, as far as movement is concerned, the focus should be more on the impact of departures to better positions rather than hiring. As described above and in my original report, Defendants clearly found departures highly disruptive.31 d. I accommodated the potential significance of differences in the rate of hiring by embodying it in my conduct regression.32 1. My conduct regression explicitly allows for the possibility that high levels of firm hiring affect the amount of undercompensation caused by the agreements. 2. My conduct regression explicitly allows for the possibility that the effect on compensation levels is different for young employees and for employees with short tenure at their firms, and so the effect of the agreements on employees at a firm might vary according to the 31 Leamer Report, pp. 34 and 45. 32 Leamer Report, Figure 20. Page 12 Reply Expert Report of Edward E. Leamer, Ph.D. 412 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page16 of 66 CONFIDENTIAL 12/10/2012 firm’s composition in this regard. These are workers who, as a group, might be less likely to be cold-called. 31. The bottom line is that Dr. Murphy’s characterization of the significance of Defendants’ hiring is misleading and mistaken. F. Dr. Murphy Has Not Disputed that the Agreements Reduced Cold-Calling and Competition Among the Defendants for Employees 32. 33. 33 As described above, documents show Defendant executives’ frustration with coldcalling when it occurred, whether or not it resulted in a poached employee. They wanted to stop it, and actively undertook procedures at the highest levels to do so. Dr. Murphy has not disputed this. Dr. Murphy has not addressed the effectiveness of the agreements in actually deterring cold calling. As I described in my Report,33 documents indicate that CEOs of the Defendant firms placed a priority on ensuring compliance.34 Thus it is undisputed that but for the agreements some workers would have otherwise learned that a competitor would have been willing to pay higher salaries than the worker was currently receiving. Some of these workers would likely have accepted the higher wage, or used this information to negotiate a higher salary from their employer, and told colleagues about the alternative employment opportunities. Leamer Report, ¶ 39 34 See, e.g., GOOG-HIGH TECH-00009454-9454 at 9454 (Email from Apple showing concern about poaching from Google and assurance from Eric Schmidt that the employee responsible would be terminated from Google), 231APPLE002140 (Bill Campbell assures Steve Jobs that Dave from Apple would not accept Google’s offer as they stopped the hiring process for two other people from Dave’s team), and 231APPLE002145 (Bruce Chizen forwards an Adobe email to Steve Jobs showing that Jerry from Adobe has been asked to back off from soliciting the one person he was after from Apple). Page 13 Reply Expert Report of Edward E. Leamer, Ph.D. 413 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page17 of 66 CONFIDENTIAL 12/10/2012 G. Dr. Murphy Incorrectly Argues that Interference in the Information Flow Would Not Affect Compensation At All 34. In addition to asserting incorrectly that the agreements could not affect the information flow about outside opportunities, Dr. Murphy argues the impact on compensation would have been nil, or even positive because:35 a. The agreements were not broad enough to affect the “market price.” b. “As a matter of economic theory, the alleged conspiracy to restrict a small number of employers from using a single recruiting tool when approaching employees at one or a few other firms would not lower compensation on a class-wide basis.”36 c. “As a matter of economics, reduced cold calling (to the extent it has an effect) could raise, rather than reduce, average compensation. If less cold calling reduced the number of potential candidates contacted by Defendants, it would reduce the pool of potential hires for those Defendants.”37 35. These comments are a highly selective and misleading characterization of the state of economy theory. 36. The reference to market prices in item (a) is startling and suggests that Dr. Murphy ignored what I said in my report. My findings about the effect of the agreements on compensation relate to the price-discovery process that was impeded by the anticold-calling agreements. I do not rely on the notion that the equilibrium market price is affected by the agreements. What I argue instead is that the whole sequence of contracts in search of that market price is affected. This is why market definition and market price are not relevant inquiries here: the process of getting to a market price across markets, across firms, and for all employees was disrupted by the agreements. Dr. Murphy’s commentary about market prices and equilibrium is thus irrelevant. 35 Murphy Report, pp. 9-10. 36 Murphy Report, p. 9. 37 Murphy Report, p. 10. Page 14 Reply Expert Report of Edward E. Leamer, Ph.D. 414 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page18 of 66 CONFIDENTIAL 37. 12/10/2012 The reference to economic theory in item (b) is also startling. While there may be some assumptions that are able to produce the result Dr. Murphy claims, other assumptions—widely accepted in the economic literature—imply the opposite. In particular, Dr. Murphy’s assertion regarding the supposedly limited nature of the recruiting restriction at issue in the agreements is at odds with widely accepted economic research into the workings of markets with less-than-perfect (imperfect) information. Contradicting Dr. Murphy, here is what Nobel Prize Winner Joseph Stiglitz wrote in an article cited in my previous report (emphasis added): “For more than 100 years, formal modeling in economics had focused on models in which information was assumed to be perfect. Of course, everyone recognized that information was in fact imperfect, but the hope, following Marshall's dictum ‘Natura non facit saltum,’ was that economies in which information was not too imperfect would look very much like economies in which information was perfect. One of the main results of our research was to show that this was not true; that even a small amount of information imperfection could have a profound effect on the nature of the equilibrium.”38 38. It is not just the work of Dr. Stiglitz that Dr. Murphy has failed to appreciate. Two other recent Nobel Prize winners have also done work on the consequences of imperfect information. Vernon L. Smith won the 2002 Nobel Prize “for having established laboratory experiments as a tool in empirical economic analysis, especially in the study of alternative market mechanisms.”39 These laboratory experiments study the price discovery process, with various informational limitations and transactions costs. Since I filed my report, Alvin Roth was awarded the 2012 Nobel Prize for “for the theory of stable allocations and the practice of 38 Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American Economic Review, Vol. 92, No. 3 (June 2002), p. 461. 39 "The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002," Nobelprize.org., December 10, 2012, http://www.nobelprize.org/nobel_prizes/economics/laureates/2002/ Page 15 Reply Expert Report of Edward E. Leamer, Ph.D. 415 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page19 of 66 CONFIDENTIAL 12/10/2012 market design.”40 Here the words “market design” refer to a broad concept and would include restrictions on cold-calling. 39. Dr. Murphy’s item (c) is another reference to some unstated economic model that, according to Dr. Murphy, apparently says that if less-preferred cold-calling is substituted for the most-preferred cold calling, then workers are made better off. But it is not enough to claim that there is a theory that allows workers to be better off. What we need is some wisdom that offers advice on whether this is likely to be the case in the present context. I consider it highly unlikely that the Defendant firms would engage in these secret, illegal and egregious agreements if the agreements increased compensation for their workers. 40. Dr. Murphy’s logic violates a basic principle of modern economics, which he did not really dispute at his deposition: “The most fundamental reason that markets with imperfect information differ from those in which information is complete is that, with imperfect information, market actions or choices convey information.”41 “… The fact that actions convey information leads people to alter their behavior, and changes how markets function. This is why information imperfections have such profound effects.”42 III. Contrary to Dr. Murphy’s Opinion Under-Compensation Would Have Impacted All or Almost All Class Members 41. Dr. Murphy describes my opinion as follows: 40 "The Prize in Economic Sciences 2012," Nobelprize.org., December 10 2012, http://www.nobelprize.org/nobel_prizes/economics/laureates/2012/ 41 Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American Economic Review, Vol. 92, No. 3 (June 2002), p. 468. 42 Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American Economic Review, Vol. 92, No. 3 (June 2002), p. 473. Page 16 Reply Expert Report of Edward E. Leamer, Ph.D. 416 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page20 of 66 CONFIDENTIAL 12/10/2012 “Dr. Leamer’s analysis has three essential steps. First, the challenged agreements must materially reduce the information available to Defendants’ employees. Second, that reduction in information must cause the salaries of individual employees to be reduced. Third, the “somewhat rigid” compensation structures of the Defendants must cause the reductions in the compensation of some employees to reduce compensation on a class-wide basis.”43 42. Dr. Murphy claims that “[n]one of the required links in the chain hold, let alone all three.”44 However he has left major elements of these three steps unanswered, has made substantial errors in his characterization of the economics of the case, has ignored or mischaracterized evidence, and as a result has failed to support his claim that there would be no substantial or class-wide impact from the Defendants’ agreements. 43. The previous section has addressed the very substantial economic theory and documentary evidence that supports (1) the finding that the agreements limited information about outside opportunities and (2) suppressed compensation of affected workers. With regard to the third step in Dr. Murphy’s characterization of my opinion–that these firms have a somewhat rigid salary structure that spreads the harm to all or almost all employees –Dr. Murphy sometimes disagrees but it is a great surprise to discover that when he feels his argument is strengthened by the opposite opinion, he changes his mind. 44. As Murphy puts it: “He [Leamer] failed to take into account when performing his statistical test that, aside from the challenged agreements, employees at a firm are affected by common factors that influence their compensation – e.g., a highly successful movie at Pixar can result in large and unusual bonuses for all Pixar employees, or a short-term reduction in the demand for PCs and the 43 Murphy Report, p. 5 44 Murphy Report, p. 6. Page 17 Reply Expert Report of Edward E. Leamer, Ph.D. 417 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page21 of 66 CONFIDENTIAL 12/10/2012 microprocessors that power them can cause a decline in Intel’s revenue and profitability and lead Intel to impose a wage freeze such as occurred in 2009.”45 45. I quite agree with the second Dr. Murphy on this. A. There is Ample Evidence in the Defendants’ Documents and Depositions that Internal Equity Played a Key Role in Wage Setting. 46. The proposition that these firms allowed salaries to be influenced by internal equity considerations is clear from Defendant HR documents and from depositions of their HR personnel. For example, managers at Apple take internal equity into careful consideration on top of performance when making a merit decision to determine an existing employee's merit increase.46 Similar approaches are used by other Defendants, where internal equity is assessed and equity report is run prior to making offers, merit increases and promotions.47 Internal equity played an important role during the negotiation processes for all Defendants, e.g., Apple had to extend an offer that was lower than what a candidate was getting at his previous job due to internal equity,48 and while a hiring manager at Adobe stated that while he does not subscribe to the ‘internal equity’ issue which assumes “all people are created equal,” he understands the sensitivity, and hence suggested spot-on bonuses for a candidate if an increase in base salary offer would skew internal equity.49 47. One expression of internal equity and fairness in Defendants’ compensation practices is their adoption and adherence to compensation structures. These structures played a substantial role in decisions regarding hiring, promotions, salary raises,50 and even demotions or lateral movements.51 Numerous Defendant 45 Murphy Report, ¶ 124 (emphasis added). 46 See 231APPLE094041-67 at 50. 47 See e.g., 76512DOC000926, ADOBE_009327, ADOBE_016608, GOOG-HIGH TECH00036370, GOOG-HIGH-TECH-00233026, LUCAS00004721 and PIX00023020. 48 See 231APPLE056385. 49 See ADOBE_002764. 50 See e.g., 76582DOC000902 (Intel follows a pay line guideline when making changes to employees’ salaries). Page 18 Reply Expert Report of Edward E. Leamer, Ph.D. 418 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page22 of 66 419 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page23 of 66 CONFIDENTIAL 12/10/2012 supported the observations of reference-dependant fairness and also shown that fairness concerns are economically significant […]. Employers who violate rules of fairness are punished by reduced productivity, and merchants who follow unfair pricing policies can expect to lose sales.” a. Levine (1993)59 surveyed 139 compensation executive at large US corporations to discern their attitudes towards fairness in wage structure. He found that the executives show strong preference to maintain constant relative wages and keep a stable wage structure within career paths and within broad occupational groups. In interviews these executives indicated reasons for maintaining relative pay, including: 1. “There is a morale cost.... People complain.” 2. If you pay new workers more than senior ones, “You will have an employee revolt on your hands,” 3. And employees start to “type up a resume, gossip.” Even the companies that claimed to be market-driven agreed that changing ‘relative’ wages in response to market forces reduced morale and increased turnover. b. Isaac (2001)60 reviews literature and theory and finds support for the idea that pay-for-performance schemes are not effective if they do not maintain fairness (emphasis added): “Labour is not a commodity. Efficiency has a different time dimension and a different conceptual framework when dealing with the labour factor as compared to capital equipment or raw materials. Labour is subject to complex social and psychological forces. People are less receptive to direction than is a piece of equipment. They react to their environment. The pace and quality of work is critically dependent on their minds and hands. In 59 Levine, D. I., “Fairness, markets, and ability to pay: Evidence from compensation executives,” The American Economic Review, Vol. 83, No. 5 (December 1993), pp. 1241-1259. 60 Isaac, J. E. , “Performance related pay: The importance of fairness,” Journal of Industrial Relations, Vol. 43, No. 2 (June 2001), pp. 111-123. Page 20 Reply Expert Report of Edward E. Leamer, Ph.D. 420 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page24 of 66 CONFIDENTIAL 12/10/2012 their working environment, they are not individuals but form part of a group, open to group pressures and values. The place of work is not merely part of an economic process but also a social institution. And so is the labour market. In such a context, people develop norms about what is right and wrong and fair. Work is not merely a way to earn income. It has meaning in itself. The size of payment for work reflects on the worth, status and selfesteem of the person concerned. People measure their worth not in absolute terms but relative to one another. But while the financial incentive is important, people are also motivated by non-financial considerations. This is not to deny the importance of the forces of supply and demand, but merely to point out that they work differently for the labour market compared to the commodity market; that the payment of a higher wage may not necessarily induce a better performance; and that the determination of wages in a workplace or an industry is not an impersonal process but an administrative act in which norms of fairness must be given substantial weight in the interest of productive efficiency. These norms are not necessarily immutable but the strength of convention into which notions of fairness are locked in, asserts itself when changes occur.” c. Similarly, according to Fehr et al. (2009)61 “[I]mportant labor market phenomena can be better understood if one takes (a) the inherent incompleteness and relational nature of most employment contracts and (b) the existence of reference-dependent fairness concerns among a substantial share of the population into account. Theory shows and experiments confirm that, even if fairness concerns were to exert only weak effects in one-shot interactions, repeated interactions greatly magnify the relevance of such concerns on economic outcomes.” (emphasis added) d. In a leading textbook on this topic, Milkovich, Newman and Gerhart62 explain that many different factors influence a company’s pay structure. These include, 61 Fehr, E., L. Goette and C. Zehnder, “A Behavioral Account of the Labor Market: The Role of Fairness Concerns," Annual Review of Economics, (2009), pp. 355-384. 62 Gerhart, M., G. Milkovich and J. Newman, Compensation, New York: McGraw-Hill Irwin, Page 21 Reply Expert Report of Edward E. Leamer, Ph.D. 421 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page25 of 66 CONFIDENTIAL 12/10/2012 but are not limited to, economic pressures, government policies and regulations, stockholders’ attitudes and cultures and customs. “An important factor influencing the internal pay structure is its acceptability to the employees involved”. Employees judge the fairness of their organization's internal pay structure by making several comparisons:  Comparing to jobs similar to their own (internal alignment),  Comparing their job to others at the same employer (internal alignment), and  Comparing their jobs' pay against external pay levels (external competitiveness). e. A seminal article by Hamermesh (1975)63 develops a theoretical model that demonstrates the implications of changing relative wages when there is interdependence in utility (relative wage enters the utility function). “Increases in one wage in a plant may affect the effort both of those workers receiving the increase and of other workers who are aware of it.” The latter group reduces effort. “The role of information is thus crucial to the analysis of interdependence.” (emphasis added) f. Di Maria & Metzler (2009)64 analyze wage structure amongst workers at Luxemburg banks in 2002 “The main results indicate that some wage dispersion is needed to increase efficiency among workers who have similar characteristics and a strong unequal wage structure between workers having different job positions will adversely affect efficiency in the bank.” 2011, Chapter 3. 63 Hamermesh, D.S., “Interdependence in the labour market,” Economica, (1975), pp. 420-429. 64 Di Maria, C. H., and S. Metzler, "Internal Wage Structure and Bank Performance in Productivity in the Financial Services Sector," The European Money and Finance Forum Vienna (2009), Chapter 9. Page 22 Reply Expert Report of Edward E. Leamer, Ph.D. 422 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page26 of 66 CONFIDENTIAL 12/10/2012 “..[A]mong workers sharing similar characteristics some wage disparity will also increase efficiency, but too much inequality will adversely affect efficiency and may even lower efficiency.” (emphasis added) g. Machin and Manning (2004)65 put competitive labor market theory to a test by studying the market for care assistants in residential homes for the elderly on England’s “sunshine coast.” The authors find that the wage structure deviates in from what a theory of competitive labor market would predict. They find that wage dispersion is small within firms, but large between firms; and that the wage dispersion that is present does not seem to be explained by workers’ productivity related characteristics. C. Class-Wide Evidence That Includes Google’s “Big Bang” Response to Facebook Demonstrates How Competitive Pressure From One Peer Firm Can Move An Entire Pay Structure Overnight 50. I described above how class-wide evidence is capable of showing that competitive pressure—when it was not impeded by the agreements—did result in substantial firm-wide compensation adjustments (including entry level and new employees66) in order to both retain high-quality workers and ensure all workers felt equitably compensated. 51. The most particular example of how this could affect class-wide compensation is Google’s Big Bang, which illustrates all three of these impacts in action. In 2010, Google announced it would raise compensation to all employees by 10 percent and made other systematic compensation changes to retain employees in the face of poaching by Facebook. Defendants’ top executives recognized that competitors’ poaching could create important disruptions to the firms’ compensation structures. As a result every Google employee (including new and entry level employees) 65 Machin, S. and A. Manning, "A test of competitive labor market theory: the wage structure among elder care assistants in the South of England," ILRReview, Vol. 57, No. 3 (April 2004), pp. 371- 385. 66 Defendants mischaracterize my testimony regarding the agreements’ impact on entry level and new employees. Defendants’ Motion to Strike, November 12, 2012, pp. 4-5. As I described in my Report and deposition, firm-wide compensation structures imply that there would have been impact on all employees including entry level and new employees. Leamer Report, ¶ 120-134; Leamer Deposition, pp. 159:3-163:18. Page 23 Reply Expert Report of Edward E. Leamer, Ph.D. 423 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page27 of 66 424 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page28 of 66 425 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page29 of 66 426 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page30 of 66 CONFIDENTIAL 12/10/2012 D. Dr. Murphy is Incorrect that the Defendants’ Data Do Not Indicate that Fairness and Internal Equity Matter 57. Dr. Murphy’s fourth opinion is that “Defendants’ compensation structures are not rigid,” but he supports this opinion by attacking only the conclusions I made from my analysis of Defendants’ data, leaving intact the important economic theory and decisive HR documents. Here is what Dr. Murphy has argued:75 (a) Defendants had (and exercised) substantial flexibility in setting compensation of individual employees. Dr. Leamer’s own model implies that employee compensation was highly individualized, with large variations even within particular job categories and between observationally similar individuals (see Part IV.D, below). As I demonstrate below, in every year and for each Defendant, there is substantial dispersion in employee compensation unexplained by Dr. Leamer’s model. Dr. Leamer has shown that different jobs have different average compensation, but not that increases in an individual’s compensation resulting from a cold call results in higher compensation for other employees. (b) Dr. Leamer’s premise is also flawed. A rigid wage structure, even if one existed, would not imply that a change in compensation for one or more employees would shift the entire structure, because the cost of increasing compensation for one employee would be enormous (an increase for all employees), and would be resisted. Thus, Dr. Leamer’s theory makes no economic sense. (c) Finally, Dr. Leamer’s analysis cannot distinguish the impact he hypothesizes from an alternative hypothesis that compensation of Defendants’ employees is broadly determined by competition in a vast labor market, and that adjustments for individual employee’s unique circumstances (such as an attractive outside offer) are highly individualized (see Part V.D.3, below). 75 Murphy Report, pp. 10-11. Page 27 Reply Expert Report of Edward E. Leamer, Ph.D. 427 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page31 of 66 CONFIDENTIAL 12/10/2012 58. The issue here is not some technical characterization of what is rigid and what is not. The issue is whether internal equity concerns spread the anti-cold-calling effects on compensation broadly across all or most members of the classes. I wrote, “A firm’s commitment to principles of ‘internal equity’ is evidenced by the imposition and maintenance of a somewhat rigid salary structure.”76 Dr. Murphy attacks the regression equations that I used to describe the internal salary structure but ignores the real question: do these firms spread the compensation suppressing effects of the agreements broadly because of internal equity considerations? 59. The information revealed from my analysis of Defendants’ employment records adds to this body of evidence. However, my opinions regarding common impact do not rest wholly or even mostly upon that analysis. 60. I do not (and did not) suggest that the “Hedonic” regressions I reported were conclusive proof that internal equity influenced compensation. They serve a different purpose. Defendant documents reveal a top-down salary-setting mechanism with overall increases in compensation determined by the top management leaving limited salary setting discretion at lower levels of management.77 Market driven compensation setting would be bottom-up with each employee receiving compensation commensurate with their outside opportunities. A bottom-up market-driven approach ignores internal equity completely. A topdown approach allows internal equity to play a role in the determination of compensation. The hedonic regressions are a numerical representation of the topdown compensation setting which allows but does not necessitate internal equity to play a role in salary setting. 61. In various instances (Dr. Murphy’s Report, Declarations, questions during my deposition), the Defendants have focused on the variability in the compensation received by Class Members.78 This discussion misses the mark. Even in firms with a “somewhat” rigid salary structure, it is to be expected that there will be salary variations for people sharing a title. This is not a symptom of firms setting 76 Leamer Report, p.49. 77 Leamer Report, ¶ 121. 78 Defendants Opposition to Class Certification, November 12, 2012, pp. 7-8. Page 28 Reply Expert Report of Edward E. Leamer, Ph.D. 428 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page32 of 66 CONFIDENTIAL 12/10/2012 compensation randomly but almost certainly reflects differences in the people and jobs that are part of the compensation structure. In any regression analysis that seeks to explain employee compensation, if sufficient data are available regarding these employee and job characteristics, much of the dispersion would be explained, and the unexplained dispersion (the residuals) would be small. However if sufficiently detailed data are not available (such as is the case here) these residuals will not necessarily be small. 62. Defendants’ anecdotal examples purport to show that similar Class Members have very disparate and unexplainable differences in compensation. However, even here the effects of Defendants’ compensation structures are apparent. For example, Defendants say 79 But Defendants fail to note that 63. For example, . 64. Defendants also attach an example of Apple’s “ .”80 Again, common objective factors, such as title, confirm a lack of variation among similar employees. Thus, 65. Figure 2 shows that for every firm in every year the prediction error of the common factors regression is typically small (about 10 percent of total compensation and often less). Figure 3 shows that there is strong overall relationship between Class Members' actual total compensation and the total compensation predicted by the 79 Declaration of Danny McKell, November 12, 2012 at ¶ 10. 80 Declaration of Steven Burmeister, November 12, 2012, Ex. B. Page 29 Reply Expert Report of Edward E. Leamer, Ph.D. 429 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page33 of 66 CONFIDENTIAL 12/10/2012 common factors regression, with these two figures generally having very high positive correlations. Figure 2: Common Factors Explain Most of Class Members’ Compensation Variation Page 30 Reply Expert Report of Edward E. Leamer, Ph.D. 430 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page34 of 66 CONFIDENTIAL 12/10/2012 Figure 3: Hedonic Model’s Predictions Generally Are Highly Correlated with Actual Compensation 66. Though these firms may have provided certain managers limited and closely supervised discretion over setting compensation levels, that discretion can be exercised (and if not, corrected) in favor of internal equity (and given the documents and other evidence here, very likely was). Discretion is not synonymous with market-driven. E. Dr. Murphy is Incorrect that My Hedonic Analysis of Named Plaintiffs’ Compensation Performed Poorly 67. Although Dr. Murphy attempts to use the Named Plaintiffs to show that my hedonic model of compensation performs poorly, actually the opposite is the case. Figure 4 below shows a scatter of predicted versus actual total compensation of the Named Plaintiffs computed by Dr. Murphy. The hedonic model performs well in predicting Page 31 Reply Expert Report of Edward E. Leamer, Ph.D. 431 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page35 of 66 CONFIDENTIAL 12/10/2012 the actual compensation of these individuals, especially considering the fact that as mentioned above—the model was only a partial representation of their salary within each firm’s structure. The overall correlation between the Named Plaintiffs’ actual total compensation and total compensation predicted by the hedonic model is 0.75. To the extent these individuals might indicate room for improvement in that model, it is with respect to the effect of changes in employment. The larger differences in predicted versus actual are for observations where an employee started a job or had a promotion (particularly Mr. Stover in 2008). Excluding those observations the correlation is 0.94. This model could potentially be improved— particularly if there were additional information for all the employees in the data such as their education, skills, and performance. Those data would assist in filling out the picture on the Defendants’ compensation structure. 68. In addition, Dr. Murphy’s assessment that the hedonic regressions show “overcompensation” for these individuals81 is a gross misapplication of these equations, which were not designed to determine who was under-compensated and who was over-compensated, or by how much. These regressions serve only to demonstrate the salary structures that each Defendant used to determine compensation. However, the CONDUCT regressions in my Report were designed to determine the amount of over- or under-compensation by each Defendant consequent to the agreements.82 Those CONDUCT regressions show only undercompensation during the conspiracy period. 81 Murphy Report, ¶ 93. 82 Leamer Report, Figure 20-24. Page 32 Reply Expert Report of Edward E. Leamer, Ph.D. 432 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page36 of 66 433 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page37 of 66 CONFIDENTIAL 12/10/2012 class.” First, my reactions to Dr. Murphy’s comments need to be put into the proper context. 71. This allegedly illegal conduct did not target any single individual. This was an attack on the information network that keeps employees informed of opportunities elsewhere. Thus, in this case, damages are not determined at the individual level. Damages are a consequence of being a part of the information network under attack. Additional damages flow from the forces of internal equity that spread the harm across all or most members of these firms. These additional damages are completely a consequence of being a member of this group. 72. I have thus used a regression model to demonstrate “a reliable Class-wide or formulaic method capable of quantifying the amount of suppressed compensation suffered by each class.” This regression model is a widely accepted way of determining whether and by how much an act or a set of acts affected price or compensation. It does so by contrasting statistically the periods in which illegal behavior was occurring with the periods in which it was absent. The model quantifies the harm to the class and in doing so tells us something about the existence of that harm and its widespread nature. 73. Tellingly, rather than casting aside this approach in favor of something else, Dr. Murphy has conducted variations of my proposed model with the same approach in mind. For example, by estimating the “conduct regression” using only the pre- or post-agreement periods Dr. Murphy has attempted to evaluate the effect on class member compensation by contrasting compensation of individuals during the agreement period with compensation during periods absent of the agreements.84 Another example is Dr. Murphy’s “conduct regression” that uses the non-conduct period in attempt to model the compensation absent the agreements, and then estimates the but-for salaries during the period of agreements.85 With this model, Dr. Murphy again has made an attempt to assess class-wide impact of the agreements. 84 Murphy Report, Appendix 12A-12D. 85 Murphy Report, Appendix 13A-13B. Page 34 Reply Expert Report of Edward E. Leamer, Ph.D. 434 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page38 of 66 CONFIDENTIAL 12/10/2012 74. Although he takes the same approach that I have used, and apparently accepts it as a valid way to proceed, Dr. Murphy has made critical errors in implementation of the approach which led to him to a wrongful conclusion that the model shows no undercompensation to the classes. I describe this in detail below. 75. A critical step in using the regression tool is to decide what control variables need to be included in the equation. In my report, I have tried to suggest the seriousness with which I approached this task partly by listing the categories of variables that need to be included and by making sure that my regression includes variables from each category: Conduct Effects, Persistence, Worker Effects, Industry Effects, and Employer Effects. I have included variables that reflect each and every one of these categories. My opinion is that the list of categories is complete and reliable as it currently stands, though the choice of variables within each category is open to further refinement (as it almost always is with non-experimental data). A. Calculation of Standard Errors Assumes Statistical Independence 76. Dr. Murphy has raised an issue of dependence among the observations and has suggested the treatment of the problem is to correct upward the standard errors of the coefficients. While Dr. Murphy has here identified an issue, he does not propose an appropriate solution. One response would be to include a variable or variables in the equation that account(s) for the correlation, leaving the residuals adequately independent. The many variables that I have included to some extent already accomplish this task. 77. Incidentally, and importantly, there is nothing in my report that refers directly or indirectly to the standard errors that Dr. Murphy is complaining about. This is because I did not rely on them and my conclusions do not depend on them. 78. The regression I estimated makes use of data on nearly 98,888 individuals and assumes that the variables in the regression account for all of the similarities among the individuals, and what is left over is uncorrelated “noise.” If what is left over is correlated among individuals in a known way, then one treatment is to adjust both the regression coefficients and the standard errors. I have written the words “one treatment” so as not to lose track that the better treatment is to find a variable or variables that are causing the correlated error structure. Page 35 Reply Expert Report of Edward E. Leamer, Ph.D. 435 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page39 of 66 CONFIDENTIAL 12/10/2012 79. If the correlations among individual observations are mostly positive as Dr. Murphy suggests, then the standard errors would be adjusted upward, though it is impossible to tell what would happen to the estimated coefficients, and the statistical significance of selected variables can go up or down. 80. Unfortunately, it is impossible for anyone to know what is the covariance matrix that is needed to revise the estimates of my model. In addition, we cannot use these data to estimate the covariance matrix. The huge covariance matrix that describes the covariance of all pairs of individuals has 98,888x98,887/2 = 4,889,368,828 elements to be estimated from only ten annual observations at most on each individual. That’s impossible. Instead, the right variables must be chosen to describe how the covariances change across individuals. 1. Dr. Murphy Relies on a “Somewhat” Rigid Wage Structure in his Adjustment of the Standard Errors. 81. 82. 86 If this issue is transformed from theory into practice there has to be some structure imposed on the huge number of new parameters introduced by the vague idea of correlation among the residuals. We need a careful analysis to decide on that structure. To do this, Dr. Murphy relies on his observation that there are somewhat rigid salary structures at Defendant firms. This is a rather important concession, contradicting his claims elsewhere that salary structures are not rigid. Here, Dr. Murphy criticizes me for failing to recognize how common elements determine compensation of all individuals at all Defendant firms. As Murphy puts it: “He [Leamer] failed to take into account when performing his statistical test that, aside from the challenged agreements, employees at a firm are affected by common factors that influence their compensation – e.g., a highly successful movie at Pixar can result in large and unusual bonuses for all Pixar employees, or a short-term reduction in the demand for PCs and the microprocessors that power them can cause a decline in Intel’s revenue and profitability and lead Intel to impose a wage freeze such as occurred in 2009.”86 In addition to this rejection of his own opinion, this explanation by Dr. Murphy ignores the fact that revenues of both Intel and Pixar are included in my model, and to the extent that movements in revenue account for common within-firm Murphy Report, ¶ 124 (emphasis added). Page 36 Reply Expert Report of Edward E. Leamer, Ph.D. 436 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page40 of 66 CONFIDENTIAL 12/10/2012 movements, then that is fully taken into account in my regression, and does not need treatment of the type that Dr. Murphy is recommending. As an aside, Dr. Murphy’s emphasis of these facts shows that he well understands the importance of internal equity to the pay structures of the Defendants; the events he describes cannot be reconciled with the “classical” model of economics he elsewhere advocates where workers contract and re-contract at the whim of supply and demand. 2. The Best Solution is to Include Variables that Eliminate the Correlation Problem 83. This connects to the most important point. If we can measure items like revenues that create important commonalities across individuals, we should generally include those variables in the equation and suitably adjust the coefficients on all the variables as well as the standard errors. In the process we would remove the observable commonalities from the residuals, perhaps making the unexplained part of the model sufficiently uncorrelated across individuals that the independence assumption of the regression technique is adequately satisfied. In other words, it would be a mistake merely to adjust the standard errors—as Dr. Murphy suggests— if the estimated coefficients would be substantially affected by the same issue. Thus I included revenue variables in my model. 3. Dr. Murphy’s Employer-Year Fixed Effects Proves too much as it would Invalidate Any Before-During-and-After Model 84. Dr. Murphy has hypothesized that revenue increases at Intel and Pixar may cause correlated increases in compensation at these two firms. But since my model already includes revenues, Dr. Murphy’s follow-on to his criticism about the standard errors in my model does not refer to revenues even though that was the only reason cited for going down this path. Instead he opts for “employer-year” effects, which are the basis for his adjusted standard errors. There are two basic problems with these employer-year effects. First, these variables collectively stand for some unnamed variable like firm revenue that explains why the residuals are correlated. That variable should be named and utilized. Second, these variables together seriously overload the model and make it impossible to estimate the CONDUCT effect if all these variables were added to the model. Dr. Murphy has not included the employer/year effects in the regression, but conceptually he has Page 37 Reply Expert Report of Edward E. Leamer, Ph.D. 437 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page41 of 66 CONFIDENTIAL 12/10/2012 edged significantly in that direction when he adjusts the standard errors for clustering based on years. The much better route is to find why the model does not track the employer-year averages well enough to render this issue moot. This just requires another well-chosen explanatory variable. B. Dr. Murphy’s “Sensitivity Analysis” is Flawed 85. Dr. Murphy purports to have performed a “sensitivity analysis” of the conduct regression but in reality he has done no such thing. His “analyses” consist of (a) clustering the standard errors, (b) adding the S&P 500 as a variable, and (c) “disaggregating” the model. 86. The large and statistically significant firm-year effects in the regression serve as Murphy’s basis both for his clustered standard errors and for including the S&P Stock Price in the equation. “The test resoundingly rejects the hypothesis that there are no such omitted firm-specific factors, and establishes the need to use ‘clustered’ standard errors (or correct for that correlation in other ways).”87 “A consequence of omitting important determinants of firm-level compensation is that Dr. Leamer’s estimated conduct effects will capture the impact of variables (other than the challenged agreements) that differ systematically between the conduct and non-conduct periods. To illustrate the potential problem, I considered what would happen if I simply add a variable measuring the performance of the stock market from his regression, which potentially would measure general economic and financial performance in the economy that Dr. Leamer acknowledges likely affect compensation (see his Figure 8 and related discussion).183 Exhibit 26 shows the results from adding the change in the 87 Murphy Report, ¶ 137. Page 38 Reply Expert Report of Edward E. Leamer, Ph.D. 438 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page42 of 66 CONFIDENTIAL 12/10/2012 S&P 500 index as an explanatory variable in his conduct regression.”88 87. While it is wise to be looking for variables to include in the model rather than just playing technical games with the standard errors, it is a major mistake to include the S&P index. As Dr. Murphy noted in his deposition, there are literally thousands of macroeconomic variables that might be included.89 Some of these variables are sure to destroy the damage estimate. Locating such a destructive variable is not a success. There has to be some wisdom in the selection of variables to be included. 88. Why would the stock market variable be included at all? My model includes employment in the information sector to capture the overall business cycle effects and also includes firm revenues to capture the cycles afflicting each of the seven Defendants. Dr. Murphy has not provided a persuasive reason that that the S&P 500 index captures cycle issues not already captured by these variables. 89. A stock market index reflects the expected future revenue of the firms that comprise the index. Included among the 500 firms in the S&P index are many firms (e.g., Goldman Sachs) that have no bearing on the Defendant’s compensation. Adobe and Apple do not decide to increase their compensation when the prospects of future revenue at Goldman Sachs improve. It might be more sensible to use the stock market values of the firms themselves (see below) but the revenue variables in my model should capture most of the information in these stock market valuations. 90. Worse yet, Dr. Murphy has used the end-of-year value of the S&P Net Total Revenue Index. If Dr. Murphy's intent was to control for the effect of “general economic and financial performance in the economy”90 on compensation, then his variable must adequately capture this effect and align the timing of the effect with the timing of the dependent variable—in this case total annual compensation, which is not determined until the last minute of the last trading day of the year—since there are stock options, restricted grants and bonuses that accrue throughout the 88 Murphy Report, ¶ 138. 89 Murphy Deposition at 302:18-304:1:4. 90 Murphy Report, ¶ 138. Page 39 Reply Expert Report of Edward E. Leamer, Ph.D. 439 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page43 of 66 CONFIDENTIAL 12/10/2012 year. This is a flawed variable which is not a logical candidate for inclusion in the model. Figure 5: December 31 Was Not a Key Date for Employee Compensation Timing of Substantial Adobe Base Salary Adjustments and Equity Compensation Payouts Date Percent of Workforce Receiving Base Salary Adjustment Date (Percent) (1) Jun-01 Jul-02 Jul-03 Jun-04 Jun-05 Jun-06 Mar-07 Mar-08 Mar-10 Mar-11 Percent of Workforce Receiving Equity Compensation Payout (Percent) (2) 95 % 95 94 94 95 96 95 96 93 91 Mar-01 Nov-01 Nov-02 Dec-03 May-04 May-05 Jun-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 92 % 33 22 47 43 95 65 67 68 51 49 57 Notes: The above lists all the months in which 10 % or more of the workforce received a base salary adjustment or equity compensation payout from 2001-2011. Values are rounded to nearest percentage. Source: Defendants' employee compensation data. 91. One critical problem is that the value of the S&P Index on any particular day does not capture any fluctuations that occurred during the year. If, for example, the S&P were either to rise or fall substantially the last days of December, that movement cannot possibly have had an effect on all the compensation decisions during the preceding year. The total compensation figure that is being explained here reflects base salary as of December and all the bonus and stock payments accumulated over the preceding year. Defendants, like many employers, adjust the salaries and hand out supplemental compensation with a “schedule” that occurs in different points throughout the year. Figure 5 shows the months in each year when large fractions of Page 40 Reply Expert Report of Edward E. Leamer, Ph.D. 440 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page44 of 66 CONFIDENTIAL 12/10/2012 Adobe’s employees received their base salary adjustments or equity compensation. There were only two instances where compensation adjustments for the largest group of employees were made in December. For example, Adobe adjusted most of its employees’ salaries in March, June, and July depending on the year. Adobe’s stock grants were largely paid out in January, May, and November. Figure 6 and Figure 7, below, show that these dates varied across Defendants and across years, but were often earlier in the year. Thus, Dr. Murphy tries to explain an employee's compensation at a point in time with the future level (unknown at the time) of the stock market. Page 41 Reply Expert Report of Edward E. Leamer, Ph.D. 441 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page45 of 66 442 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page46 of 66 443 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page47 of 66 CONFIDENTIAL 92. 12/10/2012 In Figure 8 and Figure 9 below I show the results of a corrected version of Dr. Murphy's sensitivity analysis with the growth of annual average value of S&P 500 Index in place of the end-of-year values. Contra Dr. Murphy, the original results are not sensitive to this change. Dr. Murphy’s finding that the S&P end-of-year appreciation changes my result is a great example of how sensitivity analysis can go wrong. Figure 8: Murphy Damages Model with the Average S&P 500 Index (All) Annual Undercompensation Percentages All-Salaried Employee Class ADOBE 2005 2006 2007 2008 2009 -1.13% -3.02% -4.69% -6.43% -6.49% APPLE -1.13% -3.15% -4.94% -6.79% -6.90% GOOGLE -1.31% -3.27% -4.68% -6.13% -5.48% INTEL -1.19% -3.37% -5.36% -7.23% -7.17% INTUIT LUCASFILM -8.58% -10.34% -12.17% -14.05% -14.16% -2.30% -4.00% -4.03% PIXAR -7.36% -8.56% -9.73% -10.62% -9.66% Source: Regression Estimates of Undercompensation to All-Salaried Employee Class. Figure 9: Murphy Damages Model with the Average S&P 500 Index (R&D) Annual Undercompensation Percentages Technical Employee Class ADOBE 2005 2006 2007 2008 2009 -1.62% -4.44% -6.73% -9.15% -8.82% APPLE -1.93% -5.05% -7.91% -10.80% -10.66% GOOGLE -2.97% -7.02% -9.13% -10.97% -8.83% INTEL -1.69% -3.31% -3.86% -5.41% -4.85% INTUIT -3.50% -5.37% -5.12% LUCASFILM -10.96% -14.83% -18.08% -20.46% -20.50% PIXAR -9.66% -10.99% -11.34% -12.67% -10.52% Source: Regression Estimates of Undercompensation to Technical Employee Class. 93. In addition, I have estimated the conduct regression models incorporating each firm’s annual average stock price values. This variable has a much greater ability to capture any remaining but pertinent effect of “general economic and financial performance” potentially not captured by the revenue variables. Figure 10 and Page 44 Reply Expert Report of Edward E. Leamer, Ph.D. 444 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page48 of 66 CONFIDENTIAL 12/10/2012 Figure 11 below show the undercompensation percentages derived from this regression. Figure 10: Murphy Damages Model with Defendants’ Stock Prices (All) Annual Undercompensation Percentages All-Salaried Employee Class ADOBE 2005 2006 2007 2008 2009 -2.73% -7.24% -11.21% -15.33% -15.40% APPLE -2.66% -7.41% -11.62% -15.97% -16.27% GOOGLE -2.62% -6.59% -9.66% -12.79% -11.45% INTEL -2.78% -7.92% -12.65% -17.06% -16.94% INTUIT -5.44% -9.47% -9.59% Source: Regression Estimates of Undercompensation to All-Salaried Employee Class. Figure 11: Murphy Damages Model with Defendants’ Stock Prices (R&D) Annual Undercompensation Percentages Technical Employee Class ADOBE 2005 2006 2007 2008 2009 -2.83% -7.55% -11.50% -15.65% -15.26% APPLE -3.04% -8.16% -12.72% -17.34% -17.22% GOOGLE -3.77% -9.04% -12.25% -15.22% -12.55% INTEL -2.89% -6.93% -9.83% -13.37% -12.75% INTUIT -5.83% -9.39% -9.19% Source: Regression Estimates of Undercompensation to Technical Employee Class. 1. Dr. Murphy’s Study of Data Subsets Typifies What Happens When a Model is Overloaded 94. A misleading, but unfortunately common, tactic when attacking a regression model is to overload the model with so many variables that it produces wild and statistically insignificant results. This is exactly what Dr. Murphy has done in several different ways. Page 45 Reply Expert Report of Edward E. Leamer, Ph.D. 445 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page49 of 66 CONFIDENTIAL 12/10/2012 95. Dr. Murphy has modified my proposed model of class-wide damages to test for sensitivity to benchmark periods. First, he estimates the conduct regression using only the pre-period as the benchmark. Then he estimates the conduct regression using only the post-period as the benchmark.91 96. In order for a regression model to have any ability to estimate an effect on compensation, the model has to utilize an adequately informative benchmark period. By modifying the regression model to include only pre-conduct (or postconduct) period as a benchmark, Dr. Murphy is trying to estimate the effect of the conduct that occurred over five years by utilizing the experience of merely two nonconspiracy years. It is startling that Dr. Murphy would conduct such an exercise in light of his understanding that the information in the data is limited.92 97. Another “sensitivity” test he conducts is to “first estimate [the] conduct regression using data outside [the] conduct periods, and then use the coefficient estimates to predict compensation during the conduct period.”93 Again, Dr. Murphy puts an enormous burden on a regression model to explain compensation using two disjointed two-year periods. It is important to note that the regression model is dynamic, i.e. incorporates the evolution of both total compensation and macroeconomic factors in explaining compensation levels. Thus, to throw away data in the middle of the time-period in hand (that also covers half of the entire time-period) is not sensible and may lead to an inaccurate and misleading result. 2. Dr. Murphy's Partial Disaggregation by Defendant is Improperly Implemented in a Manner Designed to Make the CONDUCT Variable Perform Poorly 98. 91 Any econometric analysis rests on wisely chosen assumptions about similarities among the observations. A standard similarity assumption is that an individual’s responses to opportunities and stimuli are similar over time, and to the extent that there are dissimilarities these are captured by control variables that change over Murphy Report, ¶ 133. 92 "...[the dataset] effectively [has] fewer than 60 observations from which to estimate [the] conduct variable" (parentheses omitted). Murphy Report, ¶ 123. 93 Murphy Report, ¶ 134. Page 46 Reply Expert Report of Edward E. Leamer, Ph.D. 446 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page50 of 66 CONFIDENTIAL 12/10/2012 time such as age. A similarity assumption is what allows one to use observations of a single individual at different points in time to estimate a model. Without that similarity assumption, estimation of the model cannot proceed. The assumption of similarity of individuals over time is entirely standard. It is also an entirely standard assumption that two individuals in the same firm are similar, and two individuals in different firms are also similar, in the sense that their dissimilarities can be adequately controlled for in the model. This is what allows the estimation of a model based on individual data taken from the same firm and from different firms. 99. Depending on the context, the right place to position a data analysis is somewhere between the extremes of perfect similarity and perfect dissimilarity. But if the data set is large and informative enough, it does little damage to allow perfect dissimilarity in the model, and then let the data decide how much dissimilarity actually applies. However, the weaker and/or briefer is the data set the more reliant we are on making the right similarity assumption. This data set we are studying is too limited to throw away the similarity-across-firms assumption as Dr. Murphy proposes. 100. Dr. Murphy, in his critique regarding the correlation across individuals, says that the dataset in reality is not as large as it seems. “Dr. Leamer’s sample contains over 500,000 individual observations, but fewer than 60 unique combinations of employer and year (and thus effectively fewer than 60 observations from which to estimate his conduct variable).”94 This should have been an alert to Dr. Murphy that one can only go so far in including variables that could reliably identify the conduct effect. By incorporating an additional 42 conduct interaction variables, Dr. Murphy has overwhelmed the model, making the conduct effect virtually unidentifiable.95 101. Complete disaggregation would require an entirely distinct model for each Defendant. Per Dr. Murphy’s thinking about the effective number of observations, this would reduce the number to at most 11 annual observations for each Defendant, and it would be impossible to estimate a model of the scope of mine with so few time-series experiments. Dr. Murphy has not gone that far. What he has done is to disaggregate each and every variable in my model that is directly related to the 94 Murphy Report, ¶ 123. 95 Murphy Report, Appendix 9A-9B. Page 47 Reply Expert Report of Edward E. Leamer, Ph.D. 447 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page51 of 66 CONFIDENTIAL 12/10/2012 CONDUCT effect, but he has left all other variables free of the Defendant effect. This seems designed only to minimize artificially the CONDUCT variable, not to approach sensibly the disaggregation issue. 102. In my model I allow some amount of variability in the CONDUCT effect across Defendants depending on their rates of hiring. In my model, I have allowed for the lagged dependent variables to vary by Defendant because it became apparent that the time series patterns were different, especially for the Google data. If I were going to disaggregate one more effect it would be revenue, based on the idea that these seven firms might have had different approaches to sharing their revenue gains with their employees. In other words, disaggregation requires better judgment than just throwing an excessive set of additional variables into the model, as Dr. Murphy has done. 3. Firm-Wide Data Can Correct for the Correlation Problem 103. As Dr. Murphy points out, the issue with correlation across individuals can be solved in different ways.96 One of Dr. Murphy’s sources identifies “use group averages instead of microdata” as one of three solutions to correlated observations.97 The perils of disaggregation with this dataset can be clearly seen if one estimates the model with an annual averaged dataset by employer-year. 104. With these firm-level annual aggregates, as Dr. Murphy points out (if we reject his earlier opinion regarding the absence of Defendants’ compensation structures), there are only have 60 observations to work with. With only nine or fewer observations per Defendant it is impossible to estimate a separate equation for each Defendant. Expressed differently, with a fully disaggregated model the standard errors of the coefficients are very large–infinite in fact. Inevitably, as we move in the direction of full disaggregation, the standard errors are going to get larger and larger. We thus need some wisdom to decide how much disaggregation is best. 96 “[The test] establishes the need to use ‘clustered’ standard errors (or correct for the correlation in other ways.)” Murphy Report, ¶137. 97 Angrist, J. D. and J. Pischke, Mostly Harmless Econometrics, New Jersey: Princeton University Press, 2009, Chapter 8.2, pp. 312-313. Page 48 Reply Expert Report of Edward E. Leamer, Ph.D. 448 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page52 of 66 CONFIDENTIAL 12/10/2012 105. 106. The challenge with estimating a model with few observations and many potential variables is to choose wisely the similarity assumption. Using the employer-year data we can allow the conduct effect to vary freely for each Defendant as proposed by Dr. Murphy. We can also incorporate the firms’ stock prices to fully account for “general economic and financial performance,” of which Dr. Murphy expressed concern. However, with so few observations we have to make a judgment about how many other variables we want to include. I have decided to limit the persistence variables to one-lag, common across defendants, and to exclude the trend variable, both for the same reason–this is a too short a times series to pick up these effects. Figure 12 and Figure 14 show the corresponding conduct regression model which uses annual average data at company-year levels instead of individual employee observations. Here, a single conduct variable is interacted with each employer, meaning that the effect of the agreement is allowed to be completely distinct for each Defendant. In addition, I include the lag of annual average stock prices of the companies, similar to Dr. Murphy’s use of the S&P 500 index. 107. With a small sample size (30 degrees of freedom) the burden is too high to allow statistical significance of the collection of all variables at conventional 95 percent or 90 percent levels. However, the T-values on the conduct coefficients are relatively high and provide evidence that the negative coefficients did not occur by mere chance. The p-value on all conduct coefficients is less than 0.5 which suggests that it is more likely than not that the compensation of employees were decreased during the period of the agreements. In addition, the test of joint significance of the conduct effect shows statistical significance for both the All Employee Class and the Technical Employee Class. 108. 98 Though the information in the employer-year data is limited, we can still extract some useful information from it. Figure 13 and Figure 15 contain the associated conduct effects from the model showing under-compensation for all Defendants in all years.98 Pixar and Lucasfilm effects have not been computed due to unavailability of stock price data. Page 49 Reply Expert Report of Edward E. Leamer, Ph.D. 449 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page53 of 66 CONFIDENTIAL 12/10/2012 Figure 12: Conduct Regression with Firm-Wide Compensation Data All-Salaried Employee Class Observation: Firm record in each year Dependant Variable: Log(Average Annual Compensation/CPI) Estimate (1) Variable Conduct_ADOBE Conduct_APPLE Conduct_GOOGLE Conduct_INTEL Conduct_INTUIT Log(Average Annual Compensation/CPI)(-1) DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Log(Number of New Hires in the Firm/Number of Employees(-1)) Log(Annual Average Stock Price )(-1) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) APPLE GOOGLE INTEL INTUIT Constant Observations R-square P-Value of the test for Joint Significance of Conduct Coefficients -0.1369 -0.0675 -0.2045 -0.1401 -0.0510 -0.2491 0.1529 0.1516 0.0067 0.1609 -0.1627 0.3455 -0.2395 -0.1639 -0.3122 -0.0817 9.2323 47 0.961 0.006 St. Error (2) ** *** ** * *** *** ** *** *** *** *** T-Value (3) (1)/(2) 0.0561 0.0552 0.0669 0.0547 0.0588 0.1315 0.2649 0.0358 0.0298 0.0330 0.0607 0.0999 0.0819 0.1020 0.0642 0.0511 0.9529 P-Value (4) -2.44 -1.22 -3.06 -2.56 -0.87 -1.89 0.58 4.23 0.23 4.88 -2.68 3.46 -2.92 -1.61 -4.86 -1.60 9.69 0.02 0.23 0.00 0.02 0.39 0.07 0.57 0.00 0.82 0.00 0.01 0.00 0.01 0.12 0.00 0.12 0.00 *** Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level (2) Average Annual Compensation is computed as the mean of employee annual total compensation Employee's total compensation is the sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings (5) Pixar and Lucasfilm are omitted from these equations (6) Defendant stock prices are computed as the annual average of the daily adjusted closing prices Source: Defendants' employee compensation data; St Louis Fed Reserve; SEC Filings; Yahoo Finance Page 50 Reply Expert Report of Edward E. Leamer, Ph.D. 450 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page54 of 66 CONFIDENTIAL 12/10/2012 Figure 13: Under-Compensation with Firm-Level Compensation Data All-Salaried Employee Class ADOBE 2005 2006 2007 2008 2009 -6.85% -11.99% -10.71% -11.03% -0.68% APPLE -3.37% -5.90% -5.27% -5.43% -0.33% GOOGLE -10.23% -17.91% -15.99% -16.47% -1.01% INTEL -7.00% -12.26% -10.95% -11.28% -0.69% INTUIT -5.10% -3.83% -0.32% Source: Regression Estimates of Firm-level Undercompensation to All-Salaried Employee Class. Page 51 Reply Expert Report of Edward E. Leamer, Ph.D. 451 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page55 of 66 CONFIDENTIAL 12/10/2012 Figure 14: Conduct Regression with Firm-Level Compensation Data (R&D) Technical Employee Class Observation: Firm record in each year Dependant Variable: Log(Average Annual Compensation/CPI) Variable Estimate (1) Conduct_ADOBE Conduct_APPLE Conduct_GOOGLE Conduct_INTEL Conduct_INTUIT Log(Average Annual Compensation/CPI) (-1) DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Log(Number of New Hires in the Firm/Number of Employees(-1)) Log(Annual Average Stock Price)(-1) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) APPLE GOOGLE INTEL INTUIT Constant Observations R-square P-Value of the test for Joint Significance of the Conduct Coefficients -0.1314 -0.1020 -0.1657 -0.1139 -0.0363 -0.3001 0.0384 0.1575 0.0491 0.1537 -0.1883 0.4845 -0.3421 -0.1707 -0.0807 0.0015 9.7441 47 0.931 0.093 St. Error (2) * * * *** *** ** *** *** *** T-Value (3) (1)/(2) 0.0719 0.0731 0.0859 0.0704 0.0764 0.1576 0.3368 0.0464 0.0403 0.0390 0.0786 0.1366 0.1105 0.1303 0.0704 0.0641 1.2094 P-Value (4) -1.83 -1.40 -1.93 -1.62 -0.48 -1.90 0.11 3.40 1.22 3.94 -2.39 3.55 -3.10 -1.31 -1.15 0.02 8.06 0.08 0.17 0.06 0.12 0.64 0.07 0.91 0.00 0.23 0.00 0.02 0.00 0.00 0.20 0.26 0.98 0.00 * Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level (2) Average Annual Compensation is computed as the mean of employee annual total compensation Employee's total compensation is the sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings (5) Pixar and Lucasfilm are omitted from these equations (6) Defendant stock prices are computed as the annual average of the daily adjusted closing prices Source: Defendants' employee compensation data; St Louis Fed Reserve; SEC Filings; Yahoo Finance Page 52 Reply Expert Report of Edward E. Leamer, Ph.D. 452 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page56 of 66 CONFIDENTIAL 12/10/2012 Figure 15: Under-Compensation with Firm-level Compensation Data (R&D) Technical Employee Class ADOBE 2005 2006 2007 2008 2009 -6.57% -11.16% -9.79% -10.20% -0.22% APPLE -5.10% -8.67% -7.60% -7.92% -0.17% GOOGLE -8.28% -14.08% -12.34% -12.87% -0.28% INTEL -5.69% -9.68% -8.48% -8.84% -0.19% INTUIT -3.63% -2.54% -0.15% Source: Regression Estimates of Firm-level Undercompensation to Technical Employee Class. C. Both Dr. Murphy’s and My Conduct Regression Analyses Demonstrate the Feasibility of the Regression Approach 109. V. The analyses described in this report are performed for the purpose of demonstrating the availability of proof and statistical methodologies common to members of the All-Employee Class and the Technical Employee Class capable of showing that all or nearly all members of each class suffered suppressed compensation due to the agreements, and capable of quantifying that harm. I understand that discovery has not yet been completed and that further evidence might emerge that is relevant to my analysis. I reserve the right to consider any such evidence and its impact, if any, on the analysis I have proposed. Conclusion 110. I therefore conclude that common proof, in the form of documents, data, economic theory, and statistical methodologies, is capable of demonstrating that the agreements artificially suppressed compensation of all or nearly all members of the All-Employee Class and Technical Employee Class. I conclude further that reliable Page 53 Reply Expert Report of Edward E. Leamer, Ph.D. 453 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page57 of 66 454 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page58 of 66 CONFIDENTIAL 12/10/2012 Figure 16: Conduct Regression with Average S&P 500 Damages Model Sensitivity Average Annual S&P 500 Price Index All-Salaried Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation/CPI) Variable Conduct * Age Conduct * Age^2 Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1)) Conduct ADOBE * Log(Total Annual Compensation/CPI) (-1) APPLE * Log(Total Annual Compensation/CPI) (-1) GOOGLE * Log(Total Annual Compensation/CPI) (-1) INTEL * Log(Total Annual Compensation/CPI) (-1) INTUIT * Log(Total Annual Compensation/CPI) (-1) PIXAR * Log(Total Annual Compensation/CPI) (-1) LUCASFILM * Log(Total Annual Compensation/CPI) (-1) ADOBE * Log(Total Annual Compensation/CPI) (-2) APPLE * Log(Total Annual Compensation/CPI) (-2) GOOGLE * Log(Total Annual Compensation/CPI) (-2) INTEL * Log(Total Annual Compensation/CPI) (-2) INTUIT * Log(Total Annual Compensation/CPI) (-2) PIXAR * Log(Total Annual Compensation/CPI) (-2) LUCASFILM * Log(Total Annual Compensation/CPI) (-2) Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Year (trend) Log(Number of New Hires In the Firm/Number of Employees(-1)) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Revenue Per Employee/CPI) (-1) DLog(Average Annual S&P 500 Index/CPI) (-1) APPLE GOOGLE INTEL INTUIT LUCASFILM PIXAR Location (State) Indicators Constant R-Square Observations St. Error T-Value (1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. Estimate (2) (3) (1)/(2) 0.0063 -0.0001 0.0020 -0.1462 0.7019 0.7360 0.4957 0.6767 0.7009 0.6874 0.8040 0.2889 0.2636 0.3704 0.2929 0.2612 0.1777 0.1868 -0.3420 0.0374 0.0011 -0.0002 0.0031 1.4161 0.0699 -0.0015 0.0082 -0.2188 -0.0653 0.1495 0.0283 0.0459 1.0149 0.1389 0.1720 0.7927 0.0688 YES YES *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** 0.0005 0.0000 0.0008 0.0101 0.0055 0.0027 0.0017 0.0024 0.0058 0.0055 0.0364 0.0053 0.0027 0.0016 0.0024 0.0056 0.0053 0.0368 0.0415 0.0056 0.0050 0.0006 0.0005 0.0156 0.0023 0.0005 0.0009 0.0022 0.0032 0.0029 0.0042 0.0162 0.0174 0.0146 0.0194 0.0264 0.0482 13.2360 -13.3757 2.6888 -14.5355 128.7812 276.8118 291.0496 276.7756 121.2948 124.2378 22.0576 54.3200 96.0626 225.9483 123.0515 46.6472 33.6197 5.0733 -8.2341 6.6385 0.2292 -0.2769 5.6325 90.8003 30.1449 -3.2232 8.9620 -100.3416 -20.6351 51.6893 6.7791 2.8270 58.3255 9.4968 8.8857 30.0816 1.4272 0.926 508,969 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted. (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources. (5) Observations are restricted to cases in which there was no change in employer in the previous two years. (6) S&P 500 Index is computed as the average of the daily adjusted close values. Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finance; PrivCo and public sources. Page 55 Reply Expert Report of Edward E. Leamer, Ph.D. 455 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page59 of 66 CONFIDENTIAL 12/10/2012 Figure 17: Conduct Regression with Average S&P 500 (R&D) Damages Model Sensitivity S&P 500 Price Index Technical Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation/CPI) Variable Conduct * Age Conduct * Age^2 Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1)) Conduct ADOBE * Log(Total Annual Compensation/CPI) (-1) APPLE * Log(Total Annual Compensation/CPI) (-1) GOOGLE * Log(Total Annual Compensation/CPI) (-1) INTEL * Log(Total Annual Compensation/CPI) (-1) INTUIT * Log(Total Annual Compensation/CPI) (-1) PIXAR * Log(Total Annual Compensation/CPI) (-1) LUCASFILM * Log(Total Annual Compensation/CPI) (-1) ADOBE * Log(Total Annual Compensation/CPI) (-2) APPLE * Log(Total Annual Compensation/CPI) (-2) GOOGLE * Log(Total Annual Compensation/CPI) (-2) INTEL * Log(Total Annual Compensation/CPI) (-2) INTUIT * Log(Total Annual Compensation/CPI) (-2) PIXAR * Log(Total Annual Compensation/CPI) (-2) LUCASFILM * Log(Total Annual Compensation/CPI) (-2) Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Year (trend) Log(Number of New Hires In the Firm/Number of Employees(-1)) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Revenue Per Employee/CPI) (-1) DLog(Average Annual S&P 500 Index/CPI) (-1) APPLE GOOGLE INTEL INTUIT LUCASFILM PIXAR Location (State) Indicators Constant R-Square Observations St. Error T-Value (1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. Estimate (2) (3) (1)/(2) 0.0073 *** -0.0001 *** -0.0111 *** -0.2043 *** 0.6785 *** 0.7207 *** 0.4390 *** 0.6425 *** 0.6598 *** 0.6715 *** 0.8388 *** 0.3008 *** 0.2554 *** 0.3620 *** 0.3159 *** 0.2944 *** 0.1046 *** 0.1484 ** -0.5788 *** 0.0686 *** 0.0206 *** -0.0016 ** 0.0066 *** 1.4834 *** 0.0839 *** -0.0012 ** 0.0139 *** -0.2433 *** -0.0417 *** 0.1344 *** -0.0120 ** 0.1156 *** 1.3634 *** 0.1430 *** 0.1581 *** 1.3259 *** -0.0045 YES YES 0.0007 0.0000 0.0010 0.0141 0.0073 0.0037 0.0022 0.0031 0.0085 0.0082 0.0694 0.0072 0.0038 0.0021 0.0030 0.0082 0.0075 0.0695 0.0587 0.0080 0.0068 0.0008 0.0008 0.0215 0.0032 0.0006 0.0013 0.0030 0.0043 0.0039 0.0059 0.0245 0.0259 0.0219 0.0316 0.0456 0.1040 10.8468 -10.8864 -10.8652 -14.4664 92.8530 197.2983 201.3110 209.3370 77.9206 82.2910 12.0842 42.0295 67.3782 172.2609 106.0838 35.9215 13.9643 2.1350 -9.8583 8.5921 3.0315 -2.0654 8.0584 68.9315 25.9499 -1.9713 11.0076 -81.5647 -9.6674 34.7738 -2.0435 4.7167 52.5895 6.5202 5.0062 29.0711 -0.0429 0.873 295,136 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted. (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources. (5) Observations are restricted to cases in which there was no change in employer in the previous two years. (6) S&P 500 Index is computed as the average of the daily adjusted close values. Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finance; PrivCo and public sources. Page 56 Reply Expert Report of Edward E. Leamer, Ph.D. 456 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page60 of 66 CONFIDENTIAL 12/10/2012 Figure 18: Conduct Regression with Average Defendant Stock Prices Damages Model Sensitivity Defendants Stock Prices All-Salaried Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation/CPI) Variable Conduct * Age Conduct * Age^2 Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1)) Conduct ADOBE * Log(Total Annual Compensation/CPI) (-1) APPLE * Log(Total Annual Compensation/CPI) (-1) GOOGLE * Log(Total Annual Compensation/CPI) (-1) INTEL * Log(Total Annual Compensation/CPI) (-1) INTUIT * Log(Total Annual Compensation/CPI) (-1) ADOBE * Log(Total Annual Compensation/CPI) (-2) APPLE * Log(Total Annual Compensation/CPI) (-2) GOOGLE * Log(Total Annual Compensation/CPI) (-2) INTEL * Log(Total Annual Compensation/CPI) (-2) INTUIT * Log(Total Annual Compensation/CPI) (-2) Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Year (trend) Log(Number of New Hires In the Firm/Number of Employees(-1)) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Stock Price/CPI) (-1) APPLE GOOGLE INTEL INTUIT Location (State) Indicators Constant R-Square Observations St. Error T-Value (1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. Estimate (2) (3) (1)/(2) 0.0059 *** -0.0001 *** 0.0050 *** -0.1641 *** 0.6791 *** 0.7447 *** 0.4969 *** 0.6765 *** 0.7036 *** 0.3128 *** 0.2563 *** 0.3677 *** 0.2933 *** 0.2640 *** -0.3530 *** 0.0387 *** -0.0066 0.0006 0.0024 *** 1.5922 *** 0.1345 *** -0.0102 *** 0.0106 *** -0.2832 *** -0.1324 *** 0.2879 *** -0.0635 *** 0.1072 *** 1.0906 *** 0.1434 *** 0.1166 *** YES YES 0.0005 0.0000 0.0008 0.0099 0.0054 0.0026 0.0017 0.0023 0.0057 0.0052 0.0027 0.0016 0.0023 0.0055 0.0409 0.0056 0.0049 0.0005 0.0005 0.0160 0.0020 0.0004 0.0011 0.0023 0.0037 0.0039 0.0024 0.0160 0.0172 0.0143 0.0189 12.6097 -12.7988 6.1651 -16.6155 126.6528 284.8534 294.8958 289.6740 123.4117 59.7396 95.2506 227.2142 129.1129 47.7498 -8.6315 6.9805 -1.3269 1.1477 4.3928 99.7455 67.2381 -29.1819 9.8170 -125.2556 -36.0708 74.6261 -26.4568 6.7153 63.4232 10.0217 6.1546 0.929 499,964 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted. (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources. (5) Observations are restricted to cases in which there was no change in employer in the previous two years. (6) Firm Stock Price computed as the average of the daily adjusted close values. Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finance; PrivCo and public sources. Page 57 Reply Expert Report of Edward E. Leamer, Ph.D. 457 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page61 of 66 CONFIDENTIAL 12/10/2012 Figure 19: Conduct Regression with Average Defendant Stock Prices (R&D) Damages Model Sensitivity Defendants Stock Prices Technical Employee Class Observation: Employee ID record in December of each year Dependant Variable: Log(Total Annual Compensation/CPI) Variable Conduct * Age Conduct * Age^2 Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1)) Conduct ADOBE * Log(Total Annual Compensation/CPI) (-1) APPLE * Log(Total Annual Compensation/CPI) (-1) GOOGLE * Log(Total Annual Compensation/CPI) (-1) INTEL * Log(Total Annual Compensation/CPI) (-1) INTUIT * Log(Total Annual Compensation/CPI) (-1) ADOBE * Log(Total Annual Compensation/CPI) (-2) APPLE * Log(Total Annual Compensation/CPI) (-2) GOOGLE * Log(Total Annual Compensation/CPI) (-2) INTEL * Log(Total Annual Compensation/CPI) (-2) INTUIT * Log(Total Annual Compensation/CPI) (-2) Log(Age) (Years) Log(Age)^2 Log(Company Tenure) (Months) Log(Company Tenure)^2 Male DLog(Information Sector Employment in San-Jose) Log(Total Number of Transfers Among Defendants) Year (trend) Log(Number of New Hires In the Firm/Number of Employees(-1)) Log(Total Number of New Hires) Log(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Revenue Per Employee/CPI) (-1) DLog(Firm Stock Price/CPI) (-1) APPLE GOOGLE INTEL INTUIT Location (State) Indicators Constant R-Square Observations St. Error T-Value (1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. Estimate (2) (3) (1)/(2) 0.0068 *** -0.0001 *** -0.0068 *** -0.2093 *** 0.6547 *** 0.7255 *** 0.4402 *** 0.6492 *** 0.6566 *** 0.3255 *** 0.2508 *** 0.3647 *** 0.3099 *** 0.3034 *** -0.5858 *** 0.0692 *** 0.0133 ** -0.0008 0.0064 *** 1.6607 *** 0.1384 *** -0.0083 *** 0.0127 *** -0.3042 *** -0.0889 *** 0.2670 *** -0.0750 *** 0.1724 *** 1.3815 *** 0.1377 *** 0.1070 *** YES YES 0.0007 0.0000 0.0011 0.0139 0.0072 0.0036 0.0022 0.0029 0.0084 0.0071 0.0037 0.0021 0.0029 0.0081 0.0581 0.0079 0.0068 0.0007 0.0008 0.0223 0.0027 0.0005 0.0015 0.0031 0.0051 0.0052 0.0033 0.0242 0.0256 0.0216 0.0311 10.1839 -10.2118 -6.2079 -15.0404 90.5135 200.5749 203.3944 220.4243 78.0298 45.9360 67.1304 174.9147 108.6765 37.2460 -10.0799 8.7670 1.9736 -1.1196 7.8292 74.6125 50.6807 -17.1490 8.4763 -97.8766 -17.4255 51.1627 -22.4884 7.1223 53.8927 6.3813 3.4413 0.878 290,089 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Total Annual Compensation is computed as sum of base annual compensation (in December), overtime pay, bonus, and value of equity compensation granted. (3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and restricted stock units from SEC Filings. (4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources. (5) Observations are restricted to cases in which there was no change in employer in the previous two years. (6) Firm Stock Price computed as the average of the daily adjusted close values. Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finace; PrivCo and public sources. Page 58 Reply Expert Report of Edward E. Leamer, Ph.D. 458 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page62 of 66 CONFIDENTIAL 12/10/2012 Exhibit 1 List of Additional Materials Relied Upon Pleadings and Orders Date Defendants' Notice of Motion and Motion to Strike the Report of Dr. Edward E. Leamer 11/12/12 Opposition to Plaintiffs' Motion for Class Certification 11/12/12 Declarations Burmeister, Steven 11/12/12 Galy, Chris 11/09/12 Maupin, Michelle 11/12/12 McAdams, Lori 11/12/12 McKell, Danny 11/12/12 Morris, Donna 11/09/12 Vijungco, Jeff 11/09/12 Wagner, Frank 11/09/12 Depositions and Exhibits Date Leamer, Edward 10/26/12 Murphy, Kevin M. 12/03/12 Zissimos, Pamela 11/13/12 Page 1 of 5 459 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page63 of 66 CONFIDENTIAL 12/10/2012 Exhibit 1 List of Additional Materials Relied Upon Expert Reports Date Expert Report of Edward E. Leamer, PhD 10/01/12 Expert Report of Professor Kevin M. Murphy, PhD 11/12/12 Publicly Available Materials Angrist, J. D. and J. Pischke, Mostly Harmless Econometrics, New Jersey: Princeton University Press, 2009, Chapter 8.2. Creswell, J. W., and V. L. Plano Clark, Designing and Conducting Mixed Methods Research, SAGE Publication: 2007, Chapter 6. Creswell, J. W., Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, SAGE Publication: 2009, Chapter 9. Di Maria, C. H., and S. Metzler, "Internal Wage Structure and Bank Performance in Productivity in the Financial Services Sector," The European Money and Finance Forum Vienna (2009), Chapter 9. Fehr, E., L. Goette and C. Zehnder, “A Behavioral Account of the Labor Market: The Role of Fairness Concerns," Annual Review of Economics , (2009). Gerhart, M., G. Milkovich and J. Newman, Compensation, New York: McGraw-Hill Irwin, 2011, Chapter 3. Hamermesh, D.S., “Interdependence in the labour market,” Economica , (1975). Isaac, J. E. , “Performance related pay: The importance of fairness,” Journal of Industrial Relations , Vol. 43, No. 2 (June 2001). Kahneman, D., Thinking, Fast and Slow, Farrar, Straus and Giroux, 2011. Levine, D. I., “Fairness, markets, and ability to pay: Evidence from compensation executives,” The American Economic Review , Vol. 83, No. 5 (December 1993). Machin, S. and A. Manning, "A test of competitive labor market theory: the wage structure among elder care assistants in the South of England," ILRReview , Vol. 57, No. 3 (April 2004). Page 2 of 5 460 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page64 of 66 CONFIDENTIAL 12/10/2012 Exhibit 1 List of Additional Materials Relied Upon Piore, M. J., “Qualitative Research: Does It Fit In Economics?,” European Management Review , (2006) 3, 17-23. Rees, A. "The Role of Fairness in Wage Determination," Journal of Labor Economics , 1993, Vol. 11, No. 1, pt. 1. Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American Economic Review , Vol. 92, No. 3 (June 2002). "The Prize in Economic Sciences 2012," Nobelprize.org., December 10, 2012, http://www.nobelprize.org/nobel_prizes/economics/laureates/2012/. "The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002," Nobelprize.org., December 10, 2012, http://www.nobelprize.org/nobel_prizes/economics/laureates/2002/. Documents Adobe ADOBE_002764 ADOBE_008098 ADOBE_008398 ADOBE_008692 ADOBE_009327 ADOBE_016608 - ADOBE_002765 ADOBE_008099 ADOBE_008399 ADOBE_008693 - ADOBE_016655 Apple 231APPLE010841 - 231APPLE010843 231APPLE055294 - 231APPLE055305 231APPLE056385 - 231APPLE056386 Page 3 of 5 461 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page65 of 66 CONFIDENTIAL 12/10/2012 Exhibit 1 List of Additional Materials Relied Upon 231APPLE081072 - 231APPLE081075 231APPLE094041 - 231APPLE094067 Google GOOG-HIGH TECH-00009270 GOOG-HIGH TECH-00009454 GOOG-HIGH TECH-00036370 GOOG-HIGH TECH-00038253 GOOG-HIGH TECH-00194984 GOOG-HIGH TECH-00195005 GOOG-HIGH TECH-00195364 GOOG-HIGH TECH-00210276 GOOG-HIGH TECH-00233026 - GOOG-HIGH TECH-00009276 GOOG-HIGH TECH-00009458 GOOG-HIGH TECH-00036461 GOOG-HIGH TECH-00038274 GOOG-HIGH TECH-00194985 GOOG-HIGH TECH-00195007 GOOG-HIGH TECH-00195365 GOOG-HIGH TECH-00210276 GOOG-HIGH TECH-00233057 Intel 76512DOC000025 76512DOC000926 76526DOC000714 76582DOC000902 76616DOC005974 - 76512DOC000026 - 76512DOC000943 - 76582DOC000922 - 76616DOC005981 Page 4 of 5 462 Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page66 of 66 CONFIDENTIAL 12/10/2012 Exhibit 1 List of Additional Materials Relied Upon Intuit INTUIT_003008 - INTUIT_003011 Lucasfilm LUCAS00004721 - LUCAS00004753 LUCAS00035991 - LUCAS00035992 LUCAS00036013 - LUCAS00036014 Pixar PIX00009271 - PIX00009272 PIX00023020 - PIX00023021 Page 5 of 5 463 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page1 of 62 IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA SAN JOSE DIVISION CONFIDENTIAL – TO BE FILED UNDER SEAL SUBJECT TO PROTECTIVE ORDER IN RE: HIGH-TECH EMPLOYEES ANTITRUST LITIGATION No. 11-CV-2509-LHK _____________________________________ THIS DOCUMENT RELATES TO: ALL ACTIONS SUPPLEMENTAL EXPERT REPORT OF EDWARD E. LEAMER, PH.D. May 10, 2013 [REDACTED] 464 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page2 of 62 TABLE OF CONTENTS I.  Introduction, Assignment, and Summary of Conclusions ..........1  II.  Defendants’ Use of Compensation Structures............................4  III.  Empirical Methodologies for Exploring the Somewhat Rigid Salary Structure ........................................................................6  A.  Choice of Aggregation Level .............................................................. 6  B.  Correlation Analysis of Compensation Structure ................................... 7  C.  Regression Analysis of Compensation Structure ................................... 7  IV.  Results of Title Based Correlations and Multiple Regressions ..10  A.  Title-by-Title Correlation Analysis of Compensation Structure .............. 10  B.  Title-by-Title Multiple Regressions ................................................... 14  V.  Decile Based Correlations and Multiple Regressions ...............18  A.  Decile Based Correlation Analysis .................................................... 18  B.  Decile Based Multiple Regression Results .......................................... 20  VI.  Additional Exploration of Adobe Correlations ..........................22  1.  Adobe Correlation Results .......................................................... 22  2.  Headcount Matters for Interpreting Correlations ............................ 24  3.  Correlations ............................................................................. 25  4.  Outliers ................................................................................... 26  VII.  Internal Versus External Forces .............................................. 29  i Supplemental Expert Report of Edward E. Leamer, Ph.D. 465 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page3 of 62 CONFIDENTIAL I. 5/10/2013 Introduction, Assignment, and Summary of Conclusions 1. I have been asked by counsel for Class Plaintiffs in this matter to respond to the following questions regarding my prior analysis and further analysis that can be conducted based on the available data in this case. I have been asked to focus my response on the employees belonging to the proposed Technical, Creative and R&D Class (“Technical Class”) identified in my initial report. 2. Question #1: Does the total compensation of Technical Class employees in specific job titles move together over time, further confirming the existence of a somewhat rigid pay structure at each Defendant? 3. Answer: When asked in the deposition (p283) “Could a nonrigid wage structure, as you've defined it, lead to parallel lines?” I responded to what I thought to be a hypothetical with “Yes, it could.” I should have added that this would require highly unusual external labor market conditions which dictated the parallel movements of vast numbers of titles. Markets typically are not so orderly, and prices of, for example, gold, silver, copper and zinc do not normally move in parallel. For that reason, I regard the parallel movements of compensation for so many titles not only to be consistent with a “somewhat rigid wage structure” but also evidence specifically in favor of the hypothesis that internal equity played an important role in determining compensation in all these firms. In this report, I confirm this opinion with two additional empirical studies. I have estimated regression models that allow me to separate the contributions of internal and external forces, and found that the internal forces are evident but the external forces are not. I have also compared average compensation for the Technical Class of titles and the non-technical employees for all the defendants. I found that the compensation curves of these two groups within each firm are highly parallel while the compensation curves for the same group from two different firms move in a much more disparate way. This again is saying that the internal forces are evident but the external forces are more difficult to detect. 4. In this Report, I present correlations that compare the movement over time of the average compensation of each title with the average compensation of the firm’s Technical Class. To accommodate titles that cannot be accessed on a title-byPage 1 Supplemental Expert Report of Edward E. Leamer, Ph.D. 466 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page4 of 62 CONFIDENTIAL 5/10/2013 title basis due to insufficient data (approximately 63 percent of Technical Class titles, but representing just 6 percent of Class Period employee-years), I also analyzed correlations of relatively narrow groups of employees (each comprising approximately a tenth of the Technical Class employees of that firm). These correlations are computed for all titles, not just 20. They reveal that there is large amount of co-movement of compensation among most of the Technical Class titles of each defendant. These correlations are consistent with a topdown budgeting method in which all members of the firm in any given year receive a common compensation increment, which is adjusted somewhat by title and possibly by individual within the title depending on specific circumstances. The evident, substantial, common, firm-wide component of compensation is what creates what I previously called a “somewhat rigid” salary structure, which allows the effects of the anti-cold-calling conspiracy to spread broadly across each firm. 5. Question #2: Do the data show additional evidence that internal factors such as internal equity partly drove the Defendants’ compensation structures, as opposed to only external market forces? 6. Answer: I have analyzed a model of sharing of compensation effects, title by title, within Defendant firms relative to movements of other Technical Class employees compensation. Again, to accommodate titles that cannot be accessed title-by-title (approximately 70 percent of Technical Class titles, but representing just 8.4 percent of Class Period employee-years), I also analyzed the compensation of relatively narrow groups of employees against the compensation of the overall Technical Class employees. 7. Specifically, I report below estimated multiple regression models that explain the year-by-year increases in average compensation at the title level in terms of four explanatory variables: (1) increases in average Technical Class compensation; (2) the previous year’s ratio of average Technical Class compensation divided by the average title compensation; (3) the previous year’s ratio of firm-wide average revenue divided by the average title compensation; (4) the percent change in software jobs in the San Jose-Sunnyvale-Santa Clara Metropolitan Statistical Area (hereafter: San Jose MSA). Page 2 Supplemental Expert Report of Edward E. Leamer, Ph.D. 467 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page5 of 62 CONFIDENTIAL 5/10/2013 8. I find that the vast majority of individuals fall within titles or groups that show 1) positive contemporaneous sharing of compensation effects, and 2) sharing across time that would spread gains in compensation across other job titles. This is consistent with my previous opinion that all or almost all Defendants’ employees would have been impacted by the non-compete agreements. Furthermore, the sharing of gains over time strongly indicates the existence of an internal sharing force driving the structure of class member compensation, rather than only external market forces. 9. Question #3: Do the data show the existence of large groups of class members who necessarily would not have been harmed by a restriction on coldcalling? 10. Answer: No. I have performed the above-mentioned statistical analyses separately for distinct subgroups of employees grouped by compensation level. I do not find persuasive evidence to suggest that there are sizeable groups whose compensation might have been disconnected from Defendants’ somewhat rigid compensation structure. The correlation and regression analysis I performed in this regard show ripple and spillover effects across employees in very different roles. The analysis shows that when each title or group is studied separately, on a case-by-case basis, it is found that, compensation almost always moves with the collection of other titles or groups. All these groups, no matter how much they differ in the job titles they contain, are found to be tied closely together. 11. Question # 4: Is it possible to identify and exclude from the Technical Class job titles based on a lack of these positive correlative relationships? 12. Answer: No. Although the vast majority of titles exhibit strong positive correlations with the overall Technical Class, there certainly are exceptions. One might consider titles with negative correlations with the overall Technical Class to be candidates for exclusion from the class. However, this is not justified statistically because statistical variability can cause some negative correlation estimates among the thousands of titles even if all the true correlations are positive. An appropriate statistical model for this kind of data allows some pooling of evidence across titles, and when this is done the analysis indicates that corrected estimated of many of these negatives is positive. In other words, Page 3 Supplemental Expert Report of Edward E. Leamer, Ph.D. 468 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page6 of 62 CONFIDENTIAL 5/10/2013 it matters for interpreting the evidence about each title that the vast majority of estimated correlations are positive. 13. II. In sum, the statistical analysis I conduct here--in conjunction with the economic and econometric evidence in my original reports--supports my original finding of a somewhat rigid pay structure at each Defendant that would have transmitted the effects of the agreements broadly, including throughout the Technical Class. Defendants’ Use of Compensation Structures 14. Most, if not all, of these defendants subscribe to services that are intended to provide them information about “market” prices for various jobs. Such information helps them keep compensation packages in line with the external opportunities, with or without the imminent threat of loss of an employee. However, these external sources provide broad industry averages with limited relevance and reliability. Regardless of what these services suggest, their information cannot compare with the information conveyed by an actual outside offer. That can ring off a loud alarm that is heard all the way up to the CEO. 15. The information by an outside offer or even a cold call can stimulate a response by management that can go much beyond the specific individual directly affected. A chain of similarities can transmit a bump in compensation for a single individual broadly across a firm for two reasons. First, when management becomes aware of an attractive outside opportunity for one individual this may make management aware also of the implicit competitive threat to similar individuals and management may feel it wise to make a preemptive move against that threat by an increase in compensation for these newly-threatened similar employees. Though the “market” does not require a bump in compensation for these similar individuals until they actually receive an outside offer, preemptive action can minimize the disruption to employee loyalty that might occur when an employee discovers that he or she had been “unfairly” undercompensated. A broad preemptive response is completely analogous to salary increases that are tied to information provided by Page 4 Supplemental Expert Report of Edward E. Leamer, Ph.D. 469 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page7 of 62 CONFIDENTIAL 5/10/2013 employment services regarding the compensation offered by the “market.” These responses are broad and not necessarily individual-based. 16. Similarity in worth is one reason why salaries can be tied together. Fairness is the second reason why a bump in compensation for a single individual can be transmitted broadly across a firm. A critical problem with “market-based” individual compensation is that the productivity of each worker in most salaried jobs is difficult to determine with accuracy, yet the range of achieved productivity can be broad. Firms need to use HR policies that encourage high levels of productivity. The highest levels of productivity come from contented employees who are committed to the mission of the enterprise. In order to maintain or to increase the contentment and commitment, it is essential for management to treat employees “fairly.” As discussed in the paragraph above, a strictly market view of employee compensation doesn’t require an increase in salary of any individual until an outside threat actually materializes, but the force of “fairness” can necessitate preemptive increases in compensation. In addition, employees are likely to have their own views of job and performance similarity, and these employees can have their productivity adversely affected if they perceive that some employees are receiving “unfairly” high compensation compared with them. 17. Fairness is a matter of personal opinion and there is no sure way to know exactly who feels equivalent to the employee who got that bump in compensation and who doesn’t really care. The title and grade structure of compensation may reflect management’s views of what is fair and it may influence the perception of similarity that determines employee fairness beliefs. This is the reason why companies tend to follow guidelines laid out in terms of salary ranges, so employees can be assured that their compensation falls within reasonable range of their colleagues. Page 5 Supplemental Expert Report of Edward E. Leamer, Ph.D. 470 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page8 of 62 CONFIDENTIAL III. 5/10/2013 Empirical Methodologies for Exploring the Somewhat Rigid Salary Structure A. Choice of Aggregation Level 18. The data set I explore is composed of compensation records of salaried individuals on the payrolls of the Defendants. These individuals are grouped by the Defendants by title and (for some of the Defendants) the titles are grouped by grade. Based on instructions from counsel regarding the employees in the Class, except for Lucasfilm I limit the inquiry to the titles that have been identified as Technical Class titles.1 19. These data could be studied at the individual level, at the title level or some more aggregated groups. I have chosen to work first with the title averages, because the individual data is likely to be dominated by forces that operate at the individual level, which can make it difficult to detect the firm wide effects including the spread of the anti-cold-calling agreements broadly across the firms. Averaging across individuals in a title can average out the individual effects, thus making the firm-wide effects more transparent. In addition, a titlelevel analysis provides a clearer perspective on the compensation structures the documentary evidence shows Defendants used to manage their many employees and maintain internal equity among their employees. 20. I have discovered that the title-by-title analysis works well for many titles but there are some titles that were used only briefly, and there are other titles that are sparsely populated and that seem much influenced by the idiosyncratic individual behavior which still masks the firm-wide effect that I am seeking to estimate. The data set contains only eleven annual observations which is adequate for the statistical work, but not plentiful. Titles that have fewer annual observations tend to produce what statisticians call “statistically insignificant” results, meaning the data sets are too small to yield accurate estimates. This is particularly troublesome for Apple which had a title restructuring in 2005 and Because Lucasfilm did not provide title data prior to 2006, there are insufficient years of data unless the inquiry is expanded to cover all Lucasfilm employees. Hence, the analysis presented below is limited to Technical Class for all Defendants, expect Lucasfilm, for whom it applies to all employees. 1 Page 6 Supplemental Expert Report of Edward E. Leamer, Ph.D. 471 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page9 of 62 CONFIDENTIAL 5/10/2013 for Lucasfilm which did not provide titles prior to 2006. In addition titles that include just a few individuals may not benefit much from the averaging across individuals and furthermore, unlike the individual data, the title compensation for sparsely populated titles can vary wildly as individuals come and go. I give some examples below of Adobe titles with highly variable headcounts and highly variable median ages. 21. To deal with the limitations of the title-by-title data, I also include the same type of statistical work but applied to ten groups of titles in each firm. I have formed the ten groups of titles by ordering the titles by average base compensation and then splitting the titles into ten deciles (based on the number of employeeyears).2 B. Correlation Analysis of Compensation Structure 22. Economists often look to correlation coefficients to measure statistically how closely different variables move together. Correlation coefficients range in absolute value from 0 to 1. One indicates perfect correlation, zero indicates no relationship. The sign on the correlation indicates whether or not the series in question move in the same direction. I begin my analysis of Defendant compensation structures with compensation correlations. 23. There are two types of correlations relevant for determining if the compensation movements of two series are similar: correlation of compensation levels and correlations of compensation changes. The correlations of the log of the levels of compensation emphasize longer run movements and the correlations of the change in the log of the levels focus on year-by-year movements. C. Regression Analysis of Compensation Structure 24. Correlation of title compensation and class compensation could come from sharing effects but could also come from third variables that operate on both For several Defendants, certain large titles made splits into ten groups impractical. In those cases a smaller number of groups was used. 2 Page 7 Supplemental Expert Report of Edward E. Leamer, Ph.D. 472 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page10 of 62 CONFIDENTIAL 5/10/2013 title and class compensation at the same time, for example, “market forces.” To confirm the existence of a somewhat rigid compensation structure revealed by my correlation analysis, I examine (company by company) a multiple regression model which forces the class compensation to compete with other variables as an explanation of title compensation. 25. This regression model explains increases in title average real (inflation adjusted) total compensation and includes the increase in class average real total compensation as one of four explanatory variables.3 By including the increase in class compensation in the equation, the regression encompasses the correlation analysis of these two variables. In the multiple regression setting, this variable allows us to determine at a particular defendant the extent to which title and class compensation move together, after controlling for the other variables in the equation, in particular, after controlling for “market forces.” If the coefficient of this variable were equal to one, then the employee would inherit 100 percent of the class compensation changes and in that sense the two would be closely tied together. This is the first sharing effect. 26. The regression model includes a second sharing variable, which is the ratio of class compensation to title compensation in the previous year. While the first sharing effect measures the extent to which the two compensation levels move together, the second measures the extent to which corrective action is taken at the company when they move apart. If the coefficient is positive on this variable it means that following periods in which the class average compensation at the company is abnormally high compared with the title, the title tends to get a special increase in compensation to bring it back in line with the class 27. The regression model requires both of these sharing variables to compete against two other determinants of title compensation at the company. One of these other variables is the previous year’s ratio of firm-wide average revenue divided by the average title compensation. This variable allows us to determine For each title regression I exclude from the class average real total compensation, the compensation of the title itself. 3 Page 8 Supplemental Expert Report of Edward E. Leamer, Ph.D. 473 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page11 of 62 CONFIDENTIAL 5/10/2013 which titles, if any, share increases in firm revenue overall. It might be expected that critical technical and creative workers are the ones who would have revenue sharing relationships with their firms since they may have an accentuated effect on the firm’s success. 28. The fourth variable is the percent growth in software jobs in the San Jose- MSA. This the external job market variable which is intended to reflect how hot or cold was the technical job market generally, not just in the San Jose MSA. 29. I illustrate this regression in Figure 1, as estimated for one Intel title.4 In this example, the two coefficients for the two sharing variables are positive, meaning that workers with this title can expect to receive a compensation increase if 1) there are general increases in the compensation of other Technical Class titles at the firm, and 2) a title that received a relatively small percent increase relative to other Technical Class titles at the company last year will tend to receive a larger increase in subsequent years. This indicates a positive sharing and internal equity effect. Both the contemporaneous and lagged coefficients suggest that internal equity forces move in a fashion that helps align worker’s compensation together with that of employees in other roles at the firm. As mentioned before this regression is estimated separately for each title and company. Titles that do not afford a sufficient number of observations (6 observations, or 7 consecutive years) are treated as ‘Not Estimated’ and are excluded from the coefficient distribution calculations presented in this report. 4 Page 9 Supplemental Expert Report of Edward E. Leamer, Ph.D. 474 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page12 of 62 CONFIDENTIAL 5/10/2013 Figure 1 Illustrative Example of Compensation Sharing Regression Model Intel Named Plaintiff Title SOFTWARE_ENGINEER_7 Variable Coefficient Std.-Error T-value P-value (1) (2) (3) (4) (5) 0.784 *** 0.064 12.238 0.000 0.251 * 0.098 2.562 0.051 -0.032 0.094 -0.346 0.743 0.092 0.126 0.731 0.498 -0.223 0.541 -0.411 0.698 Dependant Variable DLog(Title Average Annual Total Compensation) Contemporaneous Effect Variable DLog(R&D Average Annual Total Compensation) Lagged Effect Variable Log( (R&D Avg Annual Total Comp (-1) / ( Title Avg Annual Total Compensation (-1) External Forces Variables Log( (Firm Revenue Per Employee (-1) / ( Title Avg Annual Total Compensation (-1) DLog( San-Jose Information Sector Employment) Constant Observations R-squared 10 0.986 Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level. (2) Title Average Compensation is computed as the average of title employee's annual total compensation. R&D Avg Total Comp is computed over all Technical, Creative and R&D employees other than the tilte itself (3) All Compensation Variables are Inflation Adjusted Source: Defendants' employee compensation data IV. Results of Title Based Correlations and Multiple Regressions A. Title-by-Title Correlation Analysis of Compensation Structure 30. The correlations for all Defendants are reported in Exhibit 1 (Adobe) and Exhibit 2 (other Defendants). Below I will discuss the Adobe results in detail, but here it is enough to summarize the overall results with Figure 2 and Figure 3, which indicate the fractions of titles (weighted by employee years) with positive correlations between title compensation and Technical Class compensation at the same firm, restricted to titles with six or more annual Page 10 Supplemental Expert Report of Edward E. Leamer, Ph.D. 475 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page13 of 62 CONFIDENTIAL 5/10/2013 observations. The titles with five or fewer tend to produce a more extreme distribution of correlations. 31. Although there are some negative estimated correlations, that does not mean that any true correlations are negative. These estimates are computed with statistical error which is large enough to produce some negative estimates among the thousands of titles included even if all true correlations were positive. 32. Moreover, the fact that the vast majority of cases are positive is strong support for the conclusion that all the true correlations are positive. There are formal statistical methods that allow pooling of results across titles based on the assumption that the titles probably have similar correlations. These methods would shrink the estimates for each title toward the mean across all titles, which is of course positive. Once this shrinkage is done, the results indicate that for many of these negatives the corrected results will be positive, strengthening the conclusion that all titles in the class share movements with the class overall. Figure 2: Large Share of Change Correlations are Positive Compensation Change Correlation by Titles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE Negative INTEL INTUIT PIXAR Positive Source: Defendant Employee Compensation Data; Correlation Analysis Note: Distribution of growth in avg compensation correlation over titles with six or more years of data. Weighted by class-period employee years Page 11 Supplemental Expert Report of Edward E. Leamer, Ph.D. 476 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page14 of 62 CONFIDENTIAL 5/10/2013 Figure 3: Large Share of Level Correlations are Positive Compensation Correlation by Titles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE Negative INTEL INTUIT PIXAR Positive Source: Defendant Employee Compensation Data; Correlation Analysis Note: Distribution of log avg compensation correlation over titles with six or more years of data. Weighted by class-period employee years 33. It is not just statistical variability that can explain the negative or small correlations. Changes in the composition of employees within a title as employees come and go can cause changes in title compensation and mask the normal correlation with the class overall. I will illustrate this point below with a close examination of some of the Adobe titles that have low or negative correlations with the class. Page 12 Supplemental Expert Report of Edward E. Leamer, Ph.D. 477 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page15 of 62 CONFIDENTIAL 5/10/2013 Figure 4 Summary of Compensation Change Correlation Positive Sign Employer Negative Sign Not Significant Significant Not Significant Total (Percent) ADOBE APPLE GOOGLE INTEL INTUIT PIXAR Significant (Percent) (Percent) (Percent) (Percent) 67 % 54 76 94 81 86 32 % 35 22 6 14 13 0% 1 0 0 0 0 0% 10 2 1 5 1 100 % 100 100 100 100 100 Source: Defendants' employee compensation data; Correlation Analysis Note: Distribution of growth in compensation correlation over titles with six or more years of data. Weighted by class-period employee years. Figure 5 Summary of Compensation Level Correlation Positive Sign Employer Negative Sign Not Significant Significant Not Significant Total (Percent) ADOBE APPLE GOOGLE INTEL INTUIT PIXAR Significant (Percent) (Percent) (Percent) (Percent) 92 % 78 83 85 45 84 5% 16 16 14 40 15 0% 1 0 0 2 0 3% 5 1 1 12 0 100 % 100 100 100 100 100 Source: Defendants' employee compensation data; Correlation Analysis Note: Distribution of log avg compensation correlation over titles with six or more years of data. Weighted by class-period employee years. Page 13 Supplemental Expert Report of Edward E. Leamer, Ph.D. 478 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page16 of 62 CONFIDENTIAL 5/10/2013 B. Title-by-Title Multiple Regressions 34. As described above, I also analyzed a multiple regression model of compensation that explains the year-by-year increases in average compensation at the title level in terms of four explanatory variables: (1) increases in average Technical Class compensation at the firm; (2) the previous year’s ratio of average Technical Class compensation at the firm divided by the average title compensation; (3) The previous year’s ratio of firm-wide average revenue divided by the average title compensation; (4) the percent change in software jobs in the San Jose MSA. 35. The data set is limited to eleven annual observations from 2001 to 2011, and many titles have fewer observations. A four-variable regression is a heavy burden with such data, which is reflected in the number of statistically insignificant coefficients. The statistically insignificant results are particularly prevalent for the external market effects and the revenue-sharing effects.5 The two sharing variables have more statistically significant coefficients. In other words, in the competition for statistical significance, it is sharing that wins. 36. I present in Figure 6 and Figure 7, below, class-wide results for titles with at least seven observations (approximately 30 percent of all Technical Class titles and more than 91 percent of their Class Period employee years). 37. Those results show the following. First, the vast majority of titles have a positive sharing effect in either the contemporaneous relationship or the lagged relationship. Second, of those that are negative a small fraction are statistically significant. Third, even these negative results occur in the context of body of evidence that there is a general relationship supported by sharing relationships for the vast majority of titles. Many of these are statistically significant. In sum, this analysis provides support for internal relationships across all Class titles at a This model is completely appropriate if the sharing force came from the class overall, equally across all titles. If on the other hand, title A were connected only to title B, then my attempt to link A to the class overall would yield a small and probably insignificant effect unless the variability in compensation of the class were largely determined by variability in compensation of title B. To put this in simple terms, the model that I am estimating makes it less likely not more likely to find a sharing effect. 5 Page 14 Supplemental Expert Report of Edward E. Leamer, Ph.D. 479 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page17 of 62 CONFIDENTIAL 5/10/2013 firm that would tend to make impact of the agreements common to all Class members. Thus, the vast majority of these titles have a positive internal equity sharing relationship with other Technical Class titles at the same firm. The implication of these results is to support my previous conclusion that the impact of the alleged non-compete agreements would be common across the class and common across the Technical Class employees in particular. Figure 6: Large Share of Contemporaneous Coefficients are Positive Contemporaneous Coefficient by Titles 100 80 Share (%) 38. 60 40 20 0 ADOBE APPLE GOOGLE Negative INTEL INTUIT PIXAR Positive Source: Defendant Employee Compensation Data; Regression Analysis Note: Distribution of estimated contemporaneous coefficient over titles with seven or more years of data. Weighted by class-period employee years Page 15 Supplemental Expert Report of Edward E. Leamer, Ph.D. 480 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page18 of 62 CONFIDENTIAL 5/10/2013 Figure 7: Large Share of Lagged Coefficients are Positive Lagged Coefficient by Titles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE INTEL Negative INTUIT PIXAR Positive Source: Defendant Employee Compensation Data; Regression Analysis Note: Distribution of estimated lagged coefficient over titles with seven or more years of data. Weighted by class-period employee years Figure 8 Summary of Contemporaneous and Lagged Net Effect Positive Sign Employer Negative Sign Not Significant Significant Not Significant Total (Percent) ADOBE APPLE GOOGLE INTEL INTUIT PIXAR Significant (Percent) (Percent) (Percent) (Percent) 22 % 23 12 88 73 60 75 % 62 69 11 23 39 0% 0 2 0 0 0 3% 14 17 1 4 0 100 % 100 100 100 100 100 Source: Defendants' employee compensation data; Regression Analysis Note: Distribution of the sum of estimated contemporaneous and lagged coefficients over titles with six or more years of data. Weighted by class-period employee years. Page 16 Supplemental Expert Report of Edward E. Leamer, Ph.D. 481 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page19 of 62 CONFIDENTIAL 5/10/2013 39. It may be important to understand that in principle there is a matrix of sharing relationships that connect titles directly affected by the conspiracy with other titles that are tied together with these affected titles. For example, with 101 Adobe titles in the class with six or more observations, this would require potentially the estimation of a 101 by 101 matrix of connections, which is far too many parameters to estimate with only eleven years of data. The regressions that I have estimated have a much simpler structure connecting each title not separately with all of the other titles but instead with the Adobe-wide variables.6 40. The regression results for Adobe titles with seven or more years of data are reported in Exhibit 1. The first two Sections give descriptive information about the data and the two correlations. These titles are sorted by the correlations of the log levels of average real compensation (Column 7). Column (9) which is the correlation between the percent change in average real compensation is more relevant here because this correlation is part of the estimated regression.7 The regression coefficients of the four variables are collected together in Section 3 and the corresponding t-statistics are reported to their right in Section 4. 41. Roughly, a t-statistic in excess of 2 in absolute value is said to produce “statistically significant” estimate by conventional standards. For that reason, tstatistics in excess of 2 are highlighted. Among the titles with eleven years of data it is the two sharing variables that jump out with high t-statistics, more often the “corrective” variable (Column 16) than the class-wide contemporaneous effect (Column 15). The external market variable (Column 18) has a t-value in excess of 2 only 4 of 41 titles, and the revenue variable (Column 17) has one negative and no positive significant t-stats. The results are more mixed deeper into the table as the number of observations diminishes. As I noted above, this model looks for a sharing force that comes from the class overall, equally across all titles. If on the other hand, title A were connected only to title B, then my attempt to link A to the class overall would yield a small and probably insignificant effect unless the variability in compensation of the class were largely determined by variability in compensation of title B. The model that I am estimating makes it less likely not more likely to find a sharing effect. 6 The increment in the fit of the model associated with the last three explanatory variables can be found by comparing the R-sq in the last column with the squared of the correlation. 7 Page 17 Supplemental Expert Report of Edward E. Leamer, Ph.D. 482 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page20 of 62 CONFIDENTIAL 42. V. 5/10/2013 This confirms the summary above, providing direct evidence of sharing across titles. The almost always positive coefficients on the “corrective” variable equal to the lagged ratio of compensation relative to title compensation in the title indicates that if the title compensation departs from its normal relationship with the class, then corrective action is taken to either raise or lower compensation in the title. Decile Based Correlations and Multiple Regressions 43. The title-based study just described by necessity excludes titles that are infrequently populated. To include these titles in this study, I have formed groups of titles on which to conduct the correlation analysis and the multiple regressions. I split each Defendant’s Technical Class titles into ten groups. To form the ten groups, I ranked titles on the basis of average (inflation-adjusted) total compensation over the lifetime of the title and then divided these up into deciles based on employee-years.8 A. Decile Based Correlation Analysis 44. The correlation analysis of the ten groups yields strong evidence of both short and long-run compensation structures for each subgroup of the Defendants’ Technical Class employees. Figure 9 and Figure 10 indicate the numbers of the ten groups that had positive correlations with the Technical Class: 10 out of 10 for the levels correlation and 10 out of 10 for the percent change correlations. Thus, every group shares in its firm’s compensation structure. Every group shows both immediate and long-run correlation structure for every group. This is consistent with and supports my conclusion that the Defendants’ compensation was semi-rigid. Since Lucasfilm did not provide title data, individuals were ranked in a similar fashion for Lucasfilm. Although I attempted to break the firms up into 10 equal sized groups (equal based on employee years), some groups end up being larger than others because of some big titles. 8 Page 18 Supplemental Expert Report of Edward E. Leamer, Ph.D. 483 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page21 of 62 CONFIDENTIAL 5/10/2013 Figure 9: Large Share of Change Correlations are Positive Compensation Change Correlation by Deciles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE INTEL Negative INTUIT LUCASFILM PIXAR Positive Source: Defendant Employee Compensation Data; Correlation Analysis Note: Distribution of growth in avg compensation correlation weighted by class-period employee years Figure 10: Large Share of Level Correlations are Positive Compensation Correlation by Deciles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE INTEL Negative INTUIT LUCASFILM PIXAR Positive Source: Defendant Employee Compensation Data; Correlation Analysis Note: Distribution of log avg compensation correlation weighted by class-period employee years Page 19 Supplemental Expert Report of Edward E. Leamer, Ph.D. 484 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page22 of 62 CONFIDENTIAL 5/10/2013 B. Decile Based Multiple Regression Results 45. Multiple regressions have also been estimated with these decile data. As summarized in Figure 11 and Figure 12, below, positive sharing effects—both contemporaneous and lagged—are the rule. Figure 11: Large Share of Contemporaneous Coefficients are Positive Contemporaneous Coefficient by Deciles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE INTEL Negative INTUIT LUCASFILM PIXAR Positive Source: Defendant Employee Compensation Data; Regression Analysis Note: Distribution of estimated contemporaneous coefficient weighted by class-period employee years Page 20 Supplemental Expert Report of Edward E. Leamer, Ph.D. 485 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page23 of 62 CONFIDENTIAL 5/10/2013 Figure 12: Large Share of Lagged Coefficients are Positive Lagged Coefficient by Deciles 100 Share (%) 80 60 40 20 0 ADOBE APPLE GOOGLE INTEL Negative INTUIT LUCASFILM PIXAR Positive Source: Defendant Employee Compensation Data; Regression Analysis Note: Distribution of estimated lagged coefficient weighted by class-period employee years 46. The almost always positive coefficients on the “corrective” variable in Figure 12 indicate that if the title compensation of a decile departs from its normal relationship with the class, then corrective action is taken to either raise or lower compensation in the decile. The cold-calling conspiracy that would have direct impact suppressing wages in some titles would have some effect on the classwide averages which in turn would suppress compensation in all or almost all of the titles in the class. 47. Figure 11 and Figure 12 contain a few instances of negative estimates. There are several important things to note. First, every group has a positive sharing effect in either the contemporaneous relationship or the lagged relationship. Second those that are negative are not statistically significant. Third, these occur in the context of evidence of positive sharing relationships for almost every group. Many of these are statistically significant. In sum, this analysis provides support for internal relationships across all these groups that would tend to make impact common to each. Page 21 Supplemental Expert Report of Edward E. Leamer, Ph.D. 486 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page24 of 62 CONFIDENTIAL 5/10/2013 48. 49. VI. Here I want to issue another warning about misinterpretation of negative coefficients. It is important to realize that these coefficients can be affected by the changing composition of the workforce within each title.9 For instance, adding a number of junior workers might bring down the title’s average compensation (or vice versa) for reasons unrelated to the question of whether workers share broadly in things such as the gains of the company and the impact of the unlawful agreements. Idiosyncratic variability of individual characteristics within a title is going to be a bigger problem for titles with just a few employees and for titles that experience large changes10 in their headcounts. Taking into account the limitations of these data, I find no compelling reason in this analysis to exclude any of the titles from the Technical Class. Additional Exploration of Adobe Correlations 50. To test this opinion I have closely examined the correlation outputs for the Adobe dataset as set forth below. They confirm my view. I have similarly examined the data of the other defendants, and find nothing in that data to contradict this conclusion. 1. Adobe Correlation Results 51. The numerical correlations reported in compare the movement of real compensation for each title in the Technical Class with the movement of the compensation of the Technical Class overall, but excluding the selected title. A high positive correlation means that compensation of a title moves in a way that is similar to compensation in the rest of the Technical Class, thus supporting the conclusion that the title and the class have “coordinated” compensation levels, a fact which is consistent with sharing of gains and broad impact of the anti-cold- I previously demonstrated with the Common Factors Analysis that compensation at the individual level in any year depends on the title but also depends on measured individual characteristics including age. This is statistical confirmation that at least some individual characteristics matter, and this raises the possibility that changes in the individual characteristics within a title can cause changes in title compensation that can mask the firm-wide common component. 9 10 Though a stable headcount can come from equal numbers of departures and new arrivals. Page 22 Supplemental Expert Report of Edward E. Leamer, Ph.D. 487 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page25 of 62 CONFIDENTIAL 5/10/2013 calling conspiracy whether it directly affects the title under study or the rest of the Technical Class. 52. Titles are included in the table if they are populated in 6 or more years. The correlations based on 5 or fewer observations are often statistically insignificant. The table is sorted first by the number of years the title was populated, from 11 to 6, and then by the correlation of the title with the Technical Class overall. Titles with the strongest statistical correlation with the Technical Class at Adobe are shaded in green. Titles with the weakest statistical correlation with the Technical Class at Adobe are shaded in yellow. 53. The first column of numbers in Exhibit 1 has the first year of data for each title. This is important since the early years from 2001 to 2003 had a sharp decline in Technical Class compensation for Adobe, as illustrated in Figure 13 and these early years thus are an important test bed for identifying which titles moved together. It would not be surprising to find statistically weaker results if these years are not included. Figure 13 Average Total Compensation ($) Adobe Technical Class Average Total Compensation Source: Defendant Employee Compensation Data Note: Inflation-adjusted average compensation with 2011 as base year Page 23 Supplemental Expert Report of Edward E. Leamer, Ph.D. 488 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page26 of 62 CONFIDENTIAL 5/10/2013 54. The second column reports the number of years during which the title was populated. This is also important since the statistical accuracy of the estimate of correlation depends on the number of observations. For that reason, I have truncated this table at the number of years equal to 6 or more since the cases with 5 or fewer years populated are estimated with greater statistical error. 55. The third column measures the number of employee-years. 2. Headcount Matters for Interpreting Correlations 56. It is my view that compensation is influenced by the title structure, but not fully determined by the title structure. Variables like age, experience, company tenure and personal characteristics are likely to have an impact on compensation, and consequently some of the change in compensation at the title level comes from changes in the distribution of employee characteristics as employees come and go. Titles that have just a few employees may have unusual employee characteristics, and titles that lose or gain a large fraction of employees may have variability in average compensation that is substantially influenced by variability of these characteristics, which masks a close connection with the Technical Class overall. 57. The Technical Class overall has experienced a rising headcount, as illustrated in Figure 14. Titles with movement in headcounts similar to the Technical Class may experience similar movements in employee characteristics, while titles that are losing workers or gaining workers much more rapidly than the Technical Class overall may have average compensation histories different from the Technical Class, not because there is no sharing, but because the group of employees in the title is changing enough to mask the sharing. Page 24 Supplemental Expert Report of Edward E. Leamer, Ph.D. 489 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page27 of 62 CONFIDENTIAL 5/10/2013 Figure 14 Adobe Technical Class Average Headcount per Title 40 Employees/Title 30 20 10 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Source: Defendant Employee Compensation Data 3. Correlations 58. As described above, there are two types of correlations which are relevant for determining if the movements of the two series are similar. The first column of correlations (Section 2) in Exhibit 1 compares the logarithm of average total real compensation in the title and the logarithm of average real total compensation of the rest of the Technical Class. The third column of Section 2 compares the change in the logarithm of average real total compensation of the title with the Technical Class (excluding the title). 59. The corresponding t-statistics for these correlations are reported immediately following each correlation and the statistically significant correlations with tstatistics greater than two are shaded. The table is sorted first by the number of years in which the title is populated and second by the correlation between the log levels. 60. The statistically most significant correlations with the shaded t-statistics come from the longest time series with all eleven years of data populated. That is a Page 25 Supplemental Expert Report of Edward E. Leamer, Ph.D. 490 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page28 of 62 CONFIDENTIAL 5/10/2013 feature of any statistical exercise – the longer is the time series the more statistically significant are the findings. 61. There are no negative correlations for the 41 titles with all eleven years populated. These positive correlations are statistically larger than zero (statistically significant) in 39 out of the 41 cases. 4. Outliers 62. To fully understand these correlations, and the significance (or not) of the anomalies, it may be helpful to look at some data displays. Figure 15 and Figure 16 have the average real compensation for ten Adobe titles and for the Adobe employees in the Technical Class overall. Figure 15 illustrates the five titles with eleven years of data that are most highly correlated with the Technical Class overall, and Figure 16 has the least correlated titles. All these titles move together. The title with the lowest correlation is TECHNICAL_WRITER_2 which is different, but not dramatically so. Page 26 Supplemental Expert Report of Edward E. Leamer, Ph.D. 491 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page29 of 62 CONFIDENTIAL 5/10/2013 Figure 15: Selected Adobe Titles with a Full 11 years of Data Average Total Compensation ($) Most Correlated Titles Average Total Compensation Source: Defendant Employee Compensation Data; Correlation Analysis Note: Titles with highest log compensation correlation among fully populated titles Inflation-adjusted average total compensation with 2011 as base year Figure 16 Average Total Compensation ($) Average Total Compensation ($) Least Correlated Titles Average Total Compensation Source: Defendant Employee Compensation Data; Correlation Analysis Note: Titles with highest log compensation correlation among fully populated titles Inflation-adjusted average total compensation with 2011 as base year Page 27 Supplemental Expert Report of Edward E. Leamer, Ph.D. 492 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page30 of 62 CONFIDENTIAL 63. 5/10/2013 However, as noted above, when headcounts change substantially, employee characteristics may change substantially too. The headcounts for the two titles with the lowest correlation are illustrated in Figure 17. The headcount for , is very volatile with a standard deviation of the percent change equal to 72 percent compared with the Technical Class benchmark of 11 percent. title is basically withering away, with an average annual percent increase of –12 percent compared with the Technical Class benchmark of +5 percent. Figure 17: Headcounts: Least Correlated Titles Least Correlated Titles Headcount 12 Title Headcount 10 8 6 4 2 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Source: Defendant Employee Compensation Data; Correlation Analysis Note: Titles with lowest log compensation correlation among fully populated titles 64. The variability in the headcounts for these two titles is not just a hypothetical problem. It has affected substantially the median ages for these titles which are contrasted with the median age of the Technical Class overall in Figure 18. In contrast to the smooth elevation of the median age of the class, the median age of has a big jump upward in 2006, and the median age of is highly volatile. These facts surely contribute to the apparent disconnect between compensation in these titles and compensation in the Technical Class overall. And, in any event, these results Page 28 Supplemental Expert Report of Edward E. Leamer, Ph.D. 493 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page31 of 62 CONFIDENTIAL 5/10/2013 offer no reason to question my conclusion that Adobe exhibits a somewhat rigid pay structure that applied to all of its salaried employees, including those in these titles. I offer these two examples simply to illustrate the point that the presence of a few outlier titles in the analyses does not challenge our basic conclusions about how these companies pay their employees, which are also supported by economic theory and the evidentiary. I have not seen any evidence, let alone convincing evidence, that any of these titles would not have been harmed by the anti-competitive behavior I have studied. Figure 18: Median ages: Least Correlated Titles Least Correlated Titles Median Age 45 Median Age 40 35 30 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Technical Class Source: Defendant Employee Compensation Data; Correlation Analysis Note: Titles with lowest log compensation correlation among fully populated titles VII. Internal Versus External Forces 65. The regression analysis reported above indicates that the internal sharing effects are generally more detectable than either revenue sharing or the external market forces. I expand on this finding in this section with an examination of the average real compensation for the Technical Class employees and the nonTechnical Class employees of each of the defendants. I show here that there is generally more correlation within firms between these two groups, than between Page 29 Supplemental Expert Report of Edward E. Leamer, Ph.D. 494 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page32 of 62 CONFIDENTIAL 5/10/2013 firms for either group. Thus again I observe that the internal sharing forces are very evident while the external market forces are more difficult to detect. 66. Figure 19 below illustrates for each defendant the average total compensation for the Technical Class employees (RD) and for the non-Technical Class employees (NRD). For most defendants these two subgroups have total compensation that closely tracks one another. It should also be evident that average total compensation is generally much more similar within each firm than between firms. In other words, the internal sharing forces dominate and keep the compensation of the Technical Class employees and the non-Technical Class employees closely aligned. 67. This visual observation is confirmed numerically by the computation of the correlations over time of the change in logarithms of the average total real compensation between these fourteen groups of employees, reported in Table 1. Correlations in excess of 0.9 are shaded. The boxes down the diagonal contain the within firm correlations between RD and NRD. Correlations outside these boxes refer to comparisons between firms. Four out of five of the shaded correlations are in these boxes, and in addition Google has an internal correlation of 0.86. Furthermore, the within firm correlation is the largest correlation in every row and column except for Lucasfilm. Lucasfilm has a very short time series with very little variability in the percent change in compensation, making it hard to estimate correlation . The Pixar data are contaminated by very large bonuses for producers and directors in 2002 and 2006. 68. Table 2 has the levels correlations that capture the longer term co-movements of the compensation series. These confirm the importance of the internal forces compared with the external forces. forces for all but Lucasfilm, in the sense that the within firm correlation is the largest correlation in every row and column except for Lucasfilm. Lucasfilm and Intel appear to move together only because the Lucasfilm data is confined to a brief period of stable growth of compensation at both firms. Page 30 Supplemental Expert Report of Edward E. Leamer, Ph.D. 495 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page33 of 62 CONFIDENTIAL 5/10/2013 Figure 19: Defendant RD vs. NRD Average Total Compensation Page 31 Supplemental Expert Report of Edward E. Leamer, Ph.D. 496 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page34 of 62 CONFIDENTIAL 5/10/2013 Table 1 Correlations of Changes in Defendants' Average Total Compensation 2001-2011 Adobe Apple Google Intel Intuit Lucasfilm Pixar Google Intel Intuit Lucasfilm Pixar NRD RD Adobe Apple NRD RD NRD RD NRD RD NRD RD NRD RD NRD RD NRD 1.00 0.94 0.66 0.56 0.17 -0.16 0.47 0.60 0.63 0.60 0.19 -0.62 -0.53 -0.53 RD 0.94 1.00 0.64 0.65 0.13 -0.24 0.34 0.45 0.53 0.51 -0.12 -0.67 -0.51 -0.37 NRD 0.66 0.64 1.00 0.93 0.48 0.17 0.02 0.16 0.85 0.73 -0.08 -0.87 -0.56 -0.16 RD 0.56 0.65 0.93 1.00 0.42 0.07 -0.12 0.00 0.77 0.63 -0.11 -0.83 -0.45 0.05 NRD 0.17 0.13 0.48 0.42 1.00 0.86 -0.51 -0.39 0.20 0.17 0.49 -0.89 -0.62 0.21 -0.16 -0.24 0.17 0.07 0.86 1.00 -0.53 -0.50 -0.09 -0.06 0.68 -0.83 -0.50 0.19 NRD 0.47 0.34 0.02 -0.12 -0.51 -0.53 1.00 0.97 0.31 0.30 -0.01 0.92 0.00 -0.89 RD 0.60 0.45 0.16 0.00 -0.39 -0.50 0.97 1.00 0.38 0.33 0.23 0.70 -0.03 -0.89 NRD 0.63 0.53 0.85 0.77 0.20 -0.09 0.31 0.38 1.00 0.91 -0.15 -0.17 -0.43 -0.28 RD 0.60 0.51 0.73 0.63 0.17 -0.06 0.30 0.33 0.91 1.00 -0.51 0.55 -0.63 -0.34 RD NRD 0.19 -0.12 -0.08 -0.11 0.49 0.68 -0.01 0.23 -0.15 -0.51 1.00 -0.24 0.03 -0.38 RD -0.62 -0.67 -0.87 -0.83 -0.89 -0.83 0.92 0.70 -0.17 0.55 -0.24 1.00 0.58 -0.29 NRD -0.53 -0.51 -0.56 -0.45 -0.62 -0.50 0.00 -0.03 -0.43 -0.63 0.03 0.58 1.00 0.29 RD -0.53 -0.37 -0.16 0.05 0.21 0.19 -0.89 -0.89 -0.28 -0.34 -0.38 -0.29 0.29 1.00 Note: Values above 0.9 shaded. Source: Defendants' employee compensation data. Page 32 Supplemental Expert Report of Edward E. Leamer, Ph.D. 497 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page35 of 62 CONFIDENTIAL 5/10/2013 Table 2 Correlations of Defendants' Average Total Compensation 2001-2011 Adobe NRD RD Adobe Apple Google Intel Intuit Lucasfilm Pixar Apple NRD RD Google NRD RD Intel NRD RD Intuit NRD RD Lucasfilm NRD RD Pixar NRD RD NRD 1.00 0.88 -0.17 -0.17 -0.43 -0.73 0.18 0.58 0.50 0.41 0.15 -0.04 -0.33 -0.38 RD 0.88 1.00 0.24 0.27 -0.05 -0.63 0.47 0.72 0.69 0.61 0.40 0.32 -0.48 -0.51 NRD -0.17 0.24 1.00 0.99 0.91 0.38 0.65 0.33 0.64 0.68 0.74 0.58 -0.48 -0.39 RD -0.17 0.27 0.99 1.00 0.90 0.33 0.69 0.37 0.64 0.66 0.83 0.72 -0.46 -0.40 NRD -0.43 -0.05 0.91 0.90 1.00 0.67 0.53 0.13 0.36 0.44 0.81 0.59 -0.46 -0.28 RD -0.73 -0.63 0.38 0.33 0.67 1.00 -0.05 -0.44 -0.20 -0.08 0.47 0.04 -0.22 0.12 NRD 0.18 0.47 0.65 0.69 0.53 -0.05 1.00 0.87 0.64 0.66 0.93 0.98 -0.54 -0.86 RD 0.58 0.72 0.33 0.37 0.13 -0.44 0.87 1.00 0.65 0.62 0.91 0.96 -0.48 -0.90 NRD 0.50 0.69 0.64 0.64 0.36 -0.20 0.64 0.65 1.00 0.94 0.63 0.54 -0.55 -0.54 RD 0.41 0.61 0.68 0.66 0.44 -0.08 0.66 0.62 0.94 1.00 0.78 0.91 -0.72 -0.62 NRD 0.15 0.40 0.74 0.83 0.81 0.47 0.93 0.91 0.63 0.78 1.00 0.88 -0.63 -0.83 RD -0.04 0.32 0.58 0.72 0.59 0.04 0.98 0.96 0.54 0.91 0.88 1.00 -0.62 -0.86 NRD -0.33 -0.48 -0.48 -0.46 -0.46 -0.22 -0.54 -0.48 -0.55 -0.72 -0.63 -0.62 1.00 0.65 RD -0.38 -0.51 -0.39 -0.40 -0.28 0.12 -0.86 -0.90 -0.54 -0.62 -0.83 -0.86 0.65 1.00 Note: Values above 0.9 shaded. Source: Defendants' employee compensation data. Page 33 Supplemental Expert Report of Edward E. Leamer, Ph.D. 498 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page36 of 62 499 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page37 of 62 Exhibit 1 500 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page38 of 62 Exhibit 1 Adobe Section 1 Job Title First Year (1) 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2002 2002 2002 2002 2001 2001 2004 2001 2001 2001 2001 2001 2004 2001 2004 Years of Data (2) Section 2 Total Emp-Years Avg Emp dlog Avg dlog Std Dev (3) (4) (5) (6) 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 10 10 10 10 9 9 8 8 8 8 8 8 8 8 8 170 311 371 29 82 108 96 250 559 93 14 152 202 550 234 273 327 434 196 353 309 94 2095 514 35 215 496 466 234 1441 302 222 975 2041 56 2064 100 1008 41 66 47 36 37 26 330 44 104 94 143 8 93 88 64 50 32 18 15 28 34 3 7 10 9 23 51 8 1 14 18 50 21 25 30 39 18 32 28 9 190 47 3 20 45 42 21 131 27 20 89 186 5 188 9 92 4 6 4 4 4 3 33 5 12 12 18 1 12 11 8 6 4 2 0.27 0.05 0.11 0.16 0.10 -0.03 0.12 0.04 0.11 0.11 0.00 0.28 0.06 0.06 0.07 0.17 0.11 0.07 0.13 -0.06 0.08 0.08 0.05 0.08 0.00 0.07 0.05 0.06 0.09 0.06 0.00 0.09 -0.12 0.05 0.03 0.05 0.09 0.06 0.00 -0.06 -0.12 0.10 0.08 0.00 0.20 -0.30 -0.21 0.30 -0.40 0.00 -0.28 -0.10 -0.43 0.14 0.20 0.00 0.34 0.19 0.16 0.65 0.25 0.40 0.37 0.16 0.20 0.26 0.45 0.15 0.25 0.18 0.22 0.19 0.14 0.18 0.24 0.19 0.23 0.27 0.13 0.22 0.32 0.53 0.20 0.11 0.33 0.19 0.21 0.15 0.23 0.20 0.54 0.08 0.31 0.27 0.59 0.72 0.30 0.40 0.43 0.48 0.29 0.50 0.48 0.91 1.08 0.00 1.28 1.44 0.54 0.33 0.81 0.61 Level Correlation Coeff T-Stat (7) (8) 0.90 0.89 0.89 0.87 0.85 0.84 0.84 0.84 0.83 0.81 0.80 0.78 0.78 0.78 0.78 0.77 0.74 0.74 0.74 0.73 0.71 0.71 0.70 0.70 0.69 0.69 0.67 0.67 0.67 0.65 0.64 0.63 0.63 0.61 0.61 0.61 0.60 0.59 0.58 0.51 0.09 0.80 0.14 -0.02 -0.13 0.52 0.30 0.84 0.70 0.62 0.56 0.38 0.31 0.28 0.15 -0.17 6.07 5.89 5.73 5.37 4.87 4.73 4.65 4.60 4.53 4.19 3.97 3.74 3.74 3.70 3.68 3.60 3.34 3.29 3.27 3.23 3.03 3.03 2.91 2.90 2.90 2.88 2.74 2.74 2.71 2.55 2.49 2.44 2.42 2.33 2.32 2.29 2.27 2.17 2.11 1.77 0.26 3.72 0.39 -0.06 -0.37 1.59 0.85 3.82 2.38 1.92 1.64 1.02 0.80 0.73 0.36 -0.41 1 of 2 Section 3 Change Correlation Coeff T-Stat (9) (10) 0.89 0.78 0.79 0.78 0.72 0.82 0.85 0.85 0.88 0.67 0.63 0.72 0.70 0.95 0.73 0.74 0.82 0.65 0.82 0.56 0.61 0.62 0.69 0.63 0.53 0.46 0.75 0.69 0.77 0.48 0.91 0.62 0.48 0.57 0.52 0.52 0.61 0.56 0.34 0.37 0.14 0.77 -0.59 0.14 0.08 0.46 0.37 0.63 0.68 -0.36 0.52 0.58 0.30 0.65 0.40 0.60 5.55 3.55 3.59 3.56 2.97 4.08 4.56 4.47 5.31 2.54 2.29 2.96 2.78 8.29 2.98 3.11 4.00 2.39 4.06 1.91 2.20 2.25 2.68 2.27 1.75 1.48 3.18 2.71 3.39 1.56 6.03 2.22 1.55 1.94 1.70 1.71 2.20 1.91 1.02 1.13 0.40 3.22 -1.93 0.37 0.22 1.28 0.99 1.80 2.05 -0.78 1.37 1.58 0.71 1.89 0.75 1.66 Section 4 Section 5 Section 6 Regression Coefficients Contemp Lagged Revenue SJ Emp (11) (12) (13) (14) Regression T-Stats Lagged Revenue (16) (17) Net Effect C+L T-Stat (19) (20) Obs. r2 (21) (22) Contemp (15) SJ Emp (18) 1.18 1.07 0.67 2.67 0.89 0.93 0.80 1.28 0.94 3.21 2.50 0.54 0.68 0.99 0.97 0.34 0.66 0.72 1.23 0.81 0.96 0.65 0.26 0.71 0.58 0.35 0.08 0.27 0.10 0.24 0.62 0.05 0.24 0.07 0.27 -0.07 1.92 0.36 0.41 -1.62 -1.20 1.91 0.12 3.38 -0.35 -0.47 -0.36 1.70 1.42 4.15 -0.50 0.41 1.40 1.28 1.04 1.18 1.33 1.08 1.09 0.88 0.59 0.97 0.80 0.89 0.06 0.65 1.24 0.15 1.14 1.32 0.40 1.09 0.57 1.43 1.13 1.02 0.49 0.97 1.09 1.26 0.47 0.62 0.27 0.71 0.10 0.45 0.49 0.43 1.04 0.44 0.91 0.56 1.61 -0.86 0.28 1.28 1.09 0.87 0.30 0.51 1.29 0.88 1.60 2.48 0.43 2.01 0.61 0.54 0.12 -0.09 -0.12 -0.33 -0.46 0.04 0.05 0.08 0.21 -0.24 0.51 0.13 0.21 0.06 0.12 0.23 0.11 0.21 0.09 0.17 0.06 0.11 0.12 0.08 0.15 -0.07 0.14 0.10 -0.17 0.11 -0.17 0.11 0.00 0.14 0.08 0.13 0.00 0.26 0.19 -0.57 -0.07 -0.39 0.06 0.35 0.13 0.04 0.16 -0.61 0.16 -0.14 -0.07 -0.02 0.34 0.27 0.02 -0.31 -0.34 -0.48 0.58 0.51 0.84 0.19 -0.04 -1.55 -0.17 0.54 0.34 0.43 0.29 0.33 0.19 0.30 0.02 0.44 0.24 0.58 0.35 0.45 -0.15 0.47 0.56 0.27 1.23 0.54 0.94 0.75 0.40 0.55 1.06 0.65 -3.12 0.29 -0.56 1.57 1.62 0.00 0.40 5.30 0.64 1.39 1.66 1.82 0.45 -0.81 1.14 2.16 -0.70 2.46 5.15 0.67 0.66 1.49 0.65 2.43 1.93 2.60 2.27 1.03 0.50 0.98 1.30 2.87 1.56 0.60 1.39 1.29 1.48 1.59 1.27 0.89 0.60 0.91 0.45 0.51 0.17 0.49 0.21 0.35 2.20 0.07 0.39 0.14 0.36 -0.14 1.44 0.57 0.42 -4.28 -1.61 1.54 0.19 1.21 -1.22 -0.42 -0.15 5.22 4.02 1.02 -0.33 0.60 0.63 4.87 6.71 1.38 1.95 1.80 1.99 3.32 2.68 3.59 2.28 0.75 0.04 1.60 4.27 0.54 2.19 2.67 1.12 2.84 1.38 4.09 2.23 2.65 1.35 2.30 2.12 3.49 1.29 1.62 1.12 1.51 0.67 1.04 1.05 1.04 2.96 1.13 1.96 1.18 2.35 -3.06 1.16 1.76 2.35 1.33 1.84 0.97 0.67 4.89 3.62 1.65 0.71 3.63 0.51 4.48 1.77 -0.25 -0.45 -0.80 -1.23 0.37 0.45 0.47 1.45 -0.30 0.40 0.89 1.40 0.47 0.43 1.59 0.74 1.33 0.29 1.21 0.24 0.49 0.88 0.29 0.47 -0.39 0.89 0.59 -1.01 0.58 -1.72 0.51 -0.01 0.80 0.39 0.82 0.00 1.41 0.55 -4.84 -0.33 -1.17 0.43 0.52 1.72 0.12 0.19 -6.25 1.15 -0.13 -0.13 -0.07 0.47 2.92 0.07 -0.25 -0.36 -0.32 0.39 1.38 1.89 0.37 -0.08 -0.62 -0.04 1.07 0.67 0.94 0.48 0.66 0.38 0.56 0.02 0.94 0.34 0.79 0.79 0.57 -0.09 0.69 0.91 0.48 2.21 0.89 2.57 0.95 0.71 1.04 1.55 1.29 -2.95 0.48 -0.42 5.82 2.25 0.00 0.73 1.81 1.89 1.19 0.56 3.47 0.85 -0.19 0.66 2.27 -0.28 5.63 2.22 2.25 2.01 3.75 1.97 1.81 1.38 2.25 1.74 4.10 2.57 1.18 1.91 1.14 2.11 1.66 1.06 1.82 1.80 2.23 2.09 1.68 0.75 1.68 1.67 1.61 0.56 0.89 0.38 0.94 0.72 0.50 0.73 0.50 1.30 0.37 2.83 0.91 2.01 -2.48 -0.92 3.19 1.20 4.25 -0.05 0.04 0.93 2.59 3.02 6.63 -0.07 2.42 2.01 1.82 8.15 1.66 1.99 2.24 1.39 3.34 2.66 3.83 3.24 1.49 0.56 1.43 3.24 2.66 2.22 2.77 1.67 2.39 1.87 3.21 1.95 1.74 1.25 1.66 1.05 1.88 0.87 1.33 0.63 0.98 2.18 0.52 0.86 0.67 1.43 0.52 2.36 1.09 1.37 -3.98 -1.12 2.50 1.25 1.45 -0.13 0.03 0.47 6.88 7.37 1.22 -0.05 3.81 1.01 6.05 1.10 0.66 0.04 2.14 1.76 3.36 0.15 2.00 1.76 2.76 501 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 9 9 9 8 8 7 7 6 7 7 7 7 0.98 0.74 0.81 0.79 0.77 0.94 0.95 0.93 0.92 0.63 0.57 0.81 0.92 0.94 0.82 0.86 0.78 0.84 0.78 0.87 0.73 0.83 0.72 0.77 0.81 0.82 0.83 0.71 0.87 0.61 0.95 0.70 0.42 0.62 0.83 0.66 0.86 0.62 0.71 0.91 0.61 0.78 0.76 0.96 0.83 0.71 0.51 0.98 0.98 0.90 0.60 0.93 0.50 0.99 7 0.91 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page39 of 62 Exhibit 1 Adobe Section 1 Job Title First Year (1) 2005 2001 2001 2001 2005 2005 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2006 2001 2001 2006 2006 2001 2001 2001 2006 2004 2001 2001 2002 2002 2006 Years of Data (2) Section 2 Total Emp-Years Avg Emp dlog Avg dlog Std Dev (3) (4) (5) (6) 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 22 42 88 17 93 59 46 25 19 87 13 89 108 20 16 33 22 23 35 57 10 24 21 92 68 13 27 8 15 26 7 18 105 27 19 15 12 15 19 6 15 11 115 11 24 3 6 13 2 13 8 8 4 3 15 2 15 18 3 3 6 4 4 6 10 2 4 4 15 11 2 5 1 3 4 1 3 18 5 3 3 2 3 3 1 3 2 19 2 4 0.18 -0.27 -0.41 0.00 0.00 0.05 0.14 0.36 -0.06 0.03 -0.28 0.11 0.01 0.00 -0.06 -0.08 0.03 0.22 0.09 0.06 0.22 -0.25 -0.36 0.19 0.00 0.00 0.42 0.00 -0.08 -0.04 -0.14 0.00 -0.04 0.14 -0.08 -0.14 0.22 -0.22 0.28 0.00 0.06 0.08 0.40 0.14 0.37 0.41 0.76 0.33 0.36 0.27 0.36 0.21 0.95 0.45 0.12 1.05 0.43 0.23 0.20 0.70 0.33 0.74 0.49 0.26 0.53 0.32 1.15 0.59 0.16 0.21 0.29 0.63 0.49 0.34 0.41 0.31 0.51 0.36 0.46 0.52 0.90 0.32 0.32 0.53 0.00 0.73 0.52 0.29 0.31 0.73 Level Correlation Coeff T-Stat (7) (8) 0.76 0.57 0.53 0.48 0.40 0.08 0.98 0.97 0.96 0.96 0.94 0.94 0.93 0.93 0.92 0.92 0.89 0.89 0.89 0.88 0.88 0.88 0.88 0.87 0.86 0.86 0.86 0.85 0.85 0.82 0.81 0.67 0.66 0.62 0.61 0.61 0.57 0.57 0.34 0.13 0.10 0.03 -0.03 -0.17 -0.45 2.64 1.56 1.38 1.21 0.98 0.18 10.31 8.18 7.28 6.72 5.50 5.29 5.23 5.11 4.77 4.62 3.99 3.90 3.87 3.77 3.74 3.70 3.66 3.60 3.44 3.43 3.38 3.28 3.18 2.84 2.81 1.79 1.74 1.57 1.55 1.54 1.39 1.38 0.72 0.26 0.20 0.05 -0.06 -0.34 -1.00 2 of 2 Section 3 Change Correlation Coeff T-Stat (9) (10) -0.15 0.39 0.38 0.93 0.97 0.52 0.90 0.86 0.93 0.83 0.94 0.82 0.74 0.78 0.58 0.66 0.94 0.67 0.91 0.47 0.50 0.83 0.49 0.78 0.66 0.59 0.74 0.93 0.27 0.76 0.85 0.43 0.68 0.61 0.54 -0.14 0.76 0.56 -0.21 0.28 0.62 0.16 -0.72 0.11 -0.93 -0.31 0.84 0.82 4.88 7.56 1.21 3.49 2.98 4.41 2.55 4.92 2.47 1.90 2.17 1.23 1.52 4.80 1.54 3.90 0.91 1.00 2.11 0.97 2.16 1.51 1.28 1.92 4.31 0.49 2.03 2.85 0.82 1.59 1.34 1.11 -0.24 2.05 1.17 -0.38 0.50 1.36 0.28 -1.47 0.20 -4.22 Section 4 Section 5 Section 6 Regression Coefficients Contemp Lagged Revenue SJ Emp (11) (12) (13) (14) Regression T-Stats Lagged Revenue (16) (17) Net Effect C+L T-Stat (19) (20) Obs. r2 (21) (22) 0.14 -3.13 -3.36 0.58 1.30 0.49 0.93 2.20 5.49 0.42 0.10 0.70 -0.38 -0.57 -1.61 -0.13 0.07 0.24 -0.36 3.68 7.47 0.77 0.02 -0.26 Contemp (15) 0.11 -2.63 -4.12 0.54 2.06 0.34 1.48 2.79 6.77 0.84 0.28 0.76 -0.68 -1.65 -4.51 -0.54 0.24 0.40 SJ Emp (18) -0.21 2.92 5.53 0.89 0.03 -0.13 1.07 -0.93 2.13 1.00 1.40 1.19 0.60 -1.11 10.60 0.71 1.76 0.61 502 6 6 6 6 6 6 0.91 0.93 1.00 0.95 0.94 0.73 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page40 of 62 Exhibit 2 503 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page41 of 62 Exhibit 2 Apple Section 1 Job Title Years of Data 11 11 11 11 11 11 11 11 11 11 11 10 10 10 10 9 8 8 8 8 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Total Emp-Years 294 501 229 169 352 189 428 156 118 686 58 82 184 110 66 116 44 35 19 52 13 71 193 626 184 2566 29 253 130 447 244 125 1364 54 236 475 1304 110 902 371 68 61 26 549 127 118 682 167 146 29 121 63 1363 16 Section 2 Level Correlation Coeff T-Stat 0.98 13.53 0.98 13.42 0.98 13.33 0.97 12.72 0.95 9.16 0.93 7.38 0.91 6.72 0.88 5.54 0.68 2.82 -0.49 -1.69 -0.50 -1.71 -0.67 -2.52 -0.81 -3.84 -0.81 -3.93 -0.89 -5.57 -0.85 -4.33 0.98 11.69 0.97 9.97 0.76 2.89 -0.82 -3.57 -0.96 -7.90 0.99 22.21 0.99 20.45 0.99 16.77 0.99 16.70 0.99 14.96 0.99 13.76 0.98 12.12 0.98 10.75 0.98 10.68 0.98 10.66 0.98 9.93 0.98 9.91 0.97 9.77 0.97 9.58 0.97 9.33 0.97 9.17 0.97 8.72 0.97 8.62 0.97 8.61 0.97 8.25 0.96 8.15 0.96 8.01 0.96 7.91 0.96 7.88 0.96 7.80 0.96 7.79 0.96 7.75 0.96 7.71 0.96 7.63 0.96 7.62 0.96 7.52 0.96 7.33 0.95 7.10 Change Correlation Coeff T-Stat 0.74 3.11 0.87 4.91 0.65 2.41 0.70 2.79 0.71 2.82 0.84 4.39 0.65 2.45 0.39 1.21 0.36 1.09 0.43 1.33 0.07 0.20 0.03 0.08 -0.25 -0.68 0.71 2.64 0.04 0.11 -0.55 -1.59 0.59 1.27 0.78 2.48 -0.62 -1.78 0.02 0.05 0.24 0.55 0.95 5.95 0.95 6.20 0.94 5.77 0.96 6.91 0.92 4.55 0.81 2.81 0.92 4.72 0.89 3.94 0.95 6.15 0.88 3.63 0.86 3.39 0.93 4.96 0.81 2.81 0.97 7.42 0.84 3.04 0.81 2.81 0.95 6.06 0.82 2.84 0.94 5.61 0.96 6.93 0.59 1.48 0.86 3.40 0.94 5.57 0.93 5.24 0.69 1.90 0.88 3.70 0.91 4.31 0.62 1.59 0.56 1.36 0.87 3.46 0.90 4.06 0.91 4.37 0.73 2.15 Section 3 Contemp 0.80 2.46 1.15 1.29 0.92 1.68 0.51 0.71 0.58 0.66 0.03 -0.38 -0.17 0.69 -0.14 -0.43 1.84 0.30 -0.16 0.14 0.09 0.54 1.49 1.41 1.16 0.88 0.24 0.76 -0.47 1.48 -0.18 0.99 0.85 1.59 0.99 0.55 0.66 1.93 0.83 0.64 1.64 0.73 3.03 1.06 2.07 1.62 1.09 1.32 0.74 1.70 -0.61 2.37 0.94 2.74 Regression Coefficients Lagged Revenue 0.04 0.34 1.09 -0.70 0.97 0.09 1.49 -0.57 -0.22 0.76 0.36 0.20 4.63 -2.48 0.25 0.28 0.17 -0.11 0.47 -0.15 -0.11 0.21 0.08 0.18 0.08 0.18 0.07 -0.04 -0.06 0.06 0.03 0.14 3.27 -2.40 0.21 1.02 0.16 0.02 0.08 -0.13 0.05 -0.03 -0.46 0.07 1.49 -0.41 1.40 -0.29 1.48 -0.31 0.60 0.16 -0.38 0.08 1.16 0.20 5.06 1.65 0.65 0.02 -4.02 1.70 1.14 0.05 0.41 0.34 2.35 -1.09 0.57 0.28 0.80 0.42 0.37 0.03 1.07 -0.23 0.68 0.49 -0.22 0.04 0.38 0.00 0.90 0.29 1.10 -0.85 -0.90 0.48 1.20 -0.26 1.95 -0.25 0.81 0.48 0.59 0.02 0.99 0.05 2.20 -0.62 5.97 -1.48 2.06 -0.91 0.75 0.28 8.01 -4.63 1 of 22 Section 4 SJ Emp -0.06 -0.67 -0.08 0.28 0.16 0.87 1.62 -0.62 -0.23 -0.49 -0.27 0.01 -0.91 -0.53 0.20 -0.95 1.69 -0.21 -0.78 -0.07 -0.22 0.06 0.82 0.07 0.23 -0.65 0.22 -0.64 -5.63 -0.45 -0.93 0.09 -1.08 2.20 -0.18 -1.16 -0.87 0.24 -1.09 -0.32 -0.12 -1.36 -1.59 -0.87 0.97 1.40 -0.70 0.75 -0.79 1.55 -0.02 2.63 -1.10 8.30 Contemp 1.64 5.33 2.58 2.17 1.56 1.81 0.53 0.95 0.86 0.68 0.05 -0.39 -0.20 2.98 -1.03 -1.37 1.13 -0.78 0.50 0.84 1.39 12.36 30.92 3.69 10.23 0.48 1.85 -0.64 2.89 -0.73 4.26 5.64 5.11 2.55 2.01 9.39 108.02 13.99 3.23 1.64 2.84 8.22 21.14 3.58 4.18 5.58 1.37 3.63 2.79 -1.34 16.54 1.79 9.55 Section 5 Regression T-Stats Lagged Revenue 0.05 0.81 1.71 -1.82 1.52 0.26 1.67 -1.00 -0.39 1.55 0.38 0.26 2.82 -2.28 0.38 0.40 0.31 -0.16 0.60 -0.18 -0.28 0.49 0.10 0.22 0.11 0.24 0.36 -0.18 -0.53 0.47 0.14 0.54 0.37 0.97 0.28 0.50 -0.22 3.86 4.57 0.99 3.85 -0.29 1.01 1.93 0.47 -3.21 3.10 1.91 4.37 1.16 1.71 3.50 31.38 9.36 -0.70 0.20 2.23 0.94 -4.50 1.36 3.14 2.55 0.39 3.13 2.35 5.40 8.37 0.89 7.14 3.49 0.13 -0.51 -0.27 0.15 -2.99 -3.71 -0.69 1.64 0.14 0.73 1.97 0.04 3.80 0.20 2.09 -4.08 0.76 1.67 0.50 -14.63 7.98 0.13 0.00 1.66 -1.26 9.58 -0.58 -0.85 2.39 0.03 0.34 -1.22 -4.59 -8.14 0.73 -6.76 SJ Emp -0.13 -1.18 -0.19 0.46 0.26 0.87 1.57 -0.67 -0.24 -0.40 -0.47 0.01 -0.81 -1.86 1.12 -1.36 -0.93 -1.91 -0.36 -0.69 0.04 1.89 0.27 0.27 -3.23 0.12 -0.66 -1.78 -0.35 -7.34 0.19 -2.89 2.80 -0.24 -1.34 -5.68 4.22 -7.66 -0.45 -0.08 -2.62 -0.56 -8.12 0.57 1.50 -1.62 0.46 -1.83 1.13 -0.04 4.46 -1.05 4.97 Section 6 Net Effect C+L T-Stat 0.84 0.76 3.56 4.85 2.12 2.15 2.78 2.20 0.71 0.72 2.04 1.39 5.14 2.93 0.96 0.77 0.75 0.70 1.13 0.73 -0.09 -0.11 -0.30 -0.19 -0.09 -0.07 0.76 2.06 -0.20 -0.92 -0.39 -0.79 0.50 0.00 0.22 0.14 0.08 2.98 2.82 2.64 1.48 -0.14 1.92 4.59 2.12 -4.20 2.14 1.26 3.94 1.56 1.35 1.03 3.00 1.52 0.42 2.03 1.63 4.13 0.16 3.27 3.57 1.90 1.92 1.72 3.91 5.36 4.43 1.69 10.75 0.73 -0.01 0.40 0.78 0.03 6.80 8.34 1.81 7.27 -0.08 1.84 2.36 1.64 -2.81 5.47 4.61 6.55 3.63 2.55 6.50 79.73 14.05 1.05 1.35 2.69 3.04 0.82 3.17 3.90 4.53 1.38 3.72 2.72 7.02 16.33 1.98 8.46 504 r2 0.71 0.92 0.73 0.72 0.78 0.82 0.82 0.29 0.16 0.52 0.10 0.34 0.40 0.75 0.36 0.83 0.99 0.86 0.57 0.51 0.94 1.00 1.00 0.97 0.99 0.80 0.95 0.97 0.96 1.00 0.98 0.99 0.98 0.97 0.95 0.99 1.00 1.00 0.96 0.93 0.95 0.99 1.00 0.97 0.97 0.98 0.91 0.96 0.94 0.99 1.00 0.94 0.99 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page42 of 62 Exhibit 2 Apple Section 1 Job Title Years of Data 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Total Emp-Years 17 127 142 63 45 98 70 182 2915 134 143 476 53 275 255 300 125 262 16 115 33 16 35 297 57 58 26 115 103 35 49 23 431 21 64 56 14 59 48 108 79 7 109 76 260 330 123 22 242 13 32 130 24 245 Section 2 Level Correlation Coeff T-Stat 0.95 7.08 0.95 6.94 0.95 6.80 0.95 6.73 0.95 6.73 0.95 6.52 0.94 6.46 0.94 6.42 0.94 6.33 0.94 6.30 0.94 6.27 0.94 6.23 0.94 6.18 0.94 6.09 0.93 5.78 0.93 5.69 0.93 5.69 0.93 5.65 0.93 5.63 0.93 5.58 0.93 5.56 0.93 5.55 0.93 5.46 0.92 5.42 0.92 5.39 0.92 5.35 0.92 5.30 0.92 5.30 0.92 5.23 0.92 5.21 0.92 5.14 0.92 5.12 0.91 5.03 0.91 4.94 0.91 4.93 0.91 4.86 0.91 4.86 0.91 4.83 0.90 4.69 0.90 4.67 0.90 4.60 0.90 4.59 0.90 4.56 0.90 4.54 0.89 4.48 0.89 4.48 0.89 4.46 0.89 4.45 0.89 4.45 0.89 4.43 0.89 4.41 0.89 4.34 0.89 4.34 0.89 4.30 Change Correlation Coeff T-Stat 0.71 2.01 0.52 1.21 0.83 2.99 0.69 1.92 0.99 12.42 0.84 3.11 0.88 3.72 0.96 7.04 0.60 1.52 0.66 1.76 0.48 1.10 0.91 4.31 0.79 2.54 0.70 1.97 0.74 2.21 0.38 0.82 0.79 2.56 0.51 1.18 0.72 2.10 0.27 0.57 0.55 1.31 0.47 1.06 0.68 1.85 0.84 3.04 0.72 2.05 0.78 2.48 0.67 1.80 0.64 1.68 0.35 0.74 0.59 1.45 0.67 1.79 0.89 3.94 -0.24 -0.50 0.54 1.30 0.33 0.71 0.93 4.90 -0.40 -0.86 0.88 3.68 -0.20 -0.42 0.18 0.37 0.58 1.43 0.85 3.17 0.66 1.75 0.66 1.76 0.98 9.92 0.84 3.12 0.46 1.04 0.84 3.09 0.21 0.42 0.60 1.50 0.94 5.69 0.94 5.72 0.57 1.38 0.68 1.88 Section 3 Contemp 1.88 0.56 -0.30 1.09 2.37 0.42 1.03 1.85 0.75 0.94 0.38 3.20 1.14 0.82 -0.07 0.33 0.64 0.99 1.20 0.71 1.06 2.57 0.43 0.57 0.69 0.81 2.23 0.86 0.71 0.67 1.20 1.50 -0.05 3.18 0.14 3.28 -0.07 1.77 0.20 0.56 2.25 1.51 0.62 0.71 1.92 -0.25 0.94 0.72 0.45 0.25 1.90 1.20 1.48 0.59 Regression Coefficients Lagged Revenue 6.66 -3.36 0.19 -0.28 3.49 -0.40 2.55 -0.84 -0.57 0.11 -0.03 0.15 3.36 0.26 0.66 -0.02 0.73 -0.18 1.02 -0.16 0.26 0.73 -2.66 -1.18 0.91 0.12 0.80 0.45 2.18 0.57 0.33 -0.09 1.88 0.06 1.54 -0.46 1.08 -0.14 0.94 0.29 1.69 -0.48 3.07 -1.01 0.40 0.43 1.74 0.21 0.70 0.36 0.46 0.29 2.43 -1.17 0.53 0.05 2.91 -1.10 4.66 -1.96 0.72 0.03 -0.38 0.73 0.05 0.05 3.81 -0.09 0.85 0.65 -0.05 -0.48 -0.01 -0.16 1.31 -0.18 0.71 0.09 0.99 -0.05 2.31 -0.76 0.38 0.42 -0.68 0.70 3.16 -0.98 -0.16 -0.02 1.86 0.99 1.07 -0.18 1.53 0.46 0.63 0.82 5.91 -2.76 0.50 0.31 -0.23 0.25 2.06 -0.58 0.07 0.68 2 of 22 Section 4 SJ Emp 7.09 1.66 -0.56 2.00 -0.28 -0.86 1.34 -0.43 -0.36 0.07 -1.64 5.55 0.64 -1.06 -1.09 -0.42 0.58 -0.24 0.10 -1.78 -0.89 2.89 -1.40 -0.65 -0.74 -0.50 -0.57 -1.73 -0.68 0.59 -2.50 -0.15 -0.41 4.43 -1.56 -3.16 0.43 0.90 -0.37 -1.00 1.25 -1.42 1.44 -1.60 0.42 -1.48 -1.32 1.41 -1.10 -2.58 0.22 -0.86 -0.57 -1.60 Contemp 7.10 15.61 -0.28 2.49 3.89 2.29 1.02 20.57 3.05 8.01 0.87 2.00 3.07 2.39 -0.15 1.51 5.01 4.29 2.30 0.41 11.73 2.51 0.92 0.73 2.04 3.21 5.76 81.85 1.67 1.56 2.41 3.16 -0.10 4.28 2.39 26.16 -1.14 13.53 102.47 0.88 35.83 5.15 0.91 1.07 2.63 -0.16 15.21 6.32 0.56 0.21 4.09 2.24 7.04 0.97 Regression T-Stats Lagged Revenue 9.22 -8.26 2.26 -7.87 2.08 -0.91 4.60 -2.54 -0.73 0.43 -0.16 0.60 0.65 0.33 4.80 -0.28 2.18 -0.96 7.07 -1.52 0.46 1.94 -1.31 -1.16 1.95 0.41 1.55 1.68 4.59 2.06 1.22 -0.67 16.56 0.79 4.47 -2.58 1.36 -0.24 0.33 0.52 10.86 -6.30 2.15 -1.27 0.30 0.85 2.15 0.46 2.46 0.95 2.06 0.77 2.33 -1.86 34.93 6.57 3.08 -2.22 5.68 -4.15 0.57 0.03 -0.60 1.79 0.09 0.19 3.52 -0.31 11.13 11.42 -0.30 -13.49 -0.23 -1.50 9.61 -1.45 285.17 64.33 1.11 -0.11 27.91 -13.71 0.96 1.67 -0.52 1.31 2.06 -1.27 -0.31 -0.05 1.60 0.94 13.64 -4.06 24.02 5.39 0.71 0.44 0.98 -0.82 1.22 0.98 -0.34 0.58 7.13 -3.42 0.11 0.86 Section 5 SJ Emp 6.61 16.05 -0.41 2.18 -0.38 -1.47 0.29 -1.92 -0.70 0.25 -1.39 1.44 0.78 -1.39 -1.39 -1.12 2.97 -0.49 0.08 -1.46 -4.69 1.18 -1.10 -0.55 -0.86 -0.78 -0.37 -83.66 -0.72 0.64 -1.91 -0.15 -0.45 2.38 -6.65 -7.06 1.66 2.78 -73.80 -0.78 7.62 -2.03 0.68 -1.10 0.39 -0.80 -10.29 10.38 -0.28 -0.84 0.24 -0.74 -1.13 -1.01 Section 6 Net Effect C+L T-Stat 8.54 10.88 0.75 7.07 3.19 2.94 3.64 5.17 1.80 3.15 0.39 1.18 4.39 1.02 2.51 19.20 1.48 2.83 1.97 9.04 0.64 0.68 0.53 0.75 2.05 3.12 1.62 2.24 2.11 4.69 0.66 1.43 2.52 18.16 2.53 5.03 2.28 2.10 1.65 0.36 2.75 12.46 5.64 2.42 0.83 0.53 2.30 2.76 1.39 2.85 1.28 3.10 4.66 3.32 1.39 58.99 3.62 3.03 5.33 5.82 1.92 1.15 1.12 1.44 0.01 0.01 6.99 3.91 0.99 9.56 3.23 35.05 -0.08 -0.84 3.09 24.05 0.91 225.62 1.55 1.10 4.56 34.64 1.89 3.45 -0.06 -0.05 3.87 2.30 1.77 2.70 1.61 1.45 2.01 15.88 2.25 20.45 1.08 0.73 6.17 1.04 2.40 3.79 0.97 1.38 3.55 8.33 0.65 0.59 505 r2 1.00 1.00 0.95 0.98 0.98 0.93 0.95 1.00 0.92 0.99 0.84 0.96 0.98 0.97 0.98 0.82 1.00 0.97 0.97 0.76 1.00 0.92 0.92 0.95 0.94 0.94 1.00 1.00 0.94 0.99 0.98 0.98 0.23 0.96 1.00 1.00 0.79 1.00 1.00 0.64 1.00 0.99 0.92 0.94 0.97 0.92 1.00 1.00 0.46 0.81 0.99 0.95 0.99 0.75 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page43 of 62 Exhibit 2 Apple Section 1 Job Title Years of Data 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Total Emp-Years 37 34 8 103 7 8 28 61 25 7 501 74 192 11 116 239 10 44 21 17 563 12 57 145 33 131 267 47 60 8 50 57 20 20 40 144 23 72 47 19 49 29 23 332 109 18 15 11 103 38 96 103 135 14 Section 2 Level Correlation Coeff T-Stat 0.88 4.25 0.88 4.25 0.88 4.20 0.88 4.17 0.88 4.15 0.88 4.11 0.88 4.08 0.88 4.08 0.87 4.01 0.87 3.98 0.87 3.94 0.87 3.94 0.87 3.93 0.87 3.91 0.87 3.89 0.87 3.89 0.86 3.83 0.86 3.78 0.86 3.69 0.85 3.65 0.85 3.60 0.85 3.58 0.85 3.58 0.85 3.57 0.85 3.55 0.85 3.55 0.84 3.52 0.84 3.43 0.84 3.42 0.84 3.40 0.83 3.35 0.83 3.34 0.83 3.33 0.83 3.32 0.82 3.24 0.82 3.24 0.82 3.21 0.82 3.17 0.81 3.07 0.80 3.03 0.80 3.01 0.80 3.01 0.80 3.01 0.78 2.78 0.77 2.74 0.77 2.68 0.76 2.65 0.74 2.49 0.74 2.48 0.74 2.45 0.73 2.40 0.73 2.39 0.72 2.34 0.72 2.32 Change Correlation Coeff T-Stat -0.04 -0.07 0.15 0.30 0.89 3.94 0.40 0.87 0.72 2.05 -0.04 -0.09 0.45 1.02 0.26 0.55 0.59 1.45 0.26 0.53 0.85 3.21 0.61 1.53 -0.50 -1.16 0.49 1.14 0.21 0.43 0.89 3.90 0.54 1.30 0.52 1.22 0.69 1.91 0.68 1.84 0.92 4.56 0.06 0.12 0.46 1.03 0.90 4.16 0.04 0.07 0.76 2.36 -0.16 -0.32 0.29 0.60 0.52 1.21 -0.06 -0.12 0.61 1.56 0.11 0.22 0.35 0.75 -0.38 -0.83 0.94 5.74 0.91 4.27 0.55 1.31 -0.01 -0.02 0.71 2.01 0.04 0.08 0.92 4.70 0.94 5.36 -0.58 -1.42 0.90 4.05 0.59 1.45 0.66 1.76 0.89 3.97 -0.72 -2.05 0.30 0.62 0.27 0.57 0.54 1.29 -0.04 -0.08 0.07 0.14 0.74 2.23 Section 3 Contemp 0.57 1.13 1.47 0.34 0.53 0.44 0.07 1.31 0.28 1.98 3.43 0.61 -0.27 -0.28 6.50 0.95 -4.35 -0.32 0.77 1.99 1.94 0.12 -0.26 1.96 0.55 0.54 0.22 0.83 0.83 0.13 0.65 0.25 0.24 -0.34 1.96 1.43 -1.37 -0.59 1.22 2.69 1.73 2.26 -0.22 1.12 0.35 -0.37 1.36 -0.09 0.49 1.08 1.10 0.34 -0.09 -2.58 Regression Coefficients Lagged Revenue 0.88 -0.53 2.90 -1.26 -0.70 0.91 0.62 0.43 0.22 -0.32 1.15 0.14 3.01 -0.73 2.69 -1.24 3.71 -1.43 2.62 -1.42 -3.62 -0.07 1.04 0.29 0.05 0.31 2.39 -0.62 7.89 -2.48 -0.13 0.56 6.24 -1.52 -0.27 0.00 -0.40 0.84 1.43 -0.04 -0.26 -0.17 0.13 -0.26 1.45 0.06 -0.40 -0.23 0.93 0.28 0.17 0.73 0.30 1.27 1.09 0.45 0.25 -0.30 3.20 -1.30 0.05 0.93 0.75 0.33 0.46 0.59 1.47 -0.20 -0.82 0.43 -0.33 0.57 -5.78 2.74 -0.65 -1.04 0.50 0.87 4.63 -3.04 0.34 0.58 0.64 -0.32 0.76 0.03 0.36 0.31 -0.21 0.95 1.16 0.51 0.10 0.69 1.42 -0.90 0.98 0.23 3.23 -1.67 0.25 1.33 0.64 0.29 0.65 0.91 0.95 3.21 3 of 22 Section 4 SJ Emp 0.36 0.78 -1.65 -0.72 -0.27 -0.78 -2.35 -1.51 -0.39 5.06 5.76 -1.97 -0.87 -0.66 6.52 -0.89 -7.36 0.96 1.36 -0.81 0.60 -0.46 1.52 2.66 -2.78 -1.81 -2.14 1.22 -0.36 -2.42 -1.56 -0.60 1.46 -0.34 0.51 -0.59 -18.75 2.39 -1.01 0.25 -0.22 -0.27 0.23 -0.44 -2.33 1.22 -1.38 1.22 -1.43 0.78 -1.24 -2.45 -0.28 19.13 Contemp 1.77 2.87 9.23 1.28 3.42 0.71 0.56 3.08 8.63 1.68 2.07 1.40 -0.23 -0.16 2.32 1.43 -0.67 -0.20 0.94 2.93 0.89 0.51 -0.14 15.41 0.76 1.90 0.14 1.10 0.54 0.36 4.31 0.87 0.59 -2.79 3.60 1.18 -0.55 -0.45 2.88 9.26 2.31 10.93 -0.21 4.74 0.61 -0.10 1.23 -0.09 1.27 1.70 2.47 2.71 -0.15 -0.23 Regression T-Stats Lagged Revenue 2.44 -2.49 5.65 -3.68 -2.78 5.87 1.65 1.75 1.74 -1.18 1.55 0.31 12.67 -6.31 3.00 -2.32 82.49 -54.77 2.14 -1.30 -1.57 -0.14 2.07 0.84 0.04 0.66 0.99 -0.48 2.22 -1.95 -0.16 1.08 0.87 -0.63 -0.17 0.00 -0.44 1.35 1.69 -0.07 -0.17 -0.12 0.68 -1.37 1.18 0.06 -5.76 -2.47 0.91 0.66 0.72 2.37 0.19 0.35 1.76 0.48 0.17 -0.26 3.70 -2.62 0.32 7.83 2.96 1.13 1.17 1.77 7.80 -1.91 -1.74 1.46 -0.30 0.81 -1.16 1.17 -0.50 -0.46 1.31 2.57 12.60 -10.11 0.68 1.06 8.05 -1.48 0.66 0.05 2.55 0.95 -0.28 2.19 0.75 0.29 0.13 0.90 1.62 -1.38 2.94 0.68 5.32 -3.32 0.67 3.13 5.28 3.23 1.69 1.26 0.38 0.42 Section 5 SJ Emp 0.57 0.93 -4.83 -1.23 -0.56 -0.53 -6.82 -2.70 -6.26 1.91 1.48 -1.88 -0.51 -0.16 1.50 -0.59 -0.57 0.74 0.74 -0.45 0.17 -0.74 0.40 9.44 -3.50 -2.35 -0.20 0.69 -0.29 -2.29 -4.65 -0.67 1.65 -1.02 0.51 -0.26 -1.69 0.44 -1.08 0.44 -0.16 -1.13 0.10 -0.89 -1.70 0.23 -0.68 0.68 -1.50 0.56 -1.27 -9.15 -0.14 1.02 Section 6 Net Effect C+L T-Stat 1.45 2.29 4.03 5.04 0.78 2.62 0.96 1.71 0.75 3.01 1.58 1.29 3.09 11.64 4.00 3.06 3.99 78.44 4.61 2.14 -0.19 -0.18 1.64 2.22 -0.22 -0.10 2.11 0.87 14.39 2.27 0.82 0.81 1.89 0.66 -0.59 -0.21 0.37 0.30 3.42 2.63 1.68 1.12 0.25 0.65 1.19 0.60 1.55 13.27 1.48 0.86 0.71 1.63 0.51 0.17 1.91 1.62 1.09 0.41 3.33 3.00 0.70 2.62 1.00 2.18 0.70 1.04 1.14 3.94 1.14 2.01 1.11 0.79 -7.16 -0.96 -1.24 -0.49 1.72 2.53 7.32 11.71 2.08 2.10 2.90 13.34 0.54 0.26 1.48 4.45 0.13 0.12 0.79 0.20 1.47 1.02 1.33 0.76 1.47 2.39 4.31 4.19 1.35 1.85 0.99 4.33 0.56 0.68 -1.62 -0.12 506 r2 0.89 0.98 1.00 0.99 0.94 0.81 1.00 0.99 1.00 0.98 0.94 0.93 0.51 0.81 0.94 0.90 0.80 0.54 0.95 0.97 0.84 0.79 0.89 1.00 0.95 0.96 0.51 0.85 0.36 0.97 1.00 0.95 0.99 1.00 0.98 0.89 0.99 0.22 0.98 1.00 0.97 1.00 0.76 0.99 0.92 0.84 0.92 0.87 0.95 0.98 0.96 0.99 0.95 0.91 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page44 of 62 Exhibit 2 Apple Section 1 Job Title Years of Data 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Total Emp-Years 26 25 38 18 58 26 13 51 14 57 11 24 127 45 36 52 137 18 13 59 16 34 35 41 46 15 646 14 47 27 17 13 63 85 60 19 10 69 36 18 918 127 25 16 13 181 66 71 7 33 55 133 10 116 Section 2 Level Correlation Coeff T-Stat 0.70 2.22 0.70 2.20 0.70 2.20 0.66 1.95 0.66 1.95 0.65 1.90 0.65 1.90 0.64 1.88 0.64 1.87 0.64 1.86 0.63 1.82 0.63 1.80 0.62 1.79 0.62 1.79 0.58 1.58 0.57 1.57 0.56 1.51 0.55 1.49 0.55 1.48 0.55 1.46 0.54 1.45 0.54 1.42 0.53 1.39 0.53 1.38 0.52 1.36 0.52 1.35 0.52 1.35 0.51 1.33 0.51 1.31 0.50 1.30 0.49 1.25 0.49 1.24 0.47 1.20 0.47 1.18 0.45 1.11 0.44 1.10 0.44 1.08 0.42 1.04 0.42 1.03 0.41 1.01 0.41 1.00 0.39 0.96 0.38 0.93 0.38 0.93 0.38 0.91 0.37 0.90 0.37 0.88 0.36 0.86 0.34 0.80 0.32 0.76 0.31 0.73 0.29 0.68 0.26 0.61 0.09 0.20 Change Correlation Coeff T-Stat 0.23 0.48 0.68 1.86 0.79 2.56 0.11 0.22 0.07 0.15 0.43 0.95 0.51 1.18 0.23 0.47 0.38 0.82 -0.03 -0.05 0.45 1.01 0.57 1.40 0.04 0.08 0.82 2.90 0.86 3.38 0.56 1.34 0.25 0.51 0.33 0.69 0.52 1.23 0.06 0.12 0.47 1.07 0.41 0.90 0.50 1.17 0.52 1.21 0.33 0.69 0.73 2.16 0.00 0.00 -0.20 -0.41 0.96 6.64 -0.11 -0.23 0.19 0.38 -0.72 -2.07 -0.14 -0.29 0.43 0.96 -0.74 -2.18 -0.46 -1.03 -0.78 -2.50 -0.10 -0.20 -0.34 -0.73 -0.78 -2.47 0.53 1.24 0.22 0.46 -0.74 -2.21 0.36 0.78 0.88 3.65 0.11 0.22 0.37 0.81 -0.17 -0.34 0.37 0.79 -0.86 -3.42 0.08 0.16 -0.14 -0.28 0.40 0.87 0.41 0.89 Section 3 Contemp -0.23 0.94 9.17 2.32 -0.76 1.80 -1.56 1.80 0.56 -0.09 1.68 -0.12 2.05 1.18 3.09 0.91 0.93 -0.11 0.42 0.37 3.59 0.50 0.35 0.82 1.08 0.40 -0.17 0.55 1.90 -1.00 0.61 -2.54 -0.42 0.01 -0.54 0.96 -5.10 -0.58 -0.26 -0.78 0.12 1.37 -0.57 0.25 0.55 1.10 -2.58 -2.34 -0.05 -2.38 0.42 -3.16 -1.11 0.90 Regression Coefficients Lagged Revenue -0.43 0.86 0.69 0.33 2.35 -7.19 2.16 -0.46 0.61 1.32 1.36 -0.95 2.39 -0.40 1.79 -0.28 0.52 0.89 0.08 1.16 1.26 -0.17 -7.51 4.87 1.96 4.08 0.46 0.62 0.55 -1.14 -0.24 2.01 0.88 -0.89 -0.48 2.73 -1.07 2.09 0.17 0.75 2.10 0.38 -0.48 1.73 -0.64 1.85 0.14 0.66 1.05 -0.12 0.56 0.89 -0.16 -0.08 0.31 1.05 -0.37 0.00 1.69 0.29 0.30 1.50 2.26 -1.08 0.43 1.07 -0.28 1.09 -0.10 0.20 1.03 1.13 0.41 -0.38 -2.48 1.20 0.23 -0.76 0.43 0.76 -0.15 -0.03 -0.53 2.19 0.13 0.23 -0.84 2.33 -0.32 0.73 0.88 1.18 -4.59 3.42 -1.29 1.86 -1.04 1.86 0.60 -0.17 -0.13 1.60 0.80 2.56 -1.81 3.41 0.57 -0.01 4 of 22 Section 4 SJ Emp -0.85 -3.50 -19.15 7.71 -2.62 0.78 6.21 0.82 -4.00 -3.51 -1.18 -14.39 -9.17 0.77 3.47 5.19 -1.03 -0.70 -2.76 -5.12 3.17 -2.69 -0.64 -1.97 0.61 -2.38 -0.05 0.73 0.63 -2.35 -1.86 0.56 -1.20 0.67 0.50 -5.03 7.95 12.14 0.15 -2.52 -1.01 -1.56 0.63 -2.61 -1.04 -2.46 0.76 2.49 -5.93 0.62 -2.53 -15.71 4.00 -0.97 Contemp -15.24 0.89 1.03 1.39 -1.44 1.91 -0.64 1.11 1.07 -2.94 3.40 -0.13 7.13 1.08 0.92 0.41 2.28 -0.25 0.47 0.25 2.25 1.25 0.37 1.45 6.60 0.20 -2.19 0.34 3.25 -5.14 1.24 -0.86 -0.49 0.01 -1.72 2.16 -0.71 -0.30 -1.39 -0.18 3.62 1.97 -0.87 0.53 1.59 0.60 -1.62 -0.88 -0.34 -0.64 0.67 -10.86 -0.22 1.77 Regression T-Stats Lagged Revenue -28.90 49.37 0.45 0.39 2.58 -0.73 1.67 -0.35 1.90 2.40 1.85 -0.84 1.99 -0.29 1.29 -0.21 1.02 2.18 2.71 47.78 3.03 -0.42 -2.03 2.22 7.37 9.16 0.92 0.50 0.56 -0.39 -0.17 1.13 2.86 -1.87 -1.33 3.40 -1.46 3.04 0.10 0.87 1.44 0.44 -1.52 5.22 -0.92 2.26 0.32 0.93 8.54 -0.68 0.51 0.62 -2.67 -0.66 0.25 0.34 -1.24 0.00 10.67 1.89 0.79 3.44 0.91 -0.51 0.68 1.03 -0.41 0.72 -0.44 0.46 3.27 4.56 0.11 -0.12 -0.89 1.11 1.93 -2.82 0.16 0.64 -5.88 -0.58 -1.00 3.99 0.31 0.29 -2.31 5.52 -1.27 1.52 0.62 0.54 -1.77 1.94 -0.51 1.11 -8.33 18.36 0.27 -0.09 -0.27 2.48 4.11 10.87 -0.52 0.90 1.37 -0.02 Section 5 SJ Emp -12.29 -1.53 -0.53 1.99 -1.36 0.32 1.79 0.21 -3.39 -40.82 -1.01 -3.54 -8.99 0.58 0.63 1.29 -1.16 -0.55 -1.39 -2.95 0.55 -2.97 -0.30 -1.55 1.70 -0.68 -0.17 0.15 0.50 -4.56 -1.64 0.10 -0.38 0.15 0.35 -5.89 0.81 0.64 0.32 -0.31 -9.93 -1.05 0.30 -2.38 -1.00 -0.65 0.77 0.14 -20.13 0.11 -1.65 -9.37 0.41 -0.80 Section 6 Net Effect C+L T-Stat -0.66 -25.59 1.62 0.82 11.52 1.20 4.48 1.69 -0.14 -0.20 3.16 2.12 0.83 0.26 3.59 1.32 1.08 1.20 -0.01 -0.26 2.93 3.65 -7.63 -1.69 4.01 7.51 1.64 1.07 3.64 0.88 0.67 0.21 1.81 2.82 -0.59 -0.78 -0.65 -0.46 0.54 0.18 5.69 1.95 0.01 0.02 -0.30 -0.20 0.96 1.08 2.13 8.30 0.96 0.38 -0.33 -2.68 0.86 0.37 1.53 2.14 0.69 2.25 0.91 1.17 -0.28 -0.06 0.01 0.01 -0.27 -0.14 -0.64 -1.31 1.98 2.79 -4.69 -0.46 -3.06 -1.33 -0.03 -0.10 -0.36 -0.05 -0.03 -0.56 0.84 0.77 -0.43 -0.46 -0.59 -0.80 0.23 0.42 1.98 0.67 -7.17 -1.79 -3.63 -1.08 -1.09 -4.77 -1.78 -0.32 0.29 0.29 -2.36 -6.72 -2.92 -0.38 1.46 1.77 507 r2 1.00 0.88 0.97 0.93 0.97 0.83 0.97 0.74 0.97 1.00 0.97 0.99 0.99 0.97 0.87 0.91 0.94 0.98 0.97 0.93 0.93 0.98 0.94 0.86 1.00 0.84 0.95 0.55 0.97 1.00 0.98 0.95 0.91 0.90 0.88 1.00 0.79 0.87 0.94 0.81 1.00 0.98 0.85 0.99 0.93 0.52 0.85 0.86 1.00 0.79 0.94 1.00 0.89 0.89 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page45 of 62 Exhibit 2 Apple Section 1 Job Title Years of Data 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Total Emp-Years 29 117 26 22 31 11 46 52 50 49 166 36 21 59 40 16 19 54 48 44 20 73 19 6 15 24 6 57 8 10 6 6 8 11 19 12 19 18 166 16 57 13 39 18 8 10 28 12 24 114 22 6 90 87 Section 2 Level Correlation Coeff T-Stat 0.08 0.18 0.04 0.08 -0.04 -0.08 -0.04 -0.10 -0.07 -0.16 -0.27 -0.63 -0.28 -0.66 -0.36 -0.87 -0.43 -1.06 -0.48 -1.23 -0.49 -1.25 -0.50 -1.29 -0.54 -1.42 -0.62 -1.79 -0.65 -1.92 0.98 9.32 0.96 7.34 0.96 7.16 0.93 4.91 0.87 3.58 0.87 3.48 0.85 3.24 0.77 2.41 0.76 2.35 0.76 2.31 0.75 2.27 0.75 2.26 0.73 2.13 0.72 2.05 0.71 2.04 0.67 1.81 0.63 1.61 0.63 1.61 0.60 1.49 0.59 1.45 0.48 1.08 0.47 1.07 0.42 0.93 0.42 0.92 0.41 0.89 0.38 0.82 0.36 0.78 0.34 0.73 0.27 0.55 0.27 0.55 0.13 0.27 0.13 0.27 0.11 0.22 0.08 0.17 0.08 0.16 0.04 0.08 0.04 0.07 -0.01 -0.02 -0.11 -0.23 Change Correlation Coeff T-Stat 0.33 0.70 0.26 0.55 0.21 0.43 0.17 0.34 0.29 0.62 0.23 0.48 0.02 0.03 0.37 0.79 -0.96 -6.86 0.27 0.57 -0.44 -0.97 0.05 0.10 0.80 2.66 0.31 0.65 0.35 0.74 0.93 4.31 0.85 2.85 0.89 3.46 0.94 4.62 0.64 1.18 0.45 0.72 -0.41 -0.78 0.51 1.03 -0.46 -0.91 0.90 3.49 0.08 0.12 0.53 1.07 -0.47 -0.92 0.36 0.55 0.55 1.14 0.59 1.26 0.81 1.95 0.82 2.00 0.83 2.59 0.05 0.08 -0.06 -0.09 0.04 0.07 -0.61 -1.09 -0.55 -1.14 0.60 1.07 -0.32 -0.58 -0.14 -0.24 0.87 3.11 -0.84 -2.21 0.78 1.77 0.10 0.14 0.83 2.58 -0.61 -1.10 0.12 0.22 0.94 4.93 0.58 1.22 0.90 3.64 0.26 0.47 -0.44 -0.84 Section 3 Contemp 0.04 -0.56 -0.76 4.02 -0.47 0.75 2.17 1.19 -0.30 -0.03 -0.12 1.28 1.42 0.43 0.75 Regression Coefficients Lagged Revenue 0.09 1.00 1.36 -6.15 0.43 1.14 1.91 -5.35 -1.28 2.00 0.14 0.01 -1.69 6.68 0.84 -0.81 0.06 -0.07 -0.11 -0.46 0.34 -0.76 3.22 -5.96 0.36 -0.68 0.52 -0.51 0.85 -0.63 5 of 22 Section 4 SJ Emp -2.10 1.05 -2.09 23.44 -1.97 -0.87 -6.27 -2.05 -0.09 1.13 0.70 8.31 -1.28 0.18 -0.30 Contemp 0.04 -1.15 -0.93 2.41 -0.26 0.25 1.26 2.75 -6.12 -0.06 -1.22 0.99 6.57 0.46 0.43 Regression T-Stats Lagged Revenue 0.12 0.78 3.45 -3.63 0.73 1.69 1.95 -2.23 -0.93 1.01 0.05 0.00 -1.10 1.77 2.07 -1.17 1.64 -0.89 -0.26 -0.43 3.94 -3.94 1.06 -0.97 1.85 -1.97 0.58 -0.70 0.46 -0.41 Section 5 SJ Emp -0.64 0.97 -1.20 2.84 -0.32 -0.37 -1.60 -2.10 -0.54 0.48 2.00 1.00 -2.37 0.24 -0.22 Section 6 Net Effect C+L T-Stat 0.13 0.08 0.80 1.44 -0.34 -0.26 5.94 2.26 -1.74 -0.61 0.89 0.17 0.48 0.21 2.04 2.78 -0.24 -3.24 -0.14 -0.18 0.22 1.43 4.50 1.10 1.77 4.71 0.94 0.59 1.61 0.50 508 r2 0.73 0.96 0.99 0.97 0.64 0.21 0.82 0.95 0.99 0.55 0.96 0.61 0.99 0.48 0.32 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page46 of 62 Exhibit 2 Apple Section 1 Job Title Years of Data 6 6 6 6 6 6 6 6 Total Emp-Years 17 16 6 40 6 1398 15 19 Section 2 Level Correlation Coeff T-Stat -0.16 -0.32 -0.29 -0.60 -0.30 -0.62 -0.31 -0.65 -0.45 -1.02 -0.65 -1.70 -0.76 -2.36 -0.85 -3.22 Change Correlation Coeff T-Stat -0.07 -0.13 0.78 2.16 -0.55 -1.13 -0.11 -0.19 0.84 2.67 0.32 0.59 -0.93 -4.48 -0.43 -0.83 Section 3 Contemp Section 4 Section 5 Section 6 Regression Coefficients Lagged Revenue Regression T-Stats Lagged Revenue Net Effect C+L T-Stat r2 6 of 22 SJ Emp Contemp SJ Emp 509 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page47 of 62 Exhibit 2 Google Section 1 Job Title Years of Data Total Emp-Years Section 2 Level Correlation Coeff T-Stat 0.94 8.15 0.91 6.58 0.91 6.51 0.86 5.00 0.82 4.29 0.79 3.89 0.79 3.86 0.79 3.83 0.79 3.82 0.78 3.75 0.74 3.33 0.71 3.05 0.71 3.01 0.70 2.90 0.67 2.68 0.62 2.39 0.59 2.20 0.56 2.05 0.51 1.78 0.48 1.63 0.27 0.84 0.81 3.90 0.80 3.75 0.75 3.16 0.71 2.82 0.66 2.47 0.52 1.74 0.32 0.95 0.84 4.08 0.78 3.27 0.73 2.80 0.71 2.63 0.67 2.38 0.64 2.18 0.56 1.79 0.44 1.28 0.34 0.95 0.31 0.86 0.26 0.72 0.22 0.59 0.09 0.23 0.06 0.17 -0.15 -0.40 -0.24 -0.66 -0.54 -1.69 0.78 3.05 0.78 3.04 0.71 2.50 0.69 2.34 0.64 2.06 0.55 1.60 0.51 1.45 0.39 1.03 0.37 0.97 0.35 0.91 0.30 0.76 0.21 0.52 0.20 0.50 0.17 0.42 Section 3 Change Correlation Coeff T-Stat 0.89 5.63 0.88 5.21 0.83 4.27 0.76 3.30 0.82 4.05 0.78 3.55 0.75 3.22 0.61 2.21 0.84 4.31 0.82 4.01 0.75 3.24 0.72 2.91 0.83 4.25 0.70 2.78 0.50 1.64 0.47 1.52 0.55 1.84 0.53 1.77 0.23 0.66 0.39 1.21 -0.02 -0.05 0.77 3.21 0.72 2.51 0.85 4.29 0.47 1.42 0.50 1.53 0.62 2.09 0.68 2.45 0.82 3.45 0.77 2.94 0.80 3.23 0.70 2.43 0.71 2.45 0.60 1.84 0.83 3.70 0.63 2.00 0.18 0.46 0.54 1.58 0.45 1.12 0.30 0.77 -0.11 -0.27 0.01 0.02 -0.25 -0.64 -0.10 -0.24 -0.22 -0.55 0.71 2.28 0.92 5.32 0.70 2.21 0.76 2.58 0.76 2.65 0.85 3.66 0.34 0.81 0.49 1.26 0.63 1.81 0.29 0.68 0.38 0.92 0.24 0.55 -0.11 -0.25 0.52 1.36 Contemp 0.08 0.26 0.80 0.16 -0.08 -0.21 0.45 -0.27 0.61 0.38 0.64 -0.30 0.68 -0.29 -0.72 0.27 -1.63 -2.49 -1.01 -0.98 0.15 0.35 -0.11 1.58 1.78 1.25 0.46 1.20 1.37 0.96 1.06 1.73 0.80 0.28 0.12 2.00 1.05 -0.17 0.44 -0.23 0.35 0.56 -2.18 -1.80 -0.63 1.10 1.88 0.75 0.56 1.02 1.26 0.53 0.46 0.32 -1.44 -0.60 1.32 0.76 -0.08 7 of 22 Regression Coefficients Lagged Revenue 0.07 1.36 0.10 0.73 0.26 0.48 0.08 0.70 -1.78 2.60 -1.42 2.46 0.57 0.45 -0.71 2.24 0.50 0.12 0.24 0.53 0.88 -0.45 -2.66 3.51 0.53 0.03 -1.04 1.65 -1.63 2.36 0.41 0.37 -4.50 5.16 -7.13 7.79 -1.63 2.56 -2.45 3.07 0.67 0.31 0.43 0.23 -0.45 1.71 2.53 -1.92 3.60 -2.30 1.78 -1.19 0.10 0.22 1.43 -0.38 2.09 -0.38 1.43 -0.46 1.36 -0.75 2.75 -2.01 0.83 -0.13 0.10 0.34 0.02 1.64 0.63 0.47 1.92 -0.72 -0.39 2.01 0.25 -0.04 -1.16 2.30 0.55 0.79 1.41 -0.72 -3.28 3.77 -3.72 4.55 -1.27 2.21 1.74 0.04 2.60 -2.06 1.66 0.17 0.45 0.11 1.13 -0.62 -0.55 1.38 0.15 1.09 0.80 0.61 0.51 1.07 -4.65 5.64 -2.22 3.62 1.39 -0.83 1.14 0.60 -0.37 1.79 Section 4 SJ Emp -2.10 -0.87 -1.30 -1.49 0.26 -2.14 -2.87 -3.07 -1.31 -2.31 -0.85 -1.03 -1.25 -1.88 -3.79 -1.40 -4.24 -5.04 -2.55 -5.23 -4.53 -2.19 -3.16 -2.75 0.40 1.94 1.96 -3.13 -0.78 1.25 0.45 1.05 0.74 -0.24 -0.59 0.85 -0.01 1.80 1.69 -0.22 2.64 -1.11 -6.73 -2.91 -1.20 3.10 -4.37 -3.81 1.61 2.14 2.37 0.81 0.32 -0.52 -3.81 4.53 8.66 3.34 -0.64 Contemp 0.45 1.01 0.87 0.40 -0.11 -0.56 0.99 -0.83 1.49 1.00 2.62 -0.32 1.35 -0.93 -2.59 0.48 -1.47 -2.28 -1.52 -0.85 0.32 1.13 -0.14 3.14 2.18 3.31 0.71 1.21 4.96 5.78 2.63 7.82 2.41 0.63 0.18 0.89 1.31 -0.23 0.59 -0.78 1.22 1.04 -1.31 -2.13 -1.34 0.75 3.56 2.83 1.59 3.30 0.69 0.40 0.75 0.57 -0.38 -0.29 0.97 0.68 -0.26 Regression T-Stats Lagged Revenue 0.26 3.49 0.27 1.53 0.13 0.35 0.14 0.89 -1.70 2.30 -2.52 4.01 0.55 0.79 -1.34 4.09 0.56 0.20 0.27 0.99 1.79 -1.17 -1.73 2.31 0.47 0.04 -2.14 2.97 -3.56 4.96 0.50 0.37 -2.51 2.86 -3.94 4.41 -1.63 2.14 -1.26 1.94 0.91 0.40 0.64 0.53 -0.24 1.71 2.44 -2.19 2.42 -1.61 3.15 -1.67 0.09 0.15 0.71 -0.24 3.34 -0.84 3.93 -1.70 1.44 -1.12 6.48 -5.33 1.03 -0.21 0.10 0.55 0.03 1.22 0.16 0.13 1.32 -0.55 -0.39 1.39 0.24 -0.03 -2.06 4.60 1.12 0.93 1.55 -0.68 -1.20 1.38 -2.64 3.35 -1.50 2.05 0.51 0.02 1.63 -1.79 2.60 0.37 0.57 0.16 1.62 -1.01 -0.15 0.40 0.05 0.45 0.80 0.43 0.58 0.97 -0.58 0.75 -0.54 0.77 0.50 -0.31 0.56 0.33 -0.67 2.41 Section 5 SJ Emp -3.85 -1.28 -0.64 -1.13 0.15 -2.41 -1.95 -3.87 -1.16 -1.54 -0.82 -0.42 -0.83 -1.92 -5.62 -0.72 -1.61 -1.94 -1.56 -2.93 -3.20 -1.75 -2.76 -1.43 0.12 1.23 1.13 -1.47 -0.51 1.37 0.23 0.90 0.54 -0.18 -0.27 0.07 0.00 0.70 0.85 -0.12 1.48 -0.37 -0.72 -0.63 -0.46 0.24 -1.79 -3.67 1.11 1.81 0.32 0.30 0.22 -0.59 -0.48 0.24 1.46 0.78 -0.70 Section 6 Net Effect C+L T-Stat 0.15 0.37 0.36 0.62 1.06 0.37 0.24 0.26 -1.86 -1.10 -1.63 -1.80 1.02 0.69 -0.98 -1.19 1.11 0.87 0.62 0.50 1.52 2.14 -2.97 -1.23 1.21 0.75 -1.33 -1.73 -2.35 -3.28 0.68 0.51 -6.13 -2.16 -9.62 -3.40 -2.64 -1.62 -3.43 -1.12 0.82 0.70 0.78 0.81 -0.56 -0.21 4.11 2.77 5.38 2.41 3.03 3.39 0.56 0.33 2.62 0.89 3.46 4.07 2.40 4.80 2.42 1.86 4.48 7.35 1.62 1.47 0.38 0.27 0.14 0.11 2.63 0.45 2.97 1.39 -0.56 -0.34 0.69 0.39 -1.39 -1.72 0.91 1.23 1.96 1.43 -5.46 -1.31 -5.52 -2.58 -1.90 -1.52 2.84 0.58 4.48 2.23 2.41 2.73 1.01 0.92 2.15 2.18 0.71 0.14 0.68 0.17 1.26 0.79 0.83 0.58 -6.10 -0.52 -2.82 -0.47 2.71 0.67 1.90 0.61 -0.45 -0.53 r2 510 0.96 0.91 0.88 0.75 0.89 0.94 0.77 0.95 0.79 0.80 0.74 0.86 0.75 0.84 0.91 0.59 0.82 0.91 0.68 0.83 0.75 0.77 0.90 0.92 0.86 0.89 0.63 0.77 0.97 0.96 0.82 0.97 0.93 0.80 0.92 0.77 0.63 0.85 0.60 0.97 0.74 0.74 0.58 0.88 0.70 0.85 0.96 0.96 0.87 0.96 0.87 0.96 0.95 1.00 0.92 0.68 0.78 0.91 0.97 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page48 of 62 Exhibit 2 Google Section 1 Job Title Years of Data Total Emp-Years Section 2 Level Correlation Coeff T-Stat 0.11 0.26 0.10 0.25 0.09 0.22 0.08 0.19 0.00 0.00 -0.19 -0.47 0.94 6.31 0.88 4.22 0.81 3.05 0.80 2.97 0.78 2.79 0.77 2.68 0.76 2.60 0.73 2.36 0.72 2.31 0.70 2.22 0.69 2.14 0.67 2.00 0.64 1.87 0.63 1.80 0.62 1.76 0.61 1.74 0.60 1.68 0.60 1.67 0.57 1.56 0.56 1.52 0.50 1.29 0.49 1.26 0.47 1.20 0.44 1.11 0.44 1.09 0.43 1.06 0.41 1.02 0.40 0.97 0.23 0.53 0.22 0.51 0.21 0.49 0.18 0.41 0.13 0.29 -0.30 -0.69 -0.30 -0.69 0.94 5.52 0.82 2.84 0.81 2.78 0.79 2.55 0.78 2.53 0.74 2.19 0.71 2.02 0.70 1.99 0.68 1.86 0.63 1.62 0.59 1.45 0.58 1.44 0.57 1.40 0.56 1.37 0.54 1.30 0.54 1.27 0.52 1.21 0.47 1.06 Section 3 Change Correlation Coeff T-Stat 0.05 0.12 0.40 0.98 0.47 1.20 0.61 1.74 0.54 1.44 0.36 0.87 0.98 10.15 0.98 9.66 0.93 5.04 0.89 3.87 0.92 4.85 0.87 3.50 0.79 2.55 0.77 2.38 0.73 2.15 0.77 2.40 0.75 2.28 0.86 3.38 0.87 3.48 0.55 1.14 0.63 1.61 0.68 1.83 0.64 1.66 0.75 2.29 0.90 4.02 0.76 2.33 0.39 0.83 0.67 1.78 0.38 0.82 0.37 0.81 0.42 0.92 0.45 0.99 0.49 0.79 0.54 1.30 0.45 1.01 0.16 0.22 0.41 0.90 0.31 0.66 0.00 -0.01 -0.11 -0.22 -0.60 -1.51 0.96 5.86 0.88 3.25 0.92 4.09 0.82 2.51 0.98 9.30 0.84 2.71 0.79 2.22 0.75 1.95 0.97 6.88 0.84 2.71 0.55 1.13 0.63 1.41 0.51 1.02 0.63 1.40 0.56 1.17 0.75 1.95 0.78 2.19 0.48 0.94 Contemp 1.78 -0.64 -0.22 -0.11 -0.19 -0.44 0.92 1.71 2.09 1.89 -0.04 -0.01 -2.08 -0.48 -2.48 -0.78 -0.69 1.48 -0.04 0.39 -0.92 0.01 -0.89 0.41 0.15 0.78 4.23 1.37 -0.80 -1.66 -0.82 -0.65 1.37 -5.72 0.28 2.68 -0.83 -0.20 -0.36 3.76 -1.75 8 of 22 Regression Coefficients Lagged Revenue 4.82 -3.95 -1.19 2.95 -0.67 2.13 -0.73 1.64 -1.04 2.39 -1.21 2.37 0.44 0.15 1.08 -1.17 1.73 -1.40 2.59 -2.38 -1.56 2.30 -0.93 1.40 -3.14 6.08 -1.11 2.62 -6.19 6.26 -1.84 3.07 -2.40 3.41 1.36 -0.94 -0.79 1.30 -0.10 2.24 -2.25 3.15 -0.21 1.26 -1.99 3.14 0.22 0.58 -0.71 1.44 0.82 -0.11 8.54 -8.63 -4.14 4.70 -1.63 2.83 -2.94 4.48 -1.60 2.92 -1.18 2.15 2.80 -2.02 -13.34 10.00 0.43 0.82 4.65 -1.97 -3.92 4.02 -0.67 2.19 -0.84 1.88 6.86 -6.03 -2.91 2.70 Section 4 SJ Emp -8.75 -1.74 -1.85 0.18 4.19 -2.43 1.14 1.74 4.09 -0.19 0.05 1.72 -2.19 0.84 -2.27 -1.89 -7.95 2.69 0.83 12.58 -0.31 0.28 -0.82 1.15 1.90 0.71 -7.90 24.13 -2.19 -6.60 -2.97 -1.97 0.00 5.70 0.22 0.00 7.39 2.29 -1.39 2.52 -1.26 Contemp 0.53 -0.96 -0.22 -0.35 -0.27 -0.85 1.60 2.76 11.51 1.24 -0.07 -0.03 -1.36 -6.23 -3.18 -9.88 -0.25 0.97 -0.15 Section 5 Regression T-Stats Lagged Revenue 0.77 -0.59 -1.03 2.17 -0.39 1.04 -1.26 2.37 -0.75 1.17 -1.21 2.05 0.34 0.13 0.95 -0.95 5.52 -4.20 0.96 -0.73 -1.45 2.12 -1.46 2.31 -1.38 1.95 -8.70 18.00 -3.57 4.53 -12.40 19.74 -0.42 0.61 0.51 -0.33 -1.63 2.67 SJ Emp -0.38 -0.98 -0.85 0.16 1.85 -1.36 0.94 1.42 10.69 -0.07 0.04 2.49 -0.97 7.53 -2.61 -11.61 -1.33 0.73 1.56 Section 6 Net Effect C+L T-Stat 6.61 0.72 -1.83 -1.01 -0.89 -0.33 -0.84 -0.97 -1.24 -0.59 -1.66 -1.10 1.36 0.76 2.78 1.63 3.82 7.88 4.48 1.07 -1.60 -0.99 -0.94 -1.01 -5.22 -1.38 -1.59 -7.81 -8.67 -3.46 -2.62 -11.63 -3.09 -0.37 2.85 0.69 -0.83 -1.15 r2 0.69 0.98 0.96 0.92 0.95 0.94 0.99 0.99 1.00 0.91 0.99 0.99 0.98 1.00 1.00 1.00 0.93 0.94 0.99 -4.54 0.02 -5.88 0.85 0.22 1.67 1.16 0.11 -3.13 -0.97 -0.73 -0.59 -5.33 -0.15 -6.81 0.25 -0.49 0.94 1.18 -0.20 -3.15 -0.89 -0.68 -0.57 8.35 0.74 10.24 0.60 1.27 -0.12 -1.07 0.22 6.13 1.31 1.34 0.99 -0.79 0.18 -2.59 1.23 1.40 0.79 -1.13 0.91 -4.50 -1.73 -1.06 -0.91 -3.17 -0.20 -2.88 0.64 -0.56 1.60 12.77 -2.77 -2.43 -4.59 -2.42 -1.83 -5.10 -0.09 -6.54 0.47 -0.26 1.20 1.17 -0.08 -3.16 -0.92 -0.70 -0.58 1.00 0.89 1.00 0.99 0.97 0.99 0.85 0.84 0.99 0.93 0.88 0.98 -1.24 0.38 -1.29 0.26 1.52 0.38 1.11 0.10 -19.06 0.71 -1.27 0.30 0.94 1.00 -2.91 -0.92 -1.32 6.36 -2.35 -5.34 -1.76 -1.38 5.97 -2.34 6.73 4.10 3.83 -5.30 2.92 2.49 1.40 -0.58 2.11 -1.03 -4.76 -0.87 -1.20 10.62 -4.65 -4.89 -1.55 -1.43 6.14 -2.36 0.99 0.98 0.99 1.00 0.94 511 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page49 of 62 Exhibit 2 Google Section 1 Job Title Years of Data Total Emp-Years Section 2 Level Correlation Coeff T-Stat 0.44 0.99 0.42 0.93 0.38 0.83 0.35 0.74 0.34 0.72 0.30 0.63 0.30 0.63 0.29 0.61 0.25 0.51 0.22 0.45 0.19 0.39 0.15 0.31 0.14 0.29 0.12 0.23 0.10 0.20 0.09 0.18 0.07 0.13 -0.04 -0.09 -0.05 -0.11 -0.24 -0.48 Section 3 Change Correlation Coeff T-Stat 0.60 1.32 0.50 0.99 0.42 0.81 0.27 0.49 0.64 1.45 0.95 3.20 0.18 0.32 0.17 0.30 0.18 0.32 0.08 0.14 0.55 1.13 0.30 0.45 0.37 0.69 0.15 0.27 0.58 1.24 0.01 0.01 0.07 0.12 -0.37 -0.69 -0.28 -0.51 -0.60 -1.31 Contemp 9 of 22 Section 4 Section 5 Section 6 Regression Coefficients Lagged Revenue Regression T-Stats Lagged Revenue Net Effect C+L T-Stat r2 SJ Emp Contemp SJ Emp 512 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page50 of 62 Exhibit 2 Intel Section 1 Job Title Years Total of Data Emp-Years 11 432 11 1501 11 233 11 3042 11 5042 11 293 11 724 11 59 11 394 11 3991 11 715 11 437 11 6082 11 912 11 31 11 216 11 1681 11 103 11 2903 11 413 11 1438 11 2235 11 4821 11 638 11 760 11 501 11 1538 11 292 11 528 11 75 11 244 11 5735 11 2120 11 328 11 1011 11 811 11 262 11 1332 11 104 11 91 11 127 11 1525 11 9515 11 369 11 6476 11 73 11 1580 11 165 11 573 11 155 11 598 11 548 11 1676 11 473 11 402 11 373 Section 2 Level Correlation Coeff T-Stat 0.96 10.82 0.96 9.78 0.94 8.46 0.94 8.03 0.92 7.30 0.91 6.73 0.88 5.65 0.88 5.56 0.88 5.52 0.88 5.51 0.86 4.96 0.85 4.85 0.85 4.85 0.85 4.76 0.84 4.74 0.83 4.50 0.83 4.45 0.81 4.17 0.81 4.12 0.81 4.11 0.81 4.08 0.80 4.01 0.80 4.00 0.80 3.98 0.80 3.97 0.79 3.91 0.79 3.90 0.79 3.89 0.79 3.81 0.78 3.80 0.78 3.78 0.78 3.75 0.78 3.72 0.77 3.66 0.77 3.64 0.77 3.62 0.77 3.61 0.77 3.61 0.77 3.57 0.76 3.52 0.75 3.44 0.75 3.43 0.75 3.39 0.74 3.35 0.74 3.31 0.74 3.27 0.74 3.26 0.73 3.24 0.73 3.18 0.72 3.15 0.72 3.14 0.72 3.11 0.72 3.08 0.72 3.07 0.71 3.06 0.71 3.04 Change Correlation Coeff T-Stat 0.95 8.41 0.94 7.56 0.91 6.14 0.89 5.67 0.91 6.21 0.89 5.46 0.94 8.07 0.72 2.91 0.88 5.34 0.96 9.32 0.96 9.29 0.84 4.41 0.94 7.51 0.94 7.60 0.82 4.00 0.83 4.23 0.92 6.69 0.87 4.91 0.95 8.50 0.95 8.85 0.93 7.04 0.89 5.55 0.96 9.45 0.91 6.09 0.93 7.45 0.88 5.24 0.91 6.15 0.82 4.10 0.75 3.23 0.81 3.88 0.90 5.76 0.91 6.32 0.95 9.08 0.77 3.41 0.91 6.37 0.84 4.31 0.91 6.02 0.92 6.65 0.84 4.35 0.89 5.55 0.90 6.00 0.89 5.39 0.86 4.86 0.97 10.62 0.97 10.58 0.54 1.83 0.93 7.07 0.94 7.74 0.97 11.28 0.91 6.37 0.89 5.39 0.82 4.03 0.94 7.83 0.93 7.05 0.88 5.17 0.89 5.66 Section 3 Contemp 2.03 1.56 1.47 0.61 0.81 2.30 1.43 1.12 0.63 1.21 1.41 0.76 0.81 0.95 0.59 0.66 0.78 0.76 0.92 0.88 0.96 0.73 0.80 0.77 0.94 0.75 0.78 0.70 0.84 2.04 0.68 0.76 0.74 0.75 0.74 0.67 0.75 0.79 0.53 1.09 0.35 0.78 0.89 0.80 0.88 0.69 0.83 0.74 0.74 1.26 0.65 0.60 0.64 0.78 0.60 0.86 10 of 22 Regression Coefficients Lagged Revenue -0.51 0.64 0.30 0.32 1.33 -0.23 0.39 -0.20 2.22 -0.06 0.95 -0.19 0.58 0.19 0.73 0.22 0.35 -0.13 0.07 0.45 -0.28 0.49 0.75 0.30 0.45 0.34 0.69 0.20 0.35 0.44 0.62 0.09 0.39 0.30 0.70 0.09 0.20 0.32 0.38 0.07 0.63 0.02 0.22 0.42 0.19 0.27 0.53 0.13 0.34 0.23 0.24 0.46 0.20 0.22 0.83 0.05 1.07 0.36 0.36 0.21 0.61 0.06 0.29 0.30 0.29 0.11 0.71 0.38 0.36 -0.06 0.44 0.10 0.54 0.02 0.51 0.18 0.19 0.54 0.23 -0.37 0.00 0.00 0.45 -0.05 0.85 -0.21 0.28 0.13 0.17 0.11 1.21 -0.10 0.46 0.21 0.42 0.07 0.18 -0.01 -0.07 0.62 0.32 0.32 0.45 0.46 0.29 -0.03 0.23 0.24 0.22 0.25 0.10 0.41 Section 4 SJ Emp -0.34 -0.54 -0.09 0.31 -0.63 -0.45 -0.55 -0.33 0.06 -0.45 -0.32 -0.49 -0.48 -0.59 -0.13 0.03 -0.37 -0.30 -0.30 -0.09 -0.19 -0.36 -0.26 -0.22 -0.29 -0.50 -0.05 -0.23 -0.95 -0.24 -0.23 -0.31 -0.08 -0.88 0.16 -0.20 -0.17 -0.35 -0.50 0.29 0.08 0.15 0.02 -0.19 -0.05 -0.26 -0.44 -0.14 0.08 -0.88 -0.39 -0.71 0.09 -0.21 -0.11 -0.58 Contemp 6.11 6.76 4.71 7.76 3.59 4.05 1.48 2.35 4.97 5.45 4.26 4.90 6.95 3.95 3.17 4.10 5.05 4.60 8.74 5.34 3.97 7.48 12.44 4.39 5.66 4.67 3.77 3.30 4.51 3.00 9.04 6.40 11.59 4.32 6.31 3.33 4.38 4.64 4.55 3.84 3.84 5.52 4.12 12.18 9.63 3.46 4.96 12.31 10.93 3.47 5.41 2.24 12.56 11.30 4.23 3.13 Regression T-Stats Lagged Revenue -0.78 1.25 0.36 0.73 0.74 -0.25 2.09 -1.33 2.93 -0.23 0.63 -0.18 0.38 0.39 0.84 0.37 1.77 -0.54 0.12 2.00 -0.51 1.60 1.85 1.46 1.58 2.34 1.52 0.76 0.95 1.78 2.02 0.34 1.16 1.60 2.74 0.41 0.80 2.51 1.23 0.34 1.40 0.08 1.12 3.34 1.28 3.21 1.74 0.59 1.03 1.16 0.68 2.22 0.59 0.79 2.23 0.16 2.41 1.37 0.25 0.19 4.38 0.55 1.23 2.00 2.62 1.25 2.20 1.67 1.72 -0.35 1.31 0.35 2.21 0.07 1.60 0.85 0.98 3.37 0.37 -0.82 0.02 0.00 1.98 -0.25 2.74 -0.75 2.90 1.51 1.06 0.97 4.54 -0.32 1.46 1.03 4.81 0.79 1.79 -0.09 -0.14 1.57 1.65 2.06 0.98 1.36 3.94 -0.39 1.86 2.72 1.02 1.29 0.26 1.26 Section 5 SJ Emp -0.76 -1.63 -0.15 1.93 -2.53 -0.54 -1.04 -0.49 0.30 -1.73 -0.87 -2.05 -2.61 -1.49 -0.52 0.08 -1.35 -1.11 -1.67 -0.31 -0.43 -2.29 -2.23 -0.74 -1.11 -1.90 -0.17 -0.52 -3.86 -0.23 -1.62 -1.53 -0.67 -3.46 0.66 -0.63 -0.64 -1.17 -2.61 0.50 0.63 0.54 0.06 -1.69 -0.28 -0.91 -1.57 -1.28 0.67 -2.13 -1.93 -1.45 1.04 -1.66 -0.47 -1.61 Section 6 Net Effect C+L T-Stat 1.52 1.78 1.86 2.07 2.80 1.46 1.00 4.39 3.03 4.40 3.25 1.88 2.00 2.26 1.85 1.54 0.98 3.77 1.28 2.52 1.13 2.18 1.51 3.13 1.27 4.17 1.64 3.53 0.94 2.06 1.28 3.57 1.17 3.20 1.46 4.40 1.12 4.24 1.26 3.91 1.58 3.38 0.95 4.04 1.00 5.90 1.31 3.66 1.28 3.47 0.99 2.42 0.98 2.32 1.53 3.43 1.91 3.58 2.40 1.22 1.29 7.24 1.06 3.83 1.03 7.72 1.46 3.53 1.09 4.25 1.11 2.49 1.28 4.18 1.30 3.57 0.72 2.80 1.32 2.15 0.35 1.75 1.24 4.20 1.74 4.39 1.08 8.85 1.05 5.69 1.91 5.11 1.30 3.58 1.16 10.29 0.92 7.00 1.20 1.99 0.97 3.95 1.05 1.88 0.93 9.19 1.00 6.68 0.82 2.88 0.96 1.92 r2 513 0.95 0.96 0.92 0.95 0.96 0.88 0.91 0.81 0.87 0.97 0.95 0.95 0.97 0.94 0.91 0.93 0.96 0.93 0.98 0.95 0.92 0.98 0.99 0.94 0.96 0.96 0.90 0.85 0.96 0.83 0.97 0.97 0.99 0.93 0.95 0.81 0.92 0.94 0.96 0.83 0.86 0.95 0.91 0.99 0.98 0.90 0.95 0.99 0.98 0.92 0.97 0.88 0.99 0.99 0.94 0.89 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page51 of 62 Exhibit 2 Intel Section 1 Job Title Years Total of Data Emp-Years 11 1906 11 3531 11 934 11 1873 11 130 11 2037 11 88 11 366 11 137 11 828 11 969 11 87 11 179 11 8983 11 934 11 1049 11 146 11 509 11 1402 11 2097 11 268 11 546 11 12004 11 577 11 50 11 358 11 753 11 517 11 547 11 834 11 556 11 361 11 955 11 188 11 169 11 91 11 94 11 59 11 537 11 249 11 557 11 1504 11 159 11 629 11 427 11 498 11 465 11 7219 11 641 11 1364 11 117 11 3942 11 198 11 9310 11 910 11 1690 Section 2 Level Correlation Coeff T-Stat 0.71 3.04 0.71 3.03 0.71 3.03 0.71 3.02 0.71 2.99 0.70 2.98 0.70 2.98 0.70 2.95 0.70 2.94 0.70 2.92 0.70 2.91 0.69 2.89 0.69 2.87 0.69 2.87 0.69 2.86 0.69 2.85 0.69 2.84 0.69 2.84 0.69 2.83 0.68 2.81 0.68 2.77 0.68 2.76 0.68 2.75 0.67 2.74 0.67 2.72 0.67 2.72 0.67 2.70 0.67 2.69 0.67 2.68 0.66 2.67 0.66 2.66 0.66 2.65 0.66 2.65 0.66 2.64 0.66 2.63 0.66 2.62 0.66 2.60 0.65 2.59 0.65 2.59 0.65 2.59 0.65 2.58 0.65 2.54 0.64 2.53 0.64 2.51 0.64 2.50 0.64 2.49 0.64 2.49 0.64 2.47 0.64 2.47 0.63 2.45 0.63 2.44 0.63 2.42 0.63 2.42 0.63 2.40 0.62 2.40 0.62 2.39 Change Correlation Coeff T-Stat 0.97 10.58 0.89 5.61 0.92 6.73 0.96 9.25 0.90 5.77 0.92 6.42 0.91 6.08 0.95 8.65 0.67 2.53 0.93 7.12 0.91 6.08 0.75 3.25 0.87 5.06 0.96 9.77 0.96 10.05 0.89 5.67 0.65 2.41 0.89 5.51 0.94 7.53 0.97 11.50 0.95 8.82 0.94 7.55 0.95 8.95 0.96 9.51 0.45 1.42 0.85 4.50 0.97 11.28 0.84 4.39 0.95 9.06 0.94 7.57 0.89 5.49 0.55 1.88 0.95 8.72 0.88 5.23 0.92 6.63 0.84 4.34 0.84 4.32 0.81 3.93 0.97 11.61 0.78 3.47 0.90 5.76 0.90 5.82 0.85 4.66 0.94 7.72 0.87 5.03 0.91 6.15 0.92 6.44 0.93 7.41 0.97 10.80 0.95 8.60 0.86 4.68 0.97 10.47 0.75 3.16 0.93 7.13 0.94 7.87 0.96 10.06 Section 3 Contemp 0.85 0.72 0.72 0.85 0.86 0.63 0.69 0.67 0.71 0.63 0.66 0.92 0.64 0.78 0.83 0.68 0.39 0.70 0.77 0.78 0.83 0.72 0.76 0.82 1.17 0.58 0.91 0.49 0.78 0.81 0.73 1.08 0.67 0.67 0.78 1.85 0.61 0.97 0.81 0.69 0.61 0.64 0.60 0.84 0.58 0.51 0.72 0.70 0.70 0.84 0.66 0.80 0.68 0.67 0.72 0.63 11 of 22 Regression Coefficients Lagged Revenue 0.22 0.13 0.21 0.33 0.36 0.04 0.36 0.21 0.03 0.42 0.23 0.18 0.06 0.27 0.18 0.16 0.37 0.76 0.27 -0.10 0.35 -0.18 1.57 -0.16 0.05 0.57 0.25 -0.03 0.15 0.12 0.28 0.40 0.43 0.29 0.18 0.30 0.19 0.26 0.15 0.07 0.00 0.24 0.29 0.07 0.28 -0.02 0.18 0.02 0.66 0.28 0.40 -0.23 0.20 -0.12 0.28 0.06 0.29 0.08 0.02 0.36 0.28 -0.05 1.40 -0.82 0.22 -0.09 0.43 -0.06 -0.01 0.43 0.51 0.49 0.00 0.79 0.78 -0.29 0.20 0.12 0.54 -0.26 0.06 0.35 0.19 0.22 0.38 0.23 0.25 -0.04 0.23 0.07 0.13 0.12 0.14 0.13 0.15 -0.07 0.06 0.07 0.26 -0.09 0.34 0.73 0.17 0.06 0.59 0.33 0.26 -0.11 0.22 0.02 0.21 -0.01 Section 4 SJ Emp -0.14 -0.26 -0.02 -0.43 -0.38 -0.11 -0.13 -0.11 -0.67 0.06 0.26 -0.84 -0.77 0.09 -0.04 -0.60 -0.16 -0.17 -0.34 -0.02 -0.10 -0.04 0.07 0.02 -0.65 0.30 0.25 0.02 -0.16 -0.27 0.02 0.92 0.12 0.11 -0.34 -0.64 -0.89 0.10 -0.17 0.23 -0.26 -0.12 -0.42 0.15 0.02 -0.02 -0.04 0.21 0.06 0.15 -1.36 -0.07 -0.81 0.23 0.05 -0.03 Contemp 9.03 7.95 7.71 9.91 3.38 8.43 3.97 13.19 3.37 5.89 6.39 4.41 5.02 12.24 12.79 4.91 1.82 4.88 4.41 13.52 7.42 10.66 16.18 6.42 1.34 4.89 18.00 3.39 9.05 8.80 3.34 4.01 6.90 7.43 4.71 3.26 1.50 2.52 12.42 3.24 4.22 4.79 3.11 6.63 3.76 4.81 4.33 6.35 21.06 7.62 1.62 7.41 1.45 12.47 6.85 9.53 Regression T-Stats Lagged Revenue 1.52 1.05 1.32 2.79 2.74 0.33 2.60 2.01 0.07 1.28 1.93 1.78 0.21 1.20 2.16 2.20 1.01 2.72 1.78 -0.60 2.57 -1.14 3.84 -0.58 0.28 3.39 2.56 -0.35 1.57 1.42 1.15 2.29 1.34 1.00 0.78 1.58 0.81 1.16 1.65 0.91 -0.01 1.66 2.99 0.76 4.10 -0.24 1.06 0.12 0.35 0.19 2.47 -1.27 2.81 -1.70 1.48 0.26 2.41 0.68 0.16 3.17 1.08 -0.15 3.26 -2.79 1.62 -0.63 3.15 -0.46 -0.04 2.09 0.37 0.49 0.00 1.68 1.75 -0.57 2.35 1.33 1.77 -0.82 0.27 1.84 1.02 1.19 1.51 0.77 1.51 -0.25 1.03 0.32 0.92 0.74 0.57 0.55 0.90 -0.43 1.36 1.47 1.56 -0.57 0.75 1.47 1.11 0.37 0.87 0.59 3.48 -1.33 1.61 0.13 2.25 -0.08 Section 5 SJ Emp -0.83 -1.66 -0.10 -2.80 -0.96 -0.85 -0.54 -1.16 -2.35 0.37 1.47 -2.69 -4.03 0.73 -0.31 -2.62 -0.52 -0.74 -1.27 -0.15 -0.55 -0.29 0.81 0.08 -0.47 1.51 2.54 0.07 -1.08 -1.75 0.07 2.83 0.72 0.60 -1.30 -0.66 -1.45 0.15 -1.54 0.62 -1.16 -0.54 -1.05 0.67 0.07 -0.12 -0.16 1.00 1.02 0.63 -1.93 -0.39 -1.25 2.29 0.28 -0.26 Section 6 Net Effect C+L T-Stat 1.07 6.07 0.93 4.71 1.08 6.22 1.21 7.24 0.89 1.59 0.86 5.50 0.75 2.06 0.85 8.03 1.08 2.16 0.89 4.25 1.01 5.16 2.49 5.00 0.69 2.74 1.03 8.27 0.98 8.03 0.96 3.24 0.82 1.81 0.88 2.97 0.96 3.11 0.93 8.04 0.83 3.85 1.01 7.77 1.04 11.58 1.00 4.25 1.83 0.73 0.98 4.17 1.11 11.93 0.77 2.76 1.07 6.51 0.83 4.89 1.00 2.64 2.48 3.84 0.89 4.72 1.09 5.97 0.77 2.49 2.36 1.55 0.61 0.89 1.75 2.67 1.01 8.64 1.23 2.81 0.67 2.34 0.82 3.28 0.97 2.75 1.09 4.72 0.81 2.57 0.64 3.09 0.86 2.54 0.85 3.70 0.76 11.66 1.10 5.05 1.00 1.57 0.97 4.63 1.26 1.42 0.93 8.81 0.94 4.81 0.84 6.39 r2 514 0.98 0.98 0.98 0.99 0.89 0.98 0.91 0.99 0.96 0.92 0.94 0.93 0.96 0.99 0.99 0.96 0.84 0.95 0.94 0.99 0.97 0.99 0.99 0.95 0.66 0.90 0.99 0.87 0.98 0.99 0.84 0.79 0.95 0.97 0.96 0.91 0.87 0.82 0.99 0.77 0.94 0.95 0.87 0.96 0.88 0.93 0.91 0.94 1.00 0.96 0.87 0.96 0.78 0.99 0.96 0.97 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page52 of 62 Exhibit 2 Intel Section 1 Job Title Years Total of Data Emp-Years 11 283 11 142 11 2959 11 880 11 202 11 1662 11 731 11 2205 11 2086 11 1156 11 91 11 1393 11 96 11 281 11 128 11 601 11 303 11 147 11 261 11 282 11 223 11 5107 11 213 11 347 11 135 11 1471 11 2090 11 197 11 35 11 159 11 126 11 223 11 934 11 403 11 1801 11 400 11 390 11 115 11 556 11 120 11 5274 11 1349 11 29 11 83 11 120 11 167 11 379 11 164 11 57 11 2080 11 92 11 225 11 1020 11 209 11 732 11 567 Section 2 Level Correlation Coeff T-Stat 0.62 2.37 0.62 2.37 0.62 2.36 0.62 2.36 0.61 2.34 0.61 2.32 0.61 2.29 0.61 2.29 0.61 2.29 0.61 2.29 0.61 2.29 0.60 2.26 0.60 2.26 0.60 2.25 0.60 2.24 0.60 2.23 0.60 2.23 0.59 2.21 0.59 2.20 0.59 2.19 0.59 2.18 0.59 2.18 0.59 2.18 0.58 2.15 0.58 2.15 0.58 2.13 0.58 2.13 0.58 2.13 0.58 2.12 0.57 2.11 0.57 2.10 0.57 2.09 0.57 2.08 0.57 2.07 0.57 2.06 0.57 2.06 0.57 2.06 0.56 2.04 0.56 2.03 0.56 2.03 0.56 2.02 0.56 2.01 0.56 2.01 0.56 2.00 0.54 1.91 0.54 1.91 0.53 1.90 0.53 1.89 0.53 1.89 0.53 1.89 0.53 1.89 0.53 1.86 0.53 1.86 0.52 1.85 0.52 1.82 0.51 1.79 Change Correlation Coeff T-Stat 0.94 7.52 0.83 4.28 0.92 6.75 0.93 7.34 0.85 4.49 0.91 6.38 0.94 7.46 0.68 2.62 0.95 8.39 0.71 2.86 0.64 2.33 0.84 4.44 0.84 4.38 0.80 3.74 0.94 7.89 0.91 6.20 0.55 1.87 0.85 4.64 0.68 2.60 0.68 2.59 0.88 5.13 0.95 8.21 0.82 4.07 0.93 6.90 0.76 3.34 0.93 7.06 0.95 9.03 0.91 6.18 0.76 3.32 0.85 4.48 0.69 2.71 0.95 8.28 0.91 6.20 0.87 4.91 0.96 9.45 0.85 4.49 0.88 5.26 0.57 1.97 0.95 8.49 0.62 2.25 0.92 6.52 0.85 4.53 0.59 2.04 0.61 2.18 0.70 2.80 0.47 1.53 0.85 4.56 0.89 5.65 0.23 0.68 0.91 6.07 0.86 4.78 0.19 0.56 0.96 9.33 0.90 5.89 0.88 5.35 0.84 4.34 Section 3 Contemp 0.65 0.72 0.72 0.70 0.77 0.61 0.95 0.68 0.76 0.74 0.90 0.72 0.60 0.73 0.75 0.57 0.48 0.47 0.63 0.54 0.59 0.84 0.45 0.76 0.38 0.65 0.60 0.77 0.76 0.98 1.14 0.68 0.82 0.55 0.70 0.67 0.57 0.29 0.65 0.48 0.60 0.74 0.58 1.56 0.45 0.64 0.43 0.64 0.06 0.62 1.23 2.13 0.69 0.93 0.66 0.55 12 of 22 Regression Coefficients Lagged Revenue 0.05 0.30 0.31 0.18 0.20 0.13 0.32 -0.11 0.28 0.22 0.23 0.05 0.31 -0.11 0.79 -0.41 0.23 0.10 0.86 -0.51 1.18 0.26 0.19 0.02 0.15 0.30 0.65 -0.11 0.26 -0.11 0.17 0.08 0.48 0.59 0.12 0.26 0.93 0.49 0.63 -0.41 0.14 0.15 0.24 0.15 0.03 0.45 0.02 0.21 0.13 0.15 0.32 -0.21 0.18 0.03 0.16 0.05 0.57 0.11 0.74 -0.47 1.07 -0.90 0.18 0.13 0.33 -0.01 0.13 0.29 0.22 0.06 0.45 -0.41 0.16 0.17 0.20 0.31 0.18 0.00 0.36 0.00 0.23 -0.29 0.46 -0.15 0.34 0.51 1.26 -1.03 0.23 0.24 1.07 0.19 0.14 0.20 0.30 -0.11 0.28 0.22 0.33 -0.32 -0.01 0.01 5.05 -3.95 0.06 0.14 0.43 -0.28 0.43 -0.28 0.25 0.04 Section 4 SJ Emp -0.25 -0.06 -0.05 0.18 -0.61 0.04 0.18 0.54 -0.10 0.62 -1.23 0.05 -0.21 -0.15 0.04 0.06 -0.82 -0.16 -1.91 0.42 -0.09 -0.28 -0.36 -0.24 0.03 0.23 -0.01 -0.05 -0.36 0.30 0.54 -0.18 0.06 -0.30 -0.09 0.40 -0.11 -0.21 0.02 -0.07 0.32 -0.10 -0.46 0.95 -0.29 -0.58 -0.18 0.09 0.10 0.36 -0.02 3.09 -0.06 0.07 0.18 -0.15 Contemp 7.48 8.01 8.49 16.35 5.44 6.83 5.47 4.01 11.64 6.12 2.02 2.62 2.16 3.57 6.10 7.66 1.84 5.01 1.52 4.24 2.98 5.52 2.95 3.83 2.29 8.65 8.79 3.57 1.09 4.51 4.38 6.80 6.86 3.25 13.13 5.67 3.80 1.24 6.90 1.78 6.74 4.78 0.98 2.13 1.75 1.25 3.10 4.61 0.35 9.83 2.89 1.46 9.28 5.65 7.75 3.28 Regression T-Stats Lagged Revenue 0.42 2.54 2.32 1.48 1.69 1.18 5.74 -1.75 1.53 1.16 1.91 0.38 1.49 -0.46 2.68 -2.34 2.61 1.13 4.08 -4.06 1.38 0.41 0.50 0.06 0.44 0.84 2.18 -0.38 1.57 -0.60 1.70 0.72 1.14 1.74 0.93 2.02 1.85 1.07 3.97 -1.95 0.53 0.52 1.16 0.75 0.14 2.19 0.08 0.78 0.56 0.61 3.35 -1.84 1.97 0.27 0.62 0.15 0.86 0.14 2.97 -1.57 3.53 -2.14 1.40 0.96 2.24 -0.05 0.58 1.23 3.09 0.78 2.89 -2.06 0.78 0.81 0.60 0.89 1.45 0.01 0.90 0.00 1.85 -2.08 2.27 -0.65 0.40 0.67 0.97 -0.99 0.70 0.55 1.71 0.23 0.78 0.93 1.67 -0.52 1.17 0.89 4.08 -3.13 -0.01 0.02 2.76 -2.11 0.59 1.33 2.15 -1.20 3.94 -2.08 1.11 0.17 Section 5 SJ Emp -1.81 -0.33 -0.35 2.20 -2.85 0.23 0.60 2.66 -0.81 4.03 -2.07 0.13 -0.51 -0.43 0.20 0.46 -2.12 -1.06 -3.78 1.85 -0.31 -1.03 -1.50 -0.66 0.13 1.76 -0.07 -0.13 -0.34 0.79 1.07 -1.01 0.28 -1.05 -0.93 1.68 -0.43 -0.54 0.13 -0.15 2.13 -0.40 -0.59 0.70 -0.58 -0.65 -0.77 0.35 0.36 3.14 -0.03 1.66 -0.47 0.29 1.18 -0.53 Section 6 Net Effect C+L T-Stat 0.71 4.13 1.03 5.73 0.92 5.64 1.03 12.77 1.05 3.95 0.85 4.89 1.26 4.15 1.47 3.36 0.99 8.19 1.60 5.14 2.07 1.92 0.90 1.70 0.75 1.50 1.37 3.32 1.01 4.27 0.74 5.09 0.96 1.62 0.59 3.12 1.56 2.22 1.18 4.79 0.72 1.93 1.08 3.87 0.48 1.57 0.79 1.98 0.50 1.49 0.97 6.81 0.79 5.91 0.94 2.36 1.33 1.21 1.72 4.57 2.21 4.76 0.86 4.66 1.15 5.30 0.68 2.07 0.91 9.09 1.11 4.91 0.73 2.48 0.49 1.00 0.84 4.56 0.83 1.46 0.83 4.58 1.20 4.06 0.93 0.76 2.82 1.62 0.68 1.36 1.71 1.82 0.57 2.13 0.94 3.52 0.33 0.94 0.95 7.84 1.22 1.18 7.18 2.51 0.75 5.24 1.36 4.54 1.08 6.67 0.81 2.41 r2 515 0.98 0.99 0.98 0.99 0.94 0.97 0.94 0.81 0.99 0.91 0.87 0.74 0.84 0.84 0.93 0.97 0.90 0.96 0.93 0.89 0.83 0.95 0.92 0.88 0.80 0.96 0.97 0.86 0.72 0.90 0.86 0.97 0.97 0.89 0.99 0.90 0.91 0.64 0.95 0.50 0.93 0.88 0.66 0.49 0.66 0.62 0.86 0.89 0.77 0.97 0.74 0.81 0.98 0.91 0.95 0.81 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page53 of 62 Exhibit 2 Intel Section 1 Job Title Years Total of Data Emp-Years 11 147 11 86 11 102 11 4667 11 1283 11 54 11 222 11 43 11 56 11 536 11 7841 11 325 11 249 11 666 11 150 11 106 11 101 11 1976 11 353 11 56 11 137 11 105 11 125 11 117 11 65 11 156 11 35 11 98 11 225 11 171 11 45 11 533 11 243 11 774 11 47 11 199 11 111 11 30 11 31 11 361 11 734 10 901 10 102 10 1266 10 952 10 529 10 186 10 262 10 391 10 1514 10 30 10 794 10 25 10 1764 10 50 10 189 Section 2 Level Correlation Coeff T-Stat 0.51 1.78 0.51 1.77 0.50 1.75 0.50 1.75 0.50 1.74 0.50 1.74 0.49 1.67 0.48 1.66 0.47 1.62 0.46 1.56 0.46 1.55 0.46 1.55 0.46 1.54 0.46 1.54 0.46 1.54 0.44 1.49 0.44 1.46 0.44 1.46 0.43 1.43 0.43 1.42 0.43 1.42 0.42 1.38 0.41 1.34 0.41 1.33 0.40 1.32 0.38 1.22 0.35 1.14 0.35 1.12 0.34 1.10 0.34 1.08 0.34 1.08 0.34 1.07 0.33 1.05 0.33 1.04 0.29 0.92 0.27 0.84 0.25 0.76 0.21 0.64 0.17 0.52 0.12 0.38 -0.03 -0.08 0.92 6.51 0.91 6.40 0.90 5.74 0.88 5.29 0.84 4.32 0.84 4.30 0.82 4.10 0.81 3.94 0.79 3.64 0.78 3.53 0.76 3.31 0.75 3.21 0.74 3.12 0.72 2.97 0.71 2.89 Change Correlation Coeff T-Stat 0.54 1.81 0.79 3.65 0.81 3.91 0.98 12.47 0.96 9.47 0.57 1.94 0.70 2.76 0.60 2.11 0.76 3.30 0.88 5.16 0.94 7.67 0.68 2.65 0.53 1.79 0.96 9.70 0.91 6.38 0.78 3.50 0.72 2.94 0.83 4.16 0.82 4.00 0.49 1.57 0.87 4.89 0.86 4.75 0.58 2.03 0.58 2.03 -0.02 -0.07 0.74 3.13 0.59 2.08 0.57 1.97 0.71 2.82 0.80 3.76 0.50 1.62 0.41 1.28 0.86 4.84 0.83 4.27 0.73 3.05 0.60 2.10 0.48 1.56 0.09 0.25 0.66 2.46 0.79 3.70 0.47 1.51 0.96 9.16 0.96 8.44 0.83 3.66 0.92 6.33 0.94 7.21 0.98 12.18 0.82 3.73 0.91 5.67 0.97 9.92 0.77 2.94 0.88 4.88 0.69 2.31 0.96 9.71 0.55 1.62 0.39 1.04 Section 3 Contemp 1.24 1.01 0.54 0.61 0.92 0.57 0.62 0.79 0.53 0.70 0.82 0.21 1.23 0.68 0.52 0.66 0.57 0.68 0.71 1.04 0.81 0.84 0.57 0.53 0.48 0.60 0.13 0.63 0.58 0.70 0.09 1.15 0.61 0.45 0.47 0.44 0.31 0.14 0.23 0.59 0.65 1.00 0.74 1.53 1.18 0.69 0.58 0.59 0.77 0.76 0.81 0.54 0.85 0.68 0.85 0.20 13 of 22 Regression Coefficients Lagged Revenue 1.41 -0.21 0.67 -0.58 0.33 0.22 0.16 -0.13 0.32 -0.18 -0.03 0.42 0.56 -0.36 1.05 -0.64 0.16 0.41 -0.04 0.16 0.32 -0.37 -0.18 0.74 1.07 -0.31 0.13 -0.01 0.03 0.28 0.53 -0.14 0.04 0.50 0.48 -0.47 0.28 -0.25 1.39 -0.40 0.36 -0.30 0.39 -0.31 0.70 -0.34 -0.23 0.87 1.30 -0.35 0.32 -0.49 -0.31 0.80 0.55 -0.53 -0.08 0.58 0.12 -0.43 -0.43 1.15 1.12 -0.12 0.24 -0.31 0.16 -0.02 -0.13 0.47 0.37 -0.19 0.18 0.21 0.54 -0.12 -0.65 0.88 0.11 -0.24 -0.02 0.22 1.35 0.01 0.98 0.53 0.26 0.50 0.77 -0.03 0.27 0.27 0.14 0.08 0.48 -0.14 0.74 0.20 0.29 0.13 -0.01 0.72 0.32 0.04 0.88 0.44 0.20 0.15 0.33 0.16 0.58 0.07 Section 4 SJ Emp 0.81 0.49 -0.52 0.18 0.20 -0.12 0.29 0.46 -0.70 -0.24 0.32 -0.69 0.93 -0.03 -0.35 -0.07 -0.56 0.38 0.20 -0.48 0.35 0.05 0.12 -1.07 0.08 0.61 -0.34 0.51 -0.82 0.34 -1.06 1.23 0.42 0.16 -0.46 0.36 -0.29 0.12 -0.73 0.14 -0.63 -0.46 -0.89 -0.39 0.15 -0.19 -0.07 0.23 -0.06 -0.09 -0.73 0.00 -0.76 -0.09 -0.42 -0.14 Contemp 1.90 3.20 3.49 23.02 11.04 0.99 2.67 2.16 1.48 3.19 9.49 1.37 1.94 6.56 6.29 2.86 1.39 6.73 2.97 1.87 3.47 6.05 2.36 0.83 1.01 3.02 0.31 1.92 1.30 3.96 0.44 1.70 4.09 3.29 1.38 1.43 1.00 0.33 0.98 3.26 3.20 15.91 3.30 4.28 5.46 6.57 11.57 3.88 5.36 8.76 2.23 3.95 1.86 10.13 1.54 0.57 Regression T-Stats Lagged Revenue 1.26 -0.23 1.85 -1.27 1.69 0.97 4.67 -3.16 3.34 -1.57 -0.03 0.60 1.82 -0.99 2.61 -1.17 0.37 0.91 -0.13 0.51 2.99 -2.82 -0.86 3.29 0.98 -0.36 1.02 -0.06 0.24 2.44 2.01 -0.44 0.07 0.93 3.82 -2.95 0.92 -0.68 1.86 -0.52 1.33 -0.87 2.44 -1.50 2.39 -0.99 -0.25 1.07 2.07 -0.47 1.23 -1.54 -0.61 1.51 1.28 -1.03 -0.14 0.92 0.49 -1.54 -1.56 3.87 1.00 -0.13 1.26 -1.28 0.89 -0.08 -0.30 1.06 0.96 -0.38 0.46 0.51 0.99 -0.19 -1.97 2.75 0.46 -0.90 -0.07 0.77 4.71 0.11 2.03 1.81 0.19 0.67 1.56 -0.11 1.38 1.92 1.62 1.10 1.95 -0.45 3.11 1.24 2.15 1.07 -0.01 1.42 1.57 0.20 2.05 0.80 1.90 1.56 0.42 0.28 1.23 0.16 Section 5 SJ Emp 0.75 1.00 -1.88 3.88 1.40 -0.17 0.69 0.66 -1.23 -0.82 2.15 -2.77 0.84 -0.15 -2.80 -0.16 -0.89 2.20 0.53 -0.57 0.85 0.24 0.34 -1.28 0.10 1.64 -0.55 0.93 -1.07 1.13 -3.50 1.01 1.53 0.75 -0.98 0.55 -0.68 0.19 -2.07 0.50 -2.03 -2.98 -2.45 -0.91 0.39 -1.09 -0.83 0.61 -0.25 -0.58 -1.61 0.02 -0.99 -0.78 -0.75 -0.27 Section 6 Net Effect C+L T-Stat 2.66 1.76 1.68 2.97 0.87 2.97 0.77 14.83 1.24 8.41 0.54 0.38 1.18 2.61 1.84 2.77 0.70 1.05 0.66 1.60 1.14 7.10 0.04 0.12 2.29 1.50 0.81 4.14 0.55 3.42 1.19 2.82 0.62 0.76 1.16 5.99 0.99 2.16 2.43 2.24 1.18 2.78 1.23 4.84 1.27 2.77 0.30 0.24 1.78 1.85 0.92 2.34 -0.18 -0.23 1.18 1.83 0.50 0.59 0.82 2.35 -0.34 -0.82 2.27 1.42 0.85 2.92 0.60 2.26 0.34 0.53 0.81 1.32 0.49 0.81 0.68 0.80 -0.42 -0.85 0.70 1.96 0.63 1.49 2.35 7.74 1.72 3.81 1.78 1.16 1.95 3.84 0.97 4.10 0.72 6.46 1.07 3.34 1.51 5.96 1.05 6.44 0.80 0.80 0.86 3.10 1.73 2.23 0.88 6.55 1.18 0.95 0.78 1.17 r2 516 0.77 0.78 0.90 0.99 0.98 0.54 0.70 0.79 0.81 0.81 0.96 0.89 0.62 0.94 0.96 0.87 0.76 0.92 0.72 0.67 0.83 0.92 0.77 0.67 0.59 0.73 0.82 0.50 0.67 0.78 0.87 0.66 0.85 0.86 0.69 0.68 0.53 0.43 0.79 0.71 0.84 0.99 0.98 0.96 0.96 0.97 0.98 0.86 0.98 0.98 0.90 0.88 0.93 0.98 0.73 0.77 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page54 of 62 Exhibit 2 Intel Section 1 Job Title Years Total of Data Emp-Years 10 149 10 1401 10 81 10 1872 10 53 10 31 10 40 10 951 10 20 10 37 10 113 10 464 10 86 10 29 10 107 10 878 10 42 10 281 10 49 10 340 10 44 10 42 10 157 10 20 10 40 9 72 9 46 9 105 9 18 9 50 9 64 9 172 9 50 9 67 9 17 9 13 9 52 8 283 8 864 8 1526 8 50 8 420 8 288 8 1097 8 92 8 1185 8 119 8 51 8 355 8 52 8 34 8 303 8 258 8 143 8 24 8 612 Section 2 Level Correlation Coeff T-Stat 0.69 2.70 0.68 2.61 0.68 2.61 0.63 2.29 0.62 2.26 0.61 2.20 0.60 2.09 0.59 2.06 0.58 2.04 0.58 2.04 0.57 1.98 0.57 1.97 0.55 1.88 0.48 1.55 0.48 1.54 0.47 1.52 0.46 1.45 0.45 1.42 0.37 1.13 0.34 1.02 0.26 0.78 0.26 0.76 0.23 0.68 -0.28 -0.83 -0.34 -1.02 0.84 4.12 0.78 3.34 0.78 3.31 0.77 3.16 0.75 3.01 0.75 2.98 0.72 2.73 0.61 2.03 0.43 1.26 0.36 1.01 0.17 0.46 0.08 0.22 0.99 17.90 0.98 12.28 0.98 11.20 0.97 10.69 0.97 10.36 0.97 9.49 0.96 8.48 0.96 8.30 0.96 8.16 0.95 7.73 0.94 7.02 0.94 6.66 0.93 6.35 0.93 6.18 0.92 5.96 0.92 5.71 0.92 5.70 0.91 5.51 0.91 5.50 Change Correlation Coeff T-Stat 0.84 3.75 0.96 9.53 0.75 2.96 0.95 8.08 0.46 1.25 0.94 7.06 0.89 5.10 0.93 6.70 0.56 1.66 0.89 4.84 0.73 2.61 0.82 3.86 0.56 1.64 0.90 5.35 0.78 3.31 0.92 6.26 0.87 4.28 0.66 2.34 0.94 7.27 0.92 6.08 0.91 5.82 0.79 3.13 0.40 1.17 -0.32 -0.88 -0.48 -1.45 0.73 2.59 0.77 2.94 0.79 3.13 0.75 2.57 0.85 3.89 0.92 4.79 0.85 3.92 0.70 2.19 0.21 0.49 0.55 1.31 0.58 1.41 0.60 1.81 0.97 9.74 0.98 9.96 0.96 7.28 0.96 7.81 0.97 8.73 0.94 6.39 0.93 5.58 0.89 4.29 0.87 4.03 0.95 6.85 0.78 2.77 0.83 3.30 0.93 4.25 0.79 2.87 0.93 5.53 0.90 4.56 0.92 5.17 0.96 7.81 0.81 3.09 Section 3 Contemp 0.24 0.72 1.20 0.69 0.68 1.28 1.03 0.62 0.30 1.29 0.21 0.84 1.30 0.63 0.67 0.96 0.72 0.30 0.64 0.52 1.04 3.52 0.28 0.07 -0.16 2.09 1.06 1.15 0.57 0.77 3.72 0.82 0.92 0.05 5.91 0.10 1.09 0.86 0.75 0.74 0.91 0.74 0.61 0.33 0.96 0.83 2.48 1.06 0.43 0.95 1.11 0.90 0.79 1.24 1.50 0.44 14 of 22 Regression Coefficients Lagged Revenue 1.11 0.15 0.27 0.06 1.12 -0.39 0.29 -0.05 0.75 0.23 -0.42 0.82 0.47 0.29 0.30 -0.24 -0.27 0.47 0.23 0.09 0.27 0.20 0.93 0.34 2.76 0.18 0.27 0.06 0.81 0.22 0.40 -0.12 0.53 0.35 0.20 0.23 -0.15 0.13 0.16 0.11 -0.03 0.32 1.68 -0.54 0.30 0.16 0.37 0.13 0.33 -0.16 0.76 0.09 0.67 0.54 0.86 0.01 0.15 0.76 0.92 0.37 0.33 -1.05 0.28 0.19 0.94 -0.21 -0.30 0.88 3.81 -2.42 -0.15 0.52 0.34 0.38 -0.01 0.14 0.36 0.18 -0.02 0.19 0.17 -0.09 0.26 0.09 -0.04 0.04 0.09 0.08 0.07 0.18 1.18 0.23 0.75 -0.22 -0.02 0.37 0.46 0.05 1.33 -0.16 1.33 0.17 0.61 0.24 0.15 0.00 0.94 0.02 -0.86 1.10 -0.08 0.40 Section 4 SJ Emp -0.83 -0.09 0.27 0.06 -0.32 -1.13 -0.81 0.25 -0.38 0.05 0.09 -0.18 -0.29 -0.22 -0.33 0.15 -0.76 -0.09 -0.28 -0.21 -0.06 1.64 -0.07 -1.18 -1.00 -1.59 -0.76 0.49 -0.64 -1.82 1.80 -0.33 0.16 -0.96 0.48 -0.29 -0.65 -0.01 -0.24 -0.29 -0.12 -0.37 -0.20 -0.19 0.08 -0.63 -0.28 -1.71 -0.18 -0.76 -0.44 -0.11 -0.13 0.19 -1.27 -0.43 Contemp 0.32 9.38 2.19 8.10 5.31 5.65 2.39 10.29 1.05 2.39 0.34 1.89 2.28 4.22 3.00 4.86 0.50 1.79 5.60 6.64 3.33 6.75 0.52 0.16 -0.30 1.57 1.37 16.00 0.99 0.50 1.60 1.36 3.01 0.13 2.49 0.10 3.50 6.72 12.01 4.74 4.85 14.77 3.39 6.90 2.47 6.14 10.75 1.74 6.58 5.31 2.37 2.48 3.82 6.40 2.85 Section 5 Regression T-Stats Lagged Revenue 2.13 0.30 2.52 0.50 1.58 -0.57 2.53 -0.42 4.85 1.71 -1.31 2.71 0.97 0.62 3.72 -2.57 -0.68 1.35 0.41 0.19 0.52 0.37 1.44 0.72 1.89 0.22 1.40 0.28 3.39 0.89 1.53 -0.43 0.79 0.45 0.88 0.85 -0.83 0.83 1.52 0.96 -0.08 0.84 2.12 -0.79 0.43 0.22 0.68 0.21 0.52 -0.25 0.30 0.04 0.24 0.30 9.29 0.16 0.19 1.43 0.82 0.35 0.23 -0.69 0.33 0.19 1.38 -0.49 -0.54 1.61 2.36 -2.09 -0.12 0.49 1.05 1.09 -0.02 1.05 1.90 2.63 -0.04 1.16 0.29 -0.41 1.66 1.63 -0.12 0.20 1.22 1.57 0.07 0.43 1.86 1.17 1.97 -0.77 -0.02 0.46 3.98 0.68 2.15 0.56 0.24 1.16 -2.06 -0.31 0.87 0.68 0.01 0.06 3.94 2.41 SJ Emp -1.34 -0.62 0.35 0.42 -1.26 -3.26 -1.30 2.31 -0.78 0.08 0.15 -0.27 -0.34 -0.76 -0.77 0.32 -1.06 -0.28 -1.38 -1.61 -0.10 1.94 -0.09 -1.75 -1.38 -0.56 -0.43 3.20 -0.64 -0.91 0.79 -0.26 0.26 -1.59 0.41 -0.29 -0.99 -0.05 -1.88 -0.93 -0.31 -3.65 -0.59 -2.02 0.10 -2.32 -0.58 -1.30 -1.37 -1.46 -0.16 -0.20 0.30 -4.57 -1.42 Section 6 Net Effect C+L T-Stat 1.35 1.70 0.99 6.88 2.31 2.29 0.98 6.08 1.42 5.73 0.86 2.03 1.50 2.17 0.92 7.78 0.03 0.04 1.51 2.05 0.48 0.52 1.77 2.36 4.05 2.12 0.90 3.16 1.48 4.16 1.37 3.79 1.24 0.73 0.50 1.48 0.49 2.03 0.68 4.43 1.01 1.83 5.21 4.68 0.58 0.54 0.44 0.52 0.17 0.16 2.86 0.82 1.73 0.56 2.02 14.45 0.72 0.80 1.69 0.90 4.05 1.75 1.10 0.91 1.86 2.00 -0.26 -0.31 9.72 3.51 -0.05 -0.02 1.43 2.58 0.85 1.38 1.12 5.69 0.72 1.51 1.08 1.69 1.00 6.01 0.56 1.27 0.42 4.06 1.04 0.95 2.01 3.07 3.23 6.38 1.04 0.65 0.89 5.85 2.27 2.44 3.08 1.52 1.58 0.94 1.20 2.18 2.46 0.64 1.47 0.36 1.01 r2 517 0.92 0.98 0.76 0.97 0.97 0.98 0.90 0.97 0.87 0.90 0.81 0.95 0.73 0.90 0.98 0.93 0.95 0.78 0.93 0.96 0.91 0.97 0.43 0.68 0.68 0.81 0.81 0.99 0.89 0.87 0.92 0.75 0.97 0.71 0.96 0.79 0.95 0.97 0.99 0.95 0.94 1.00 0.91 0.98 0.83 0.98 0.99 0.87 0.97 1.00 0.97 0.93 0.82 0.93 0.99 0.93 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page55 of 62 Exhibit 2 Intel Section 1 Job Title Years of Data 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 Total Emp-Years 359 152 98 374 689 203 291 65 318 24 217 201 214 304 266 116 180 1077 155 57 48 64 246 157 33 41 87 62 72 69 10 460 29 53 102 33 324 14 132 34 79 730 1281 355 206 4110 644 108 64 23 82 412 434 97 41 151 Section 2 Level Correlation Coeff T-Stat 0.91 5.42 0.91 5.32 0.90 5.00 0.90 4.94 0.90 4.92 0.88 4.53 0.87 4.41 0.86 4.07 0.84 3.77 0.83 3.68 0.82 3.50 0.82 3.49 0.81 3.36 0.81 3.36 0.80 3.32 0.80 3.30 0.78 3.03 0.77 2.97 0.77 2.92 0.76 2.91 0.76 2.90 0.76 2.90 0.76 2.87 0.75 2.81 0.75 2.81 0.75 2.81 0.75 2.79 0.75 2.77 0.75 2.75 0.72 2.56 0.72 2.51 0.71 2.50 0.71 2.44 0.70 2.38 0.69 2.34 0.69 2.32 0.67 2.23 0.67 2.20 0.65 2.11 0.65 2.10 0.65 2.08 0.56 1.65 0.55 1.60 0.52 1.51 0.48 1.33 0.47 1.30 0.46 1.26 0.45 1.24 0.45 1.24 0.44 1.19 0.43 1.18 0.39 1.04 0.37 0.98 0.26 0.65 0.19 0.48 0.10 0.24 Change Correlation Coeff T-Stat 0.84 3.53 0.67 2.01 0.94 6.09 0.70 2.19 0.94 6.39 0.95 6.80 0.94 6.05 0.65 1.90 0.91 4.83 0.74 2.49 0.96 7.70 0.84 3.43 0.94 6.24 0.52 1.37 0.91 4.94 0.91 4.95 0.88 4.13 0.92 5.43 0.95 6.98 0.54 1.45 0.40 0.99 0.56 1.52 0.93 5.66 0.88 4.13 0.83 3.26 0.39 0.95 0.11 0.24 0.94 6.08 0.37 0.89 0.20 0.46 0.15 0.34 0.91 5.04 0.29 0.67 0.41 1.00 0.66 1.76 0.74 2.47 0.58 1.60 0.55 1.48 0.94 5.98 0.52 1.38 0.85 3.63 0.64 1.86 0.61 1.71 0.79 2.88 0.76 2.59 0.91 4.91 0.88 4.20 -0.42 -1.03 0.74 2.44 0.47 1.18 0.31 0.72 -0.03 -0.07 0.91 5.06 0.13 0.30 0.43 1.06 -0.46 -1.15 Section 3 Contemp 0.59 0.43 1.44 0.58 0.87 2.06 0.64 1.50 0.65 0.68 0.63 0.54 0.62 0.23 0.48 0.62 0.40 0.57 0.93 1.12 0.70 0.81 0.99 0.60 2.33 0.84 0.77 0.71 0.42 0.04 0.79 0.53 0.18 0.47 1.06 1.60 0.29 1.25 0.89 0.59 0.62 0.68 0.53 0.72 0.64 1.00 0.56 0.73 0.77 0.54 0.42 0.18 0.62 0.31 1.06 -0.41 15 of 22 Regression Coefficients Lagged Revenue -0.10 0.50 0.75 0.12 0.21 0.34 0.04 0.53 1.50 0.11 0.25 0.42 0.46 0.13 0.76 -1.51 0.35 0.12 2.29 -0.04 0.17 -0.21 0.30 -0.04 0.24 -0.01 -0.07 0.37 -0.43 0.41 0.34 0.34 0.16 0.13 0.26 0.09 0.43 0.15 1.05 -0.14 0.73 0.12 1.22 -0.14 -0.13 -0.37 0.45 0.59 0.41 -1.63 0.76 0.40 1.02 0.04 0.47 0.37 0.15 0.43 0.06 0.24 1.77 -0.84 0.31 0.03 0.87 0.37 0.78 0.27 2.22 -0.21 0.84 -1.27 0.18 0.23 0.61 0.13 0.41 -0.13 0.38 0.09 -0.05 0.59 0.64 -0.30 0.64 -0.17 0.44 -0.25 0.48 -0.37 0.51 -0.33 0.31 -0.10 0.61 0.36 0.88 -0.32 0.53 0.02 0.30 0.30 0.64 -0.14 0.30 -0.01 0.33 0.16 -0.70 1.54 -0.50 0.48 Section 4 SJ Emp -0.47 -0.29 -0.88 -0.61 -0.83 -0.73 -0.17 1.81 -0.06 -3.04 0.27 0.29 -0.06 -0.43 -0.06 -0.76 0.04 -0.20 0.20 1.02 0.95 0.05 0.25 -0.51 0.25 0.84 0.44 -0.27 -0.35 -0.32 0.75 -0.20 -1.00 0.65 -0.04 1.94 0.05 1.89 -0.37 0.89 -1.07 0.87 0.62 0.06 0.49 0.45 0.24 0.72 0.58 0.79 0.17 0.58 -0.13 0.99 -0.95 -0.43 Contemp 4.46 3.08 2.61 1.66 1.67 43.99 7.62 3.06 4.53 1.06 32.69 3.36 5.00 0.84 4.05 6.72 2.75 5.81 9.92 2.78 4.75 1.51 6.76 1.01 2.80 2.52 1.60 85.90 0.63 0.34 0.58 8.28 0.59 0.89 3.56 8.75 2.30 6.47 5.32 10.55 1.95 5.55 3.75 1.72 3.56 5.46 6.06 0.39 2.46 1.33 0.65 1.06 4.92 2.27 0.70 -2.83 Regression T-Stats Lagged Revenue -0.38 3.44 3.03 0.66 0.25 0.71 0.04 1.49 1.34 0.30 2.43 7.04 3.81 1.42 1.28 -1.46 1.09 0.46 2.31 -0.04 6.94 -8.81 1.40 -0.22 1.47 -0.07 -0.18 1.44 -1.36 2.10 2.40 3.96 0.51 0.48 2.02 0.83 4.50 1.94 1.86 -0.43 3.51 0.65 1.36 -0.12 -0.56 -2.17 0.65 1.45 0.74 -2.32 1.52 1.13 1.67 0.10 58.69 59.28 0.13 0.81 0.35 1.65 1.22 -0.48 3.96 0.37 1.92 1.14 1.19 0.45 2.14 -0.18 5.92 -5.09 1.15 1.57 2.56 0.58 2.31 -0.80 5.92 1.33 -0.11 1.98 5.21 -1.91 4.51 -0.97 1.02 -0.51 2.52 -1.65 3.02 -1.71 3.00 -0.96 0.34 0.25 3.63 -0.96 1.22 0.03 0.36 0.44 3.52 -0.61 2.26 -0.08 2.30 0.93 -0.30 0.82 -3.01 3.66 Section 5 SJ Emp -1.76 -1.03 -0.98 -1.07 -1.87 -9.31 -1.07 3.42 -0.15 -1.88 6.75 0.89 -0.25 -0.91 -0.27 -4.87 0.12 -1.08 1.44 1.65 3.27 0.04 0.84 -0.67 0.76 1.30 0.68 -22.97 -0.32 -1.25 0.26 -1.66 -1.66 0.62 -0.03 5.55 0.20 4.51 -1.43 7.48 -1.94 3.72 2.35 0.08 1.38 1.44 1.35 0.27 1.22 0.97 0.13 1.70 -0.59 3.30 -0.31 -1.77 Section 6 Net Effect C+L T-Stat 0.49 1.50 1.18 3.69 1.65 2.00 0.62 0.51 2.37 3.38 2.32 23.84 1.10 7.90 2.26 5.65 1.00 2.51 2.97 2.25 0.80 22.98 0.84 2.75 0.86 3.82 0.16 0.25 0.05 0.12 0.95 6.30 0.56 1.37 0.83 4.79 1.36 12.17 2.17 2.40 1.44 4.66 2.02 1.58 0.86 3.16 1.06 1.60 2.74 6.78 1.60 2.23 1.79 1.75 1.17 129.23 0.57 0.33 0.10 0.41 2.56 1.06 0.84 7.81 1.05 1.65 1.25 1.31 3.28 2.68 2.44 10.41 0.47 2.02 1.86 5.42 1.30 5.86 0.96 10.05 0.57 1.11 1.32 6.73 1.17 5.18 1.16 1.83 1.13 3.80 1.52 5.74 0.87 5.57 1.34 0.39 1.65 3.75 1.07 1.56 0.72 0.57 0.82 2.81 0.91 4.64 0.65 2.74 0.36 0.11 -0.91 -3.25 r2 518 0.97 0.92 0.94 0.92 0.99 1.00 0.99 0.95 0.98 0.94 1.00 0.88 0.96 0.72 0.98 0.99 0.94 0.98 1.00 0.80 0.95 0.70 0.97 0.94 0.98 0.90 0.62 1.00 0.67 0.76 0.64 0.99 0.93 0.74 0.95 0.99 0.90 0.98 0.98 0.99 0.95 0.97 0.96 0.76 0.90 0.97 0.97 0.74 0.95 0.75 0.47 0.91 0.97 0.97 0.76 0.90 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page56 of 62 Exhibit 2 Intel Section 1 Job Title Years of Data 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Total Emp-Years 17 104 163 283 245 236 18 43 26 116 38 118 331 23 47 58 389 114 78 11 10 154 38 57 14 93 12 61 40 70 81 45 35 8 90 82 31 569 15 17 39 83 123 32 351 10 47 252 162 59 196 38 17 15 100 34 Section 2 Level Correlation Coeff T-Stat 0.09 0.23 0.99 14.44 0.99 13.23 0.98 10.30 0.97 9.67 0.97 8.77 0.96 8.21 0.95 7.10 0.95 6.90 0.95 6.82 0.95 6.61 0.94 6.35 0.94 6.31 0.94 6.28 0.94 6.16 0.94 6.02 0.93 5.80 0.92 5.11 0.91 4.78 0.91 4.77 0.90 4.64 0.90 4.59 0.89 4.28 0.88 4.22 0.88 4.19 0.88 4.10 0.87 3.95 0.86 3.80 0.86 3.79 0.86 3.74 0.86 3.72 0.86 3.70 0.85 3.68 0.85 3.62 0.85 3.55 0.84 3.43 0.84 3.42 0.83 3.32 0.82 3.24 0.82 3.23 0.82 3.22 0.80 3.02 0.80 2.98 0.78 2.78 0.77 2.72 0.76 2.61 0.73 2.42 0.73 2.41 0.73 2.40 0.73 2.38 0.71 2.27 0.71 2.27 0.71 2.22 0.67 2.03 0.61 1.73 0.61 1.73 Change Correlation Coeff T-Stat 0.04 0.10 0.82 2.85 0.85 3.20 0.90 4.19 0.79 2.57 0.68 1.87 0.38 0.82 0.23 0.47 0.26 0.53 0.67 1.83 0.71 2.03 0.25 0.52 0.74 2.23 0.30 0.64 -0.04 -0.08 0.84 3.08 0.58 1.41 0.86 3.44 0.84 3.06 0.56 1.36 -0.21 -0.43 0.89 3.86 0.91 4.34 -0.01 -0.03 0.79 2.58 0.51 1.17 -0.28 -0.59 0.51 1.18 0.46 1.03 0.39 0.84 0.78 2.53 0.69 1.91 0.64 1.66 0.43 0.95 0.67 1.79 0.15 0.31 0.72 2.06 0.32 0.67 0.74 2.23 -0.32 -0.69 0.14 0.27 0.86 3.43 0.53 1.26 0.28 0.58 0.64 1.69 0.96 6.79 0.35 0.75 0.47 1.06 0.50 1.15 0.53 1.26 0.48 1.09 0.31 0.65 0.37 0.81 0.22 0.40 -0.14 -0.27 -0.05 -0.09 Section 3 Contemp -0.56 1.14 0.57 0.89 1.32 1.14 -0.14 0.31 -0.70 0.38 0.38 0.97 0.48 1.69 0.69 0.65 0.81 0.98 0.64 0.52 -0.52 0.70 2.43 0.30 1.41 0.39 1.73 -2.12 0.91 -0.20 1.55 1.92 -0.36 -3.96 1.34 2.16 1.23 0.93 2.26 0.87 -5.32 2.81 0.33 1.45 -0.31 1.00 2.28 -0.88 0.33 -0.14 1.52 -13.06 0.54 -0.74 -0.53 2.16 16 of 22 Regression Coefficients Lagged Revenue -0.38 1.10 1.18 -0.09 0.15 0.26 0.35 0.06 0.61 -0.15 0.88 -0.17 0.87 -0.01 0.93 0.23 0.15 0.73 0.04 0.24 0.23 0.56 1.19 0.03 1.24 0.22 1.01 -0.35 0.12 -0.28 0.16 0.42 0.37 -0.06 1.26 -0.50 0.46 0.57 0.56 0.59 0.03 0.29 -0.35 0.38 1.12 -0.12 1.33 0.01 1.63 -0.08 0.53 0.14 1.98 0.00 -1.62 1.89 0.00 -0.55 -0.03 0.30 -1.09 1.49 1.03 -0.04 -0.35 0.80 -4.09 3.34 0.61 -0.07 1.13 -0.81 1.76 -0.59 0.64 -0.26 1.27 -0.47 2.52 -0.26 -2.53 3.26 0.85 -0.20 0.33 0.45 2.36 -0.44 -0.68 1.13 1.04 0.13 1.32 -0.60 -0.61 0.51 0.19 0.32 -0.74 1.35 0.71 -0.41 -9.42 3.60 0.91 0.53 -0.05 2.31 -0.77 2.84 1.40 -1.80 Section 4 SJ Emp -1.61 -0.01 -0.17 -0.14 0.49 0.10 -0.31 -0.25 -1.01 -0.10 -0.87 -0.07 0.07 1.06 1.02 -0.70 0.32 0.28 -0.63 -0.99 0.55 -0.27 0.31 0.44 0.17 -0.10 0.02 -2.71 0.22 -1.19 -0.68 0.46 -1.47 -7.26 0.26 1.24 0.20 0.11 0.09 1.72 -4.08 0.69 -0.39 -0.57 -1.28 0.47 0.97 -1.11 -0.52 -0.76 0.47 -2.98 0.09 -3.50 -3.35 0.84 Contemp -0.55 1.48 170.84 2.34 3.19 17.95 -0.12 0.21 -0.49 2.45 0.16 3.96 0.32 8.89 4.52 0.37 1.48 9.71 3.30 0.18 -0.13 0.72 1.55 0.14 3.38 0.19 155.52 -2.11 0.56 -0.15 2.23 1.64 -0.46 -2.93 6.07 2.08 0.98 1.39 0.83 0.39 -1.61 2.06 0.17 0.39 -0.19 1.14 7.20 -1.10 0.31 -0.11 0.89 -0.77 0.82 -0.91 3.65 Section 5 Regression T-Stats Lagged Revenue -0.23 0.59 1.03 -0.25 47.89 194.68 1.14 0.36 2.10 -0.84 15.99 -6.89 1.14 -0.02 0.95 0.33 0.12 1.14 0.44 4.00 0.16 0.55 6.27 0.33 0.76 0.30 8.16 -3.65 0.77 -3.15 0.12 0.54 1.15 -0.25 4.95 -2.37 1.03 1.65 0.33 0.46 0.02 0.15 -0.53 0.94 1.02 -0.19 0.80 0.01 1.26 -0.13 0.43 0.15 275.61 -0.38 -1.70 3.49 0.00 -0.99 -0.03 0.65 -2.74 5.13 1.63 -0.07 -0.60 2.23 -3.93 4.56 4.89 -0.77 1.99 -1.91 0.50 -0.27 1.68 -0.95 0.48 -0.55 1.54 -0.33 -1.16 1.98 1.02 -0.32 0.30 0.53 0.82 -0.23 -0.62 1.51 1.18 0.27 8.06 -4.27 -1.37 1.79 0.32 0.72 -0.86 2.25 0.77 -0.57 -0.79 0.82 1.05 0.72 -0.63 4.04 1.41 -7.06 SJ Emp -0.80 -0.01 -80.66 -0.51 1.67 2.33 -0.36 -0.22 -1.09 -1.02 -0.48 -0.46 0.05 7.14 7.38 -0.54 0.87 1.04 -1.35 -0.38 0.17 -0.44 0.28 0.23 0.20 -0.07 3.81 -4.25 0.23 -1.40 -1.23 0.53 -2.45 -5.07 1.70 1.82 0.13 0.23 0.07 0.81 -1.77 0.68 -0.27 -0.22 -1.12 0.52 4.22 -2.35 -0.67 -0.88 0.38 -0.84 0.05 -1.40 1.98 Section 6 Net Effect C+L T-Stat -0.94 -0.37 2.32 1.59 0.71 117.74 1.24 1.91 1.94 2.94 2.02 18.15 0.73 0.49 1.24 0.59 -0.55 -0.21 0.42 1.74 0.61 0.19 2.16 5.16 1.72 0.69 2.70 9.52 0.81 3.08 0.81 0.32 1.19 1.41 2.24 7.23 1.10 1.96 1.09 0.28 -0.48 -0.09 0.34 0.22 3.56 1.80 1.63 0.45 3.04 1.94 0.91 0.31 3.72 205.65 -3.75 -1.93 0.91 0.33 -0.23 -0.11 0.46 0.53 2.95 1.79 -0.71 -0.54 -8.05 -3.88 1.94 5.87 3.29 2.12 2.99 0.65 1.57 1.55 3.53 0.67 3.38 0.89 -7.85 -1.51 3.67 1.84 0.66 0.23 3.81 0.58 -0.99 -0.39 2.04 2.97 3.60 7.82 -1.48 -1.22 0.53 0.33 -0.88 -0.44 2.23 0.88 -22.47 -0.78 1.45 1.22 -1.29 3.56 r2 -0.77 3.92 519 0.70 0.85 1.00 0.97 0.95 1.00 0.87 0.60 0.84 0.99 0.77 0.99 0.87 0.99 0.99 0.84 0.83 0.99 0.98 0.74 0.38 0.92 0.95 0.68 0.96 0.54 1.00 0.99 0.75 0.92 1.00 0.93 0.97 0.98 0.99 0.83 0.75 0.89 0.78 0.95 0.91 0.94 0.78 0.96 0.93 0.97 0.99 0.90 0.89 0.97 0.57 0.48 0.87 0.90 0.99 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page57 of 62 Exhibit 2 Intel Section 1 Job Title Years of Data 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Total Emp-Years 12 16 224 27 52 31 878 88 9 14 15 68 34 11 12 47 24 14 187 10 15 17 201 98 8 222 8 28 72 17 25 131 12 18 402 41 77 12 36 8 93 23 31 53 485 12 44 7 21 15 6 8 22 14 20 18 Section 2 Level Correlation Coeff T-Stat 0.60 1.69 0.60 1.67 0.59 1.64 0.59 1.62 0.58 1.59 0.54 1.45 0.50 1.31 0.49 1.27 0.49 1.26 0.42 1.04 0.39 0.95 0.38 0.91 0.36 0.85 0.34 0.81 0.31 0.74 0.24 0.55 0.12 0.26 0.08 0.17 -0.08 -0.17 -0.18 -0.42 -0.22 -0.50 -0.43 -1.07 0.97 7.68 0.96 7.13 0.96 6.83 0.95 5.98 0.95 5.93 0.93 5.17 0.92 4.79 0.92 4.72 0.91 4.36 0.91 4.26 0.90 4.06 0.90 4.03 0.89 3.99 0.89 3.96 0.89 3.95 0.88 3.76 0.88 3.74 0.87 3.57 0.87 3.55 0.87 3.50 0.85 3.28 0.84 3.09 0.84 3.07 0.84 3.06 0.83 3.00 0.83 2.96 0.82 2.89 0.82 2.89 0.78 2.52 0.78 2.48 0.77 2.45 0.75 2.25 0.75 2.24 0.73 2.16 Change Correlation Coeff T-Stat 0.69 1.90 0.68 1.85 0.33 0.70 -0.59 -1.47 -0.79 -2.62 0.67 1.83 0.59 1.48 -0.79 -2.57 0.61 1.34 0.60 1.48 0.62 1.59 -0.51 -1.17 -0.62 -1.57 -0.14 -0.27 0.60 1.29 0.29 0.61 0.09 0.17 0.24 0.50 0.37 0.78 0.29 0.62 0.53 1.26 0.48 1.10 0.90 3.51 0.97 6.67 0.92 4.03 0.92 4.09 0.72 1.48 0.09 0.15 0.48 0.95 0.83 2.13 0.24 0.35 0.91 3.08 0.78 1.78 0.86 2.35 0.79 2.26 0.90 2.05 0.77 2.12 0.76 1.68 -0.03 -0.05 0.13 0.22 0.56 1.16 0.91 3.87 0.68 1.61 -0.14 -0.25 0.76 2.02 0.62 1.37 0.56 1.17 0.68 1.62 0.38 0.59 0.70 1.39 0.68 1.32 0.97 5.92 0.61 1.34 0.43 0.84 1.00 19.25 -0.06 -0.10 Section 3 Contemp 1.46 0.81 1.58 -2.44 -0.26 2.56 1.85 -0.24 -2.99 5.60 7.30 -4.24 -0.33 3.17 -8.69 2.29 4.06 0.71 -0.10 15.96 1.02 5.55 17 of 22 Regression Coefficients Lagged Revenue 4.18 -1.01 0.54 0.75 0.63 -0.86 0.08 0.44 0.23 -0.06 0.74 0.13 0.75 -0.70 0.32 -0.37 -4.04 3.39 3.82 -2.25 2.86 -2.56 -1.64 1.33 0.65 -0.02 2.67 -1.80 -11.14 12.08 1.15 -0.73 2.08 -1.49 -0.45 0.92 -0.08 0.12 30.79 -17.07 -0.23 0.62 2.37 -2.37 Section 4 SJ Emp -6.31 0.35 0.91 -1.28 -0.07 0.92 0.51 0.19 -3.51 1.36 3.35 -1.91 0.24 1.00 -6.51 0.52 2.58 0.81 -0.82 35.69 -0.63 1.63 Contemp 1.14 0.11 1.44 -0.37 -0.49 0.54 46.85 -2.49 Section 5 Regression T-Stats Lagged Revenue 1.33 -0.55 0.15 0.24 1.03 -2.22 0.02 0.24 0.88 -0.33 0.30 0.06 35.03 -45.73 6.95 -11.05 SJ Emp -2.46 0.07 1.42 -0.25 -0.20 0.26 19.62 3.14 Section 6 Net Effect C+L T-Stat 5.64 1.53 1.35 0.14 2.21 1.32 -2.36 -0.24 -0.03 -0.04 3.30 0.50 2.60 43.87 0.08 0.54 r2 0.99 0.82 0.87 0.75 0.92 0.76 1.00 1.00 2.90 5.09 -0.76 -0.27 0.34 2.25 4.58 -0.62 1.18 0.63 -2.54 -3.84 0.88 -0.05 -0.44 0.88 3.05 -0.79 0.27 0.15 9.42 10.16 -5.88 0.32 5.84 3.07 5.44 -0.72 0.19 0.45 0.96 0.97 0.64 0.93 0.55 0.66 18.07 0.43 -0.08 5.13 0.20 3.35 0.61 20.25 -0.54 -0.12 4.95 -0.09 2.98 -0.66 -14.21 1.27 0.24 -4.84 0.27 -3.45 0.29 15.65 0.70 -0.97 5.17 -0.16 1.37 3.44 6.14 0.27 -0.18 46.74 0.79 7.92 0.65 19.43 0.11 -0.10 5.01 0.10 3.33 0.46 1.00 0.95 0.77 0.98 0.56 0.96 520 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page58 of 62 Exhibit 2 Intel Section 1 Job Title Years of Data 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Total Emp-Years 149 22 10 8 14 10 34 15 9 31 12 8 13 10 40 24 11 10 170 Section 2 Level Correlation Coeff T-Stat 0.71 2.03 0.68 1.86 0.61 1.56 0.55 1.32 0.52 1.20 0.51 1.19 0.51 1.18 0.49 1.14 0.42 0.93 0.41 0.90 0.27 0.55 0.24 0.49 0.23 0.47 0.21 0.42 0.18 0.37 0.09 0.18 -0.02 -0.04 -0.41 -0.90 -0.74 -2.21 Change Correlation Coeff T-Stat 0.98 7.11 0.36 0.66 0.98 8.07 -0.12 -0.18 0.93 2.58 -0.65 -1.47 -0.76 -1.67 0.50 0.99 0.35 0.52 0.16 0.16 -0.80 -2.34 -0.33 -0.61 0.89 2.81 0.67 1.28 0.60 1.29 0.42 0.65 0.58 1.23 -0.20 -0.20 0.06 0.10 Section 3 Contemp 18 of 22 Section 4 Section 5 Section 6 Regression Coefficients Lagged Revenue Regression T-Stats Lagged Revenue Net Effect C+L T-Stat r2 SJ Emp Contemp SJ Emp 521 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page59 of 62 Exhibit 2 Intuit Section 1 Job Title Years of Data 11 11 11 11 11 10 10 10 10 9 9 9 9 9 9 9 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Total Emp-Years 2981 597 293 150 140 170 1571 69 194 57 1073 94 81 758 46 486 113 24 29 114 22 177 206 48 22 7 43 354 58 110 143 26 136 16 378 25 15 16 180 17 120 26 14 145 90 377 167 268 203 31 10 53 118 146 39 Section 2 Level Correlation Coeff T-Stat 0.60 2.26 0.59 2.18 0.54 1.91 0.40 1.29 0.26 0.81 0.78 3.55 0.55 1.85 0.49 1.60 0.40 1.25 0.67 2.39 0.64 2.22 0.59 1.94 0.54 1.70 0.53 1.67 0.17 0.46 -0.01 -0.02 0.80 3.25 0.68 2.25 0.61 1.87 0.46 1.25 0.33 0.87 0.33 0.85 -0.63 -2.00 0.82 3.26 0.74 2.48 0.72 2.33 0.70 2.17 0.65 1.93 0.62 1.75 0.31 0.72 0.21 0.48 0.04 0.10 -0.10 -0.23 -0.33 -0.78 -0.55 -1.49 -0.73 -2.36 -0.83 -3.37 0.95 6.25 0.93 5.09 0.93 4.88 0.92 4.71 0.90 4.15 0.89 3.88 0.86 3.33 0.84 3.14 0.84 3.05 0.84 3.04 0.83 3.02 0.81 2.81 0.81 2.77 0.80 2.65 0.78 2.46 0.75 2.28 0.75 2.27 0.74 2.22 Change Correlation Coeff T-Stat 0.97 12.05 0.95 8.57 0.97 11.05 0.76 3.31 -0.05 -0.13 0.98 10.93 0.79 3.16 -0.30 -0.78 0.76 2.86 0.08 0.21 0.69 2.34 0.57 1.56 0.77 2.94 0.68 2.05 0.74 2.70 0.46 1.28 0.91 4.90 0.72 2.32 0.76 2.62 0.81 3.08 -0.04 -0.10 0.94 5.94 0.13 0.30 0.65 1.73 0.87 3.60 0.86 3.41 0.54 1.28 0.79 2.61 0.71 2.01 -0.45 -1.01 0.90 4.19 -0.21 -0.43 -0.09 -0.18 0.12 0.25 0.73 2.11 0.14 0.28 0.60 1.52 0.98 8.84 0.93 4.44 0.98 8.53 0.71 1.74 0.92 4.10 0.96 6.19 0.62 1.36 0.57 1.20 0.92 4.14 0.96 5.81 0.98 9.39 0.42 0.81 0.91 3.70 0.33 0.61 0.83 2.55 0.85 2.83 0.88 3.28 0.93 4.32 Section 3 Contemp 1.50 1.13 1.50 2.01 0.69 1.08 1.34 -0.19 1.39 0.62 1.15 1.10 1.63 0.34 2.01 1.34 0.44 1.52 2.07 1.40 0.37 2.15 1.48 2.10 2.05 3.15 0.89 1.31 0.76 -0.86 1.05 1.11 1.45 -0.39 1.15 -0.19 0.27 Regression Coefficients Lagged Revenue 1.01 -0.26 1.33 -0.48 1.17 -0.49 1.70 -0.80 1.28 -0.43 -0.18 0.15 1.01 -0.36 0.68 -0.18 1.36 -0.33 0.82 -0.05 0.25 0.30 0.36 0.01 1.09 -0.15 -0.90 0.56 0.71 -0.11 1.60 -0.55 0.22 1.21 2.13 -0.81 2.81 -1.72 1.62 -1.07 0.68 0.51 2.42 -2.11 5.60 -4.14 0.32 -0.98 1.38 -0.10 0.40 0.59 1.50 -0.51 2.39 -0.84 3.57 -1.38 1.35 -0.69 -0.28 0.30 1.49 -0.29 2.96 -1.25 1.05 -1.03 4.61 -3.16 0.70 -0.18 0.93 -0.52 19 of 22 Section 4 SJ Emp -0.34 -0.04 -0.08 -0.27 1.77 0.12 0.02 0.15 -0.44 0.38 -0.41 1.56 0.23 -0.09 -0.23 0.31 -2.04 -0.39 0.60 0.50 -1.04 1.22 2.16 3.09 0.31 -0.24 -0.15 0.14 2.21 2.45 -0.40 -2.38 -0.62 0.99 -0.29 -0.23 2.08 Contemp 10.44 8.97 8.38 4.41 1.41 4.91 13.75 -0.28 1.89 0.53 3.94 2.52 4.23 0.33 2.20 4.91 1.78 0.39 1.19 0.84 0.95 2.70 1.84 6.73 1.40 1.69 2.01 6.24 0.73 -2.20 5.44 0.35 2.56 -0.83 1.93 -0.04 0.62 Regression T-Stats Lagged Revenue 2.21 -1.05 3.99 -3.14 2.13 -1.64 1.72 -1.21 2.27 -0.74 -0.37 0.47 6.15 -3.76 1.47 -0.42 0.78 -0.27 0.91 -0.07 0.68 1.77 0.28 0.01 1.86 -0.49 -0.28 0.37 0.66 -0.16 3.62 -2.13 0.33 2.25 0.24 -0.10 0.79 -0.53 0.48 -0.34 0.84 0.41 1.46 -1.39 1.56 -1.55 1.26 -4.45 1.17 -0.13 0.08 0.14 1.58 -1.42 3.53 -3.28 1.19 -0.94 2.04 -1.87 -0.61 1.27 0.28 -0.06 3.71 -3.39 1.32 -2.01 1.31 -1.27 0.23 -0.07 1.93 -1.36 Section 5 SJ Emp -1.42 -0.29 -0.29 -0.33 2.01 0.23 0.14 0.17 -0.43 0.24 -0.85 2.86 0.46 -0.02 -0.18 0.90 -5.15 -0.06 0.22 0.17 -0.53 0.96 1.36 4.93 0.20 -0.08 -0.52 0.44 1.30 3.56 -1.51 -0.55 -1.23 2.15 -0.30 -0.03 4.48 Section 6 Net Effect C+L T-Stat 2.51 4.97 2.46 5.57 2.67 3.97 3.71 2.77 1.97 2.14 0.89 1.50 2.35 11.01 0.50 0.57 2.75 1.12 1.44 0.92 1.40 2.74 1.47 1.11 2.71 4.12 -0.56 -0.14 2.73 2.07 2.94 4.97 0.66 0.73 3.65 0.29 4.88 0.93 3.01 0.61 1.05 0.99 4.57 1.88 7.08 1.74 2.42 8.37 3.43 2.57 3.54 0.77 2.39 1.78 3.70 5.12 4.33 1.71 0.49 0.54 0.77 1.34 2.60 0.31 4.41 3.45 0.66 0.61 5.76 1.56 0.52 0.08 1.20 1.59 r2 522 0.99 0.98 0.97 0.87 0.71 0.97 0.99 0.52 0.94 0.40 0.89 0.90 0.92 0.51 0.75 0.94 1.00 0.83 0.83 0.74 0.97 0.95 0.93 0.99 0.93 0.95 0.82 0.98 0.87 0.99 0.98 0.83 0.93 0.96 0.86 0.62 0.98 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page60 of 62 Exhibit 2 Intuit Section 1 Job Title Years of Data 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 Total Emp-Years 96 39 91 8 26 26 31 9 8 405 230 14 23 15 8 12 18 78 38 115 37 102 74 24 338 17 6 16 54 98 179 23 19 35 18 15 16 10 38 Section 2 Level Correlation Coeff T-Stat 0.71 2.02 0.71 2.01 0.71 2.00 0.69 1.92 0.67 1.81 0.58 1.41 0.57 1.39 0.54 1.27 0.52 1.22 0.46 1.02 0.43 0.96 0.42 0.93 0.41 0.91 0.40 0.88 0.38 0.82 0.38 0.81 0.35 0.75 0.33 0.70 0.33 0.69 0.29 0.60 0.28 0.58 0.23 0.48 0.07 0.14 0.05 0.10 0.01 0.01 0.00 -0.01 -0.05 -0.09 -0.09 -0.17 -0.12 -0.25 -0.13 -0.27 -0.24 -0.50 -0.26 -0.54 -0.29 -0.61 -0.36 -0.78 -0.38 -0.83 -0.40 -0.87 -0.46 -1.02 -0.47 -1.06 -0.85 -3.22 Change Correlation Coeff T-Stat 0.95 5.47 0.74 1.93 0.49 0.97 0.68 1.62 0.19 0.33 0.28 0.51 0.77 2.08 -0.38 -0.71 0.78 2.14 0.60 1.30 0.69 1.63 0.36 0.67 0.09 0.15 0.17 0.30 -0.03 -0.06 0.44 0.85 0.27 0.49 0.38 0.70 0.85 2.82 0.09 0.15 0.59 1.27 0.66 1.51 -0.05 -0.09 0.48 0.94 0.43 0.82 -0.30 -0.55 -0.13 -0.23 -0.15 -0.26 -0.93 -4.33 0.81 2.40 0.34 0.63 0.09 0.16 0.07 0.13 0.83 2.61 0.22 0.40 0.53 1.08 0.80 2.29 0.69 1.36 -0.92 -3.98 Section 3 Contemp Section 4 Section 5 Section 6 Regression Coefficients Lagged Revenue Regression T-Stats Lagged Revenue Net Effect C+L T-Stat r2 20 of 22 SJ Emp Contemp SJ Emp 523 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page61 of 62 Exhibit 2 Pixar Section 1 Job Title TECHNICAL_DIRECTOR ARTIST_SKETCH ENGINEER_SOFTWARE ANIMATOR_SUPERVISING ANIMATOR ANIMATOR_DIRECTING LAYOUT_ARTIST ENGINEER_SR_SOFTWARE DESIGNER_PRODUCTION ANIMATOR_FIX ART_DIRECTOR ENGINEER_QUALITY_ASSURANCE SYSTEMS_ADMINISTRATOR_SR ARTIST_STORY MGR_DESKTOP_SYSTEMS SYSTEMS_ADMINISTRATOR SCIENTIST_SR TECH_DIRECTOR_SUPERVISING MGR_FINANCIAL_SYSTEMS ENGINEERING_MANAGER ENGINEER_ASSOCIATE ARTIST_GRAPHIC ADMINISTRATOR_TECH_DEPT TECH_DIRECTOR_LEAD_CRTV_SVCS DEVELOPER_RENDERMAN_PRODUCTS TECH_DIRECTOR_CRTV_SVCS SCULPTOR ENGINEER_PRODUCTION_SUPPORT PROJECT_MGR_STUDIO_TOOLS MGR_SYSTEMS_OPERATIONS ENGINEER_RENDERMAN_SUPPORT VP_SOFTWARE_ENGINEERING USER_INTERFACE_DESIGNER DIR_RENDERMAN_PRODUCT_DEV DESIGNER_ENVIRONMENTAL ARTIST_AFTER_EFFECTS TECHNICAL_WRITER TECHNICAL_LEAD_RENDERING ARTIST_STORY_DEVELOPMENT ARCHITECT_SYSTEM TECHNICAL_LEAD_BACKUP_GROUP ART_DIRECTOR_SHADING TECHNICAL_DIRECTOR_LEAD ENGINEER DIR_STUDIO_TOOLS MGR_MEDIA_SYSTEMS ENGINEER_SR_MEDIA_SYSTEM MGR_TOOLS_WORKFLOW ENGINEER_MEDIA_SYSTEMS MGR_QUALITY_ASSURANCE ENGINEER_PIPELINE ENGINEER_RECORDING HR_APPLICATION_DEVELOPER RENDER_PIPELINE_SPECIALIST Years Total of Data Emp-Years 11 1872 11 141 11 503 11 70 11 772 11 44 11 129 11 53 11 62 11 73 11 70 11 54 11 91 11 247 11 11 11 133 11 62 11 70 11 11 11 11 11 11 11 42 11 24 11 11 11 11 11 44 11 22 11 35 10 35 10 10 10 15 10 12 10 20 9 9 9 15 8 25 8 13 8 8 8 20 7 11 7 8 7 22 7 115 7 7 7 7 7 9 7 12 7 7 7 16 7 7 7 16 7 7 7 7 7 19 Section 2 Level Correlation Coeff T-Stat 0.94 8.31 0.91 6.64 0.91 6.41 0.82 4.35 0.81 4.21 0.77 3.57 0.75 3.37 0.74 3.31 0.73 3.20 0.72 3.10 0.70 2.95 0.58 2.16 0.56 2.04 0.55 1.98 0.51 1.79 0.50 1.75 0.50 1.74 0.49 1.67 0.43 1.41 0.42 1.38 0.42 1.38 0.42 1.37 0.38 1.22 0.34 1.09 0.21 0.63 0.19 0.59 0.17 0.52 0.12 0.36 0.50 1.62 0.41 1.28 0.28 0.83 0.26 0.76 0.14 0.40 0.34 0.95 0.17 0.45 0.58 1.73 0.35 0.92 0.34 0.89 0.27 0.70 0.98 10.74 0.96 7.73 0.95 6.70 0.92 5.28 0.85 3.60 0.82 3.21 0.78 2.79 0.76 2.65 0.56 1.50 0.43 1.07 0.25 0.57 0.06 0.14 0.02 0.05 -0.03 -0.06 -0.14 -0.32 Change Correlation Coeff T-Stat 0.89 5.65 0.82 4.06 0.93 7.25 0.89 5.41 0.78 3.53 0.89 5.59 0.79 3.68 0.79 3.59 0.86 4.86 0.75 3.21 0.76 3.26 0.82 4.06 0.81 3.97 0.46 1.48 0.81 3.89 0.29 0.86 0.39 1.21 0.72 2.95 0.84 4.41 0.83 4.20 0.88 5.34 0.63 2.29 0.86 4.72 0.84 4.35 0.79 3.66 0.26 0.75 0.41 1.29 0.12 0.35 0.71 2.65 0.74 2.66 0.68 2.45 0.56 1.79 0.66 2.35 0.78 3.01 -0.43 -1.07 0.73 2.36 0.63 1.60 0.81 3.05 -0.03 -0.06 0.85 3.29 0.90 4.22 0.78 2.52 0.79 2.25 0.76 2.31 0.96 7.09 0.86 3.41 0.18 0.36 0.77 2.39 0.26 0.54 0.61 1.53 0.70 1.96 0.92 4.69 -0.06 -0.11 0.55 1.33 Section 3 Contemp 0.55 1.29 0.95 0.23 0.55 -1.79 0.91 0.70 -0.52 0.53 1.18 0.72 1.07 1.27 1.08 0.74 1.06 1.91 0.91 0.88 0.84 1.15 0.60 0.95 1.01 0.57 0.84 0.77 1.47 1.03 1.10 3.29 0.65 1.66 1.85 -0.34 0.56 1.03 -0.05 1.66 -0.83 0.55 1.04 1.18 2.09 2.94 1.90 1.06 -0.71 1.05 2.22 0.97 0.09 1.06 Regression Coefficients Lagged Revenue 0.31 0.03 1.53 -0.12 0.70 0.01 2.42 -0.22 0.48 0.06 3.71 0.06 1.27 0.15 1.61 0.00 2.50 -0.22 1.60 -0.05 0.70 -0.04 1.11 0.24 0.56 0.12 1.09 0.01 0.42 0.01 1.15 0.06 1.26 -0.09 0.66 -0.15 0.34 0.00 0.24 0.08 0.21 0.04 0.84 0.08 0.02 0.09 0.24 0.06 0.25 0.03 0.92 0.18 0.35 0.07 0.92 0.01 0.68 0.03 0.40 -0.20 0.49 0.02 0.66 0.72 0.35 0.02 0.14 0.12 1.06 0.30 1.69 0.31 0.96 0.85 0.02 0.22 0.57 0.11 0.21 -0.06 4.13 -0.40 1.40 0.06 1.77 -0.06 0.74 0.09 0.29 0.07 0.52 0.05 1.47 0.15 1.29 -0.21 0.69 0.07 0.53 0.16 0.86 0.07 0.26 0.01 1.52 0.50 0.37 0.29 21 of 22 Section 4 SJ Emp -0.02 0.18 -0.25 2.26 -0.82 2.65 0.47 0.79 3.16 0.10 1.55 -0.86 0.70 0.41 1.19 -0.16 0.07 3.54 0.90 0.56 0.53 1.67 -0.13 0.73 1.20 -1.39 1.70 -1.08 -4.53 2.10 -0.34 -9.33 0.43 2.32 -1.74 -2.68 -6.04 2.32 -1.05 2.78 2.52 0.28 -0.58 -0.79 5.04 -1.45 -1.79 -9.01 2.87 -0.85 -0.01 0.02 -0.48 0.00 Contemp 3.08 7.17 6.38 0.18 5.27 -1.16 3.97 1.75 -0.22 0.86 4.33 1.07 5.49 2.96 4.76 1.93 2.05 4.54 5.48 4.82 5.76 3.63 4.06 4.89 4.52 2.12 4.85 1.17 2.67 3.42 2.08 2.20 1.94 3.77 5.23 -0.22 11.18 6.00 -0.10 0.99 -0.40 1.35 5.27 0.89 4.09 7.78 0.65 -0.61 18.35 2.35 509.00 0.03 6.82 Section 5 Regression T-Stats Lagged Revenue 0.63 0.60 4.44 -1.77 1.64 0.14 1.94 -1.18 1.97 1.47 2.92 0.44 3.23 1.90 2.89 0.03 1.55 -0.97 2.81 -0.33 1.74 -0.33 1.77 1.00 2.03 1.65 2.26 0.07 1.69 0.09 2.43 0.51 2.72 -0.49 1.97 -0.89 1.95 0.03 1.10 1.22 1.20 0.67 2.51 0.76 0.10 1.73 1.21 0.87 1.44 0.42 3.91 1.80 2.20 1.10 1.57 0.04 2.62 0.15 1.19 -0.93 1.33 0.06 1.19 1.18 1.17 0.19 0.40 0.55 12.17 6.25 2.03 0.66 17.44 10.07 0.08 2.32 2.80 0.51 0.19 -0.21 1.31 -1.32 1.81 0.93 3.52 0.21 0.72 8.33 3.32 0.72 16.92 3.50 279.12 0.99 5.52 3.33 0.16 0.45 11.24 -0.40 0.31 22.03 0.68 44.62 0.65 15.44 SJ Emp -0.06 0.40 -0.62 1.85 -3.57 2.22 0.79 1.11 1.44 0.10 1.81 -0.75 1.48 0.43 1.88 -0.20 0.06 3.08 2.06 1.12 1.39 1.85 -0.36 1.37 2.01 -1.63 4.11 -0.60 -2.08 1.93 -0.13 -2.35 0.35 1.91 -4.55 -1.00 -16.87 3.35 -0.29 0.75 1.09 0.23 -1.49 0.96 -0.50 -5.53 -3.41 0.72 -6.19 -0.01 3.82 -0.07 0.01 Section 6 Net Effect C+L T-Stat 0.86 1.32 2.82 6.78 1.65 3.78 2.65 5.34 1.03 3.32 1.92 3.94 2.18 5.50 2.32 5.27 1.98 2.14 2.12 4.47 1.89 3.36 1.83 3.79 1.63 4.81 2.36 2.98 1.50 4.24 1.89 2.50 2.31 2.91 2.56 4.81 1.24 4.99 1.12 3.60 1.05 4.31 1.98 3.68 0.62 2.11 1.19 4.01 1.25 4.30 1.49 3.88 1.19 4.57 1.69 1.58 2.15 3.58 1.44 2.70 1.59 2.68 3.95 2.37 0.99 2.17 1.80 3.41 2.92 7.02 1.35 1.15 1.52 20.27 1.05 3.89 0.52 0.90 1.87 1.13 3.30 2.38 1.95 2.38 1.92 2.38 3.45 3.37 2.35 -0.02 1.58 3.09 1.22 1.61 1.43 r2 5.57 1.63 4.23 8.20 1.54 -0.02 21.97 3.38 620.48 0.50 7.54 524 0.82 0.94 0.91 0.89 0.92 0.92 0.92 0.89 0.83 0.83 0.83 0.80 0.90 0.70 0.86 0.62 0.68 0.87 0.88 0.86 0.88 0.79 0.84 0.86 0.85 0.85 0.92 0.39 0.85 0.81 0.67 0.89 0.61 0.88 0.99 0.85 1.00 0.97 0.86 0.83 0.93 0.94 0.98 0.97 0.97 0.99 0.98 0.80 1.00 0.97 1.00 0.53 1.00 Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page62 of 62 Exhibit 2 Pixar Section 1 Job Title ENGINEER_SOFTWARE_TECHSUPPORT ENGINEER_IMAGE_MASTERING TECHNICAL_LEAD_TELECOM ENGINEER_SCREENING_ROOM MGR_IMAGE_MASTERING CGI_PAINTER DESIGNER_CAMERA ENGINEER_APPLICATIONS FINANCIAL_APPS_DEVELOPER MGR_SR_PROJECT_STUDIO_TOOLS LAYOUT_ARTIST_LEAD MEDIA_SYSTEMS_COORDINATOR Years of Data 7 6 6 6 6 6 6 6 6 6 6 6 Total Emp-Years 7 8 6 6 6 65 6 6 6 6 6 8 Section 2 Level Correlation Coeff T-Stat -0.86 -3.77 0.92 4.74 0.92 4.65 0.88 3.76 0.88 3.69 0.74 2.20 0.60 1.50 0.52 1.22 0.46 1.03 0.46 1.03 0.42 0.93 0.12 0.24 Change Correlation Coeff T-Stat 0.01 0.03 0.54 1.13 0.75 1.97 0.79 2.24 0.78 2.18 0.53 1.07 0.76 2.00 0.57 0.98 0.80 2.31 0.21 0.31 0.27 0.49 -0.35 -0.66 Section 3 Contemp -0.51 Regression Coefficients Lagged Revenue 0.02 -0.01 22 of 22 Section 4 SJ Emp 2.20 Contemp -0.63 Regression T-Stats Lagged Revenue 0.07 -0.03 Section 5 SJ Emp 1.07 Section 6 Net Effect C+L T-Stat -0.49 -0.55 r2 525 0.58 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page1 of 40 IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA SAN JOSE DIVISION CONFIDENTIAL – TO BE FILED UNDER SEAL SUBJECT TO PROTECTIVE ORDER IN RE: HIGH-TECH EMPLOYEES ANTITRUST LITIGATION No. 11-CV-2509-LHK _____________________________________ THIS DOCUMENT RELATES TO: ALL ACTIONS REBUTTAL SUPPLEMENTAL EXPERT REPORT OF EDWARD E. LEAMER, PH.D. July 12, 2013 526 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page2 of 40 TABLE OF CONTENTS I.  Introduction, Assignment, and Summary of Conclusions ..........1  A.  My Opinions ................................................................................... 1  B.  Dr. Murphy’s Opinions and My Specific Responses ................................ 2  C.  Summary of My Responses ............................................................... 4  II.  Dr. Murphy Considers Only Isolated Individual Cold Calls, and Ignores the Effects of Bursts of Cold Calls and Heightened Threats of Future Cold Calls That Would Have Occurred Absent the Illegal Agreements ...................................7  III.  Contrary to Dr. Murphy’s Opinion, the Presence of Individual Effects, Even Large Ones, Leaves Room for Common Factors Affecting All ............................................................................ 11  1.  Defendants’ Use of Salary Range Targets is Consistent with My Title-Focused Analysis ............................................................... 13  2.  Google’s Big Bang Demonstrates that Dr. Murphy’s Individual-Level Approach Hides Common Impact ................................................ 13  IV.  Dr. Murphy’s Claims about Statistical Errors are False ............16  A.  Correlations are Informative ........................................................... 17  B.  There is No “Reflection Problem” in My Analysis ................................. 18  C.  Dr. Murphy’s Theory of Regression toward the Mean Requires Randomness That Is Not Part of the Compensation Determination in the Technical Class ........................................................................ 19  D.  Dr. Murphy’s Study of Chicago Daily Temperature is Flawed and Irrelevant ..................................................................................... 21  V.  Dr. Murphy’s Analysis of “Sharing” in the ACS Data is Flawed and Unreliable ......................................................................... 21  A.  The ACS Data Suffer from Critical Measurement Errors That Make Them Unsuited to the Analysis that Dr. Murphy Has Carried Out .......... 22  1.  ACS Survey Practices Create Potentially Serious Response Errors .... 22  2.  The ACS Annual Data Mix Two Years of Information ....................... 23  B.  The ACS Correlations Are Much Lower Than the Title-by-Title Correlations Computed with the Defendant Payroll Data...................... 24  C.  Other Flaws in the ACS Data for Dr. Murphy’s Analysis ....................... 28  VI.  Dr. Murphy’s Concerns about Common Effects Excluded from My Work Are Strictly Hypothetical ........................................... 28  i Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 527 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page3 of 40 VII.  Conduct Regression................................................................. 30  VIII. Almost All Employees Received Supplemental Compensation or Salary Increases ................................................................. 31  APPENDIX A.  Defendants’ Use of Salary Ranges .......................... 33  ii Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 528 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page4 of 40 CONFIDENTIAL I. July 12, 2013 Introduction, Assignment, and Summary of Conclusions 1. I have been asked by the Plaintiffs to comment on the Supplemental Report of Dr. Kevin M. Murphy dated June 21, 2013 (“Murphy Supplemental Report”), and in particular to say whether any of the opinions expressed by Dr. Murphy cause me to change the conclusion reached in my Supplemental Report dated May 10, 2013 (“Leamer Supplemental Report”), that the alleged restraint of competition by the Defendant firms suppressed compensation to all or nearly all members of the proposed Technical Class. They do not. Exhibit 1 lists materials I have relied upon in addition to the materials cited in my previous reports. A. My Opinions 2. Dr. Murphy has distorted my opinions, and to set the record straight I offer a summary in this section. 3. The hypothesis that underlies my study of the defendants’ payroll records is that the non-compete agreements prevented a burst of actual cold calls from happening and also eliminated the threat of future cold calls between the agreeing parties. I have never offered the opinion that the effect of a single isolated cold call would necessarily increase compensation for every employee in the Technical Class. My opinion is that the information conveyed by each cold call reinforces the information in other cold calls, making the effects “superadditive”, meaning that the effect of a burst of cold calls is more than the sum of the parts. My opinion is that, absent these illegal agreements, bursts of cold calls and a heightened threat of cold calls would have been met with increases in compensation for all or almost all individuals in the Technical Class. 4. Cold calls that were suppressed by the non-compete agreements were likely more concentrated in some titles than in others. I also have the opinion that the firms’ assessments of the threat of cold calls—and their responses to those threats—would have been broader than just the cold calls that actually would have happened in the but-for world. Because the cold calls in the but-for world would have been more concentrated in some titles than in others, and because any broad response to the burst of actual cold calls and the threat of future cold Page 1 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 529 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page5 of 40 CONFIDENTIAL July 12, 2013 calls would have occurred through Defendants’ title-based pay systems, I have chosen to use the title averages as the basis for my data work to help define the class. In addition, title averages tend to be less affected by the idiosyncratic individual variability which is irrelevant to a finding of common impact throughout the Technical Class. 5. As a measure of the tightness of the ties that bind titles together, I have reported correlations of both the levels of compensation and the percent changes in compensation of each title vis-à-vis the rest of the firm’s Technical Class absent the title in question.1 My opinion is that this correlation evidence supports and is supported by the abundance of documents and testimony that reveal the importance of internal equity issues for firms generally and for these firms in particular. 6. Correlations need not be solely the consequence of internal equity concerns that work to tie compensation together, but may also arise partly from other factors that are common across titles. I have therefore controlled for what I regard to be the two most powerful common forces–firm performance (measured by firm revenue) and external market forces (measured by the employment levels in the San Jose MSA). In the estimated model that I have presented, these forces have different impacts on the various titles but these forces do not explain away the substantial correlation between title compensation and the firm’s overall Technical Class compensation. B. Dr. Murphy’s Opinions and My Specific Responses 7. In his Supplemental Report, Dr. Murphy presents the following opinions:2 a. Dr. Murphy claims my analysis must, but cannot, demonstrate that “a raise to employees who receive a cold call would increase compensation even to other employees with the same job title.” RESPONSE: This comment refers to the effect of a single cold call, 1 Leamer Supplemental Report, pp. 10-12. 2 Murphy Supplemental Report, pp. 1-2. Page 2 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 530 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page6 of 40 CONFIDENTIAL July 12, 2013 not to the relevant hypothetical: bursts of cold calls and a heightened threat of future cold calls. b. Dr. Murphy claims “correlations of average compensation by job title with overall average compensation for the proposed Technical Class cannot show that raises for some employees necessarily would result in raises for some or all.” RESPONSE: This also refers to the wrong hypothetical. For the relevant hypothetical of bursts of cold calls and elevated threats of cold calls, correlations of compensation, correlations of changes in compensation, and the contemporaneous and inter-temporal relationships in compensation across the proposed Class all strongly support the conclusion that Defendants’ compensation is structured such that it would make the impact of the non-compete agreements common to the proposed Class. c. Dr. Murphy claims that “neither [my] correlation analysis nor [my] regression analysis can distinguish a ‘somewhat rigid’ compensation structure” because they fall “victim” to two well-known statistical fallacies and that these fallacies “virtually guarantee” my sharing regression results. RESPONSE: The “reflection” and “regression-to-the mean” fallacies do not apply to my work. The first fallacy amounts to the familiar statement that correlation is not causation, but I have never claimed otherwise. It also amounts to the familiar generic fact that estimated regression models change when additional variables are added into the equation. I am fully aware of this fact, and the reason I added additional variables into my correlation analysis is to determine the extent to which the observed correlations are due to two potentially important common factors. Dr. Murphy, rather than being helpful, merely states what is obvious: that there theoretically might be other variables one could study. If that were all that is necessary to invalidate a regression, no one could ever estimate a regression with nonexperimental data. The second, “regression-to-the-mean,” fallacy depends on the presence of substantial randomness in the data set; Defendants do not pay their employees in a substantially random way. Page 3 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 531 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page7 of 40 CONFIDENTIAL July 12, 2013 d. Dr. Murphy claims that I do not “establish that the proposed class is properly defined.” RESPONSE: I have provided evidence that supports the proposed class. Dr. Murphy has provided no evidence useful for an alternative definition of the boundaries of the class. e. Dr. Murphy implies that I needed to “improve the accuracy” of the conduct regression. RESPONSE: My conduct regression demonstrates a reliable methodology capable of measuring damages on a class-wide basis. The regression model I proposed utilizes the variation in the data and is accurate enough to distinguish impact year-by-year and defendant-bydefendant. C. Summary of My Responses 8. Dr. Murphy’s first four arguments boil down to claims that 1) the presence of substantial individual effects implies that there cannot be a common firm-wide internal equity component to compensation, and 2) the statistical evidence that I find of the importance of internal equity and sharing as a common factor in compensation is the result of something else—either some other common factor(s) he fails to identify or a statistical anomaly. I discuss his final issue regarding my conduct regressions below. 9. There are certain similarities in how Dr. Murphy and I view Defendants’ compensation setting and important differences: a. Dr. Murphy and I both agree that there are individualized factors in individual compensation (though he exaggerates their importance and downplays the extent to which Defendants take a systematic approach to adjusting compensation in response to those individualized factors within their firm-wide compensation structures); b. Dr. Murphy and I both agree that market factors play a role in compensation. It is for this very reason that I included market factors in my sharing regressions to control for these effects; and Page 4 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 532 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page8 of 40 CONFIDENTIAL July 12, 2013 c. Dr. Murphy and I both agree that there may be common factors within the firm—not related to the non-compete agreements—that may influence employee compensation. Firm performance is probably the most important common factor and the only one identified by Dr. Murphy. I included firm revenue to control for such effects. While Dr. Murphy is silent about what other factors may tie firm-wide employee compensation together, the statistical, theoretical and documentary evidence I have presented establishes that internal equity and the use of a salary structure by these firms is also an important factor. 10. In this Report, I address Dr. Murphy’s claims. First, I point out that Dr. Murphy incorrectly focuses on the reaction that firms make to individual isolated cold calls, and he ignores the response that firms make to bursts of cold calls. He also ignores the broad preemptive responses that firms make to the threat of cold calls, for example, the across-the-board increase in base salaries for Google employees in 2011. 11. Second, Dr. Murphy incorrectly acts as if the data evidence has to stand on its own in determining the class.3 Wise interpretation of non-experimental data needs to be sensitive to the context in which the data were generated, and persuasive conclusions from the numerical data require the information in the numerical data and the documents to be aligned. The data in this case support and are supported by substantial documentary and testimonial evidence including but not limited to the following: a. The non-compete agreements covered all employees in the defendant firms; b. The CEOs of the defendant firms confirmed the broad and substantial impact that the cold calling was likely to have had by the fact that they personally got involved in these illegal agreements; c. HR documents of all these firms confirm the importance of internal equity in the setting of compensation levels; Deposition of Kevin Murphy Vol. 2, July 5, 2013 at p.443:12-14, “The court can read the documents. I’m an economist. I got no particular advantage of reading documents.” 3 Page 5 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 533 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page9 of 40 CONFIDENTIAL July 12, 2013 d. Depositions of HR professionals within these organizations also confirm the importance of internal equity; and e. There is substantial literature in economics which Dr. Murphy ignores regarding the importance of internal equity in the compensation setting, brought forward by my previous reports and Dr. Hallock.4 12. 13. Moreover, a direct causal inference such as the one alluded to by Dr. Murphy requires experimental evidence like a clinical trial in which the treatment is randomized, but as Dr. Murphy surely knows, there is nothing like that in this data set. Accordingly, we analyze correlations, which are routinely used by economists to draw causal conclusions when supported by compelling frameworks and complementary information. The fact that all or almost all of the titles are tied closely together is evidence that the impact of the agreements would spread at least throughout the Technical Class. 14. 4 Only by incorrectly focusing on the impact of individual isolated cold calls and by incorrectly ignoring the substantial documentary and testimonial evidence is Dr. Murphy able to issue the challenge that I have not shown the causal chain linking a cold call to compensation of the recipient and to anyone else. This challenge is only marginally relevant for the bursts of cold calls prevented by the agreements and irrelevant for the preemptive compensation increases that firms can make to prevent cold calls from happening and to mitigate the damage that attractive cold calls might cause. In neither case is the impact spread through the firm per the causal chain to which Dr. Murphy refers. Third, the fallacies that Dr. Murphy identifies simply do not apply to this context. First, I anticipated and addressed the potential “reflection problem” by analyzing correlations between non-overlapping sets of employees. I used these correlations to assess whether these titles have compensation levels that are tied together, and in the face of competitive pressure they are likely to remain tied together. Second, I reject Dr. Murphy’s notion that compensation is subject to the same kind of randomness as the daily weather in Chicago. For that reason, Dr. Murphy’s concerns about “regression toward the mean” are unjustified by Expert Witness Report of Kevin F. Hallock, May 10, 2013 (“Hallock Report”). Page 6 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 534 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page10 of 40 CONFIDENTIAL July 12, 2013 the circumstances and not connected to any factual evidence that describes how these firms chose compensation levels. Employee compensation is the outcome of a deliberate decision making process followed by the firms and is not subject to the degree of randomness that Dr. Murphy suggests. 15. 16. To further suggest the existence of omitted variables, Dr. Murphy also uses data on U.S. compensation by occupation collected by the American Community Survey. It is evident that Dr. Murphy has not seriously studied these ACS data and presumes that his cursory look is enough. In the brief period of time I have had to review this work, I have uncovered numerous serious errors both with the data and with the way they have been (mis-)interpreted by Dr. Murphy. The ACS-based work of Dr. Murphy is irrelevant and unreliable. 17. II. Fourth, Dr. Murphy again emphasizes that left-out variables can cause problems with regression analysis. However, he has not put forward any specific example of such an effect. This argument remains entirely hypothetical and entirely unconvincing. While I have controlled for the external and internal non-sharing effects that he claims pollute my results, he has not presented any evidence showing that omitted non-sharing external or internal effects are actually responsible for the positive sharing in my results. He has not elaborated on what his claimed ‘other common factors’ could be. Nor has he proposed any test of whether my results are flawed. Fifth, the conduct regressions in my Report and Reply Report illustrate a method of computing damages for the Technical Class and are capable of providing reliable estimates of Defendants’ under-compensation of their employees. Dr. Murphy Considers Only Isolated Individual Cold Calls, and Ignores the Effects of Bursts of Cold Calls and Heightened Threats of Future Cold Calls That Would Have Occurred Absent the Illegal Agreements 18. Dr. Murphy proposes that all impact begins with individuals who would have been cold-called but-for the non-compete agreement. He insists on proof of a causal chain linking other employees to the ones that would have had a cold call. This theory is a strictly reactive theory, i.e., any compensation-setting reaction Page 7 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 535 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page11 of 40 CONFIDENTIAL July 12, 2013 by management is in response to a specific cold call. This view is clearly stated by Dr. Murphy [emphasis added]: 8. Dr. Leamer’s empirical analysis focuses on whether changes in average compensation for various job titles are correlated with movements in the average compensation level for the proposed class as a whole. He does not examine whether changes in compensation at the individual level, which is where the initial impact of any cold call would occur, necessarily cause changes in compensation for all or nearly all employees in the same job title or for the proposed class as a whole.5 19. And: 22. […] Even if, as Dr. Leamer claims, a “Large Share of [Job Title] Change Correlations are Positive,” it does not follow that Defendants have compensation structures that require them to change compensation for all, or nearly all, class members if they raise one employee’s compensation in response to a cold call.6 20. This theory of Dr. Murphy’s presumes incorrectly that the impact of cold calls is additive, as if a burst of 1,000 cold calls were equivalent to 1,000 times the effect of a single isolated cold call. On the contrary, the information in one call would tend to reinforce the information in others, and the effect is consequently likely to grow rapidly with the number of calls (or to use Dr. Murphy’s preferred term, “super-additive”). Given this aspect of the cold-call effects, it is my opinion that the high degree of historical co-movement in compensation across titles supports the conclusion that the response of these firms to a burst of cold calls would have spread at least to the edge of the Technical Class. 5 Murphy Supplemental Report, ¶ 8. 6 Murphy Supplemental Report, ¶ 22. Page 8 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 536 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page12 of 40 CONFIDENTIAL July 12, 2013 21. Another avenue for the effect of the agreements—and perhaps the most important one—is their disruption of proactive strategies in response to cold calls. By completely eliminating the threat of cold calls between the agreeing parties, the agreements also completely eliminated the need for management to make a preemptive response. The greatest error of Dr. Murphy’s response is that he ignores completely the avenue of effect through preemptive responses to threatened cold calls in the form of broad increases in compensation intended both to suppress the cold calling rate and to make the cold calls that nonetheless occur relatively unimportant. 22. For studying the case of preemptive responses to threatened cold calls, the job of the analyst is not to trace out the impact of cold calls from individual to individual or from title to title but instead to identify the sets of individuals that management would likely include for preemptive increases in compensation. These preemptive responses apply not just to those workers who are experiencing increased external competition but also to all the others who would be included because of internal equity considerations. The historical correlations help to identify the subset of titles that would likely be excluded – those titles that historically had compensation levels that were unconnected with the rest of the firm. 23. My theory of damages includes the reaction to a burst of cold calls and also the broad preemptive responses that management would make to the threat of cold calls.7 There is substantial evidence in this case for the occurrence and importance of these types of responses. Some examples already offered by Dr. Hallock are: [Intuit] 8 [Google] 7 Leamer Supplemental Report, ¶ 15. 8 Deposition of Mason Stubblefield, Intuit, March 29, 2013 at p. 70. Page 9 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 537 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page13 of 40 538 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page14 of 40 CONFIDENTIAL July 12, 2013 24. 25. III. Preemptive adjustments are intended to minimize the damage that attractive cold calls might cause to the behavior of not just the individuals who (in the but-for world) would have been cold-called—but also the broad swath of employees whose loyalty might be diminished by knowledge of better opportunities via cold calls received by their colleagues. In an earlier report, Dr. Murphy pointed out that the amount of movement between the Defendants was never very great in any of the years for which Defendants have provided payroll records, and he has used that as an argument that the agreements could not have had much effect.13 However, the fact that the CEOs of these firms got involved in this non-compete scheme means that the cold calls prevented by the agreements potentially had serious systemic effects even if there wasn’t much movement of employees. The CEOs who formed these agreements must have expected that the impact was not just through the loss of an individual employee or two consequent to a cold call but through the broad increased threat of movement and the reduced worker loyalty that can be created by knowledge of better opportunities elsewhere.14 Contrary to Dr. Murphy’s Opinion, the Presence of Individual Effects, Even Large Ones, Leaves Room for Common Factors Affecting All 26. Dr. Murphy’s first opinion is: The variation in individual compensation, which Dr. Leamer’s analyses ignore, shows that a raise for one or some does not necessarily cause a raise for all or nearly all.15 13 Murphy Report, pp. 18-20, and Leamer Reply Report, pp. 11-13. As Pixar’s President Ed Catmull observed in an email to a Disney executive: “Every time a studio tries to grow rapidly, it seriously messes up the pay structure . . . by offering higher salaries to grow at the rate they desire, people will hear about it and leave.” PIX00000229. 14 15 Murphy Supplemental Report, p. 2. Page 11 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 539 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page15 of 40 CONFIDENTIAL July 12, 2013 27. This view is completely off-point. To determine whether the employees in the proposed Technical Class were harmed by the non-compete agreements, I do not have to demonstrate (nor do I believe) that a “raise for one or some does necessarily cause a raise for all or nearly all.” My opinion is that the documents and the data support the conclusion that the response to the bursts of cold calls prevented by the agreements and the response to the threat of cold calls prevented by the agreements would together have had effects that extended throughout the proposed Technical Class, increasing compensation in the butfor world for all or almost all of the proposed class members. The reason for this is that both the response to bursts of cold calls and, even more, the response to the threat of cold calls would surely raise internal equity concerns that would spread the impact to the edge of the class. 28. My work is based on the assumption that there are individual effects in compensation and there are also common firm-wide effects that tend to tie the individuals together. My opinion is that the class should include (1) all individuals who were in the group of probable recipients of the burst of cold calls, and (2) all who were in the group of individuals who would have experienced heightened risk of cold calls and also (3) those individuals who are linked to the first two groups by internal equity considerations. 29. The payroll data that I have studied cannot be used to identify the first two affected groups, but the written record indicates that these individuals are very likely concentrated inside the Technical Class. It is possible that the increased cold calls and heightened threat of cold calls extended very broadly, affecting all or almost all members of the Technical Class, but I do not rely on that possibility. What I rely on is that the forces of internal equity are very broad and likely to extend the impact of the anti-cold-calling agreements to all or almost all members of the Technical Class. The statistical task is to identify the common factors in the individual data and to apportion these common factors between internal and external forces. 30. As I explained in my report, one of the reasons that I chose to work with titlebased averages is that averaging across the individuals in any title can reduce the Page 12 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 540 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page16 of 40 CONFIDENTIAL July 12, 2013 individual idiosyncratic effects and make the common factors more evident.16 The other reason for using a title-based data set is that it is the title structure that allows senior management to control compensation throughout the firm. The right class definition consequently should be title-based, and I have explored the technical-class titles to determine if there are any titles with average compensation packages that are not tied internally to compensation packages in other titles. I have not found any titles that are immune to the forces of internal equity and that should be excluded from the class. Dr. Murphy has not made any attempt to argue that any titles should be excluded. 1. Defendants’ Use of Salary Range Targets is Consistent with My Title-Focused Analysis 31. This approach is supported by Defendants’ use of target salary ranges in determining their employees’ base compensation. As shown in Appendix A, the target salary range data17 matched with their payroll data indicates that Defendants conformed their employees’ compensation to those ranges percent of the time (employee-years for which data were available). 2. Google’s Big Bang Demonstrates that Dr. Murphy’s IndividualLevel Approach Hides Common Impact 32. 16 Dr. Murphy claims that the search for impact should begin at the level of individual compensation. A closer look at the Google data, including the 10 percent across-the-board increase that occurred on January 1, 2011, illustrates why the title is an appropriate level of aggregation for this analysis: the inherent noise in the individual level data tends to drown out the signal of the internal pay structure we are trying to detect. I will demonstrate here that individual variation in the data masks even such a sweeping common phenomenon as the Google Big Bang, which we know occurred. An analyst working with this data will do much better justice to such common phenomena by studying the titles as opposed to the individual employees. Leamer Supplemental Report, p. 6. This analysis is based upon salary range data produced by Adobe, Apple, Google, and Intel. Intuit did not produce adequate data, and thus was not included in this study. 17 Page 13 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 541 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page17 of 40 CONFIDENTIAL July 12, 2013 33. Table 1 reports summary statistics for year-by-year percent increase in base compensation for Google’s employees in the Technical Class. These include the mean, or average, increase in base compensation and the standard deviation, a measure of the variability in that increase across Technical Class employees. According to Dr. Murphy’s theory that making a company-wide change in pay largely precludes individual variation, he would apparently expect something like a 10 percent mean and a 0 standard deviation for the percent change in base salary for the period that includes January 1, 2011 (December 31, 2010 to December 31, 2011). This would indicate that all effects are common effects and there are no individual effects. However, the mean for the year 2011 is percent, , and the standard deviation is percent. The standard deviation in 2011 is similar in size to all the other years, and usually exceeds the mean. This demonstrates that there was very substantial individual variation in all years, even 2011 - the year in which we know there was a large common factor. 34. Table 2 provides the same information about total compensation, which also shows variability even in the year 2011 in which we know there was a common factor affecting compensation. Hence, the presence of individual variation, such as seen in Table 2 and emphasized by Dr. Murphy, is entirely consistent with common impact. Page 14 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 542 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page18 of 40 CONFIDENTIAL July 12, 2013 Table 1 Google Base Salary Increase Technical Class Employees with Google for the last Two Years Year Mean Median Max Min Std. Dev Obs. 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 All Source: Google Employee Compensation Data Table 2 Google Total Compensation Increase Technical Class Employees with Google for the last Two Years Year Mean Median Max Min Std. Dev Obs. 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 All Source: Google Employee Compensation Data Page 15 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 543 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page19 of 40 544 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page20 of 40 CONFIDENTIAL July 12, 2013 “reversion toward the mean.” His claims are false and my work does not suffer from either of these problems. A. Correlations are Informative 37. Dr. Murphy’s second opinion is a repeat of the familiar statement that “correlation is not causation.” In the language of economics, Dr. Leamer implies that his correlations reflect causality – that a change in one variable leads to or causes a change in the other – but he then offers only evidence of co-movement. However, correlation, or similar movement, in average job-title compensation does not establish the necessary causation to support Dr. Leamer’s theory.18 38. 18 19 Correlations are an accepted part of the scientific enterprise in economics and economists routinely study them in pursuit of knowledge. For example, a textbook cited by Dr. Murphy describes correlation as a “measure… of the strength of a relationship between two random variables.”19 Moreover, in a published article, Dr. Murphy uses correlation analysis to establish a “strong link between… crack [cocaine] and increased homicide rates by the young.”20 This article also makes use of a simple regression formulation despite recognizing that “[i]t is possible that omitted variables… affects both crack and outcomes like homicide.” In this same article Dr. Murphy and his co-authors use aggregation which “increases the signal-to-noise” ratio in a fashion similar to my averaging across individuals to reduce the noise in individual compensation.21 Murphy Supplemental Report, ¶ 21. Casella G. and R. L. Berger, Statistical Inference, Cengage Learning; Second Edition (June 18, 2001), p. 169. Fryer, R. G., P. S. Heaton, S. D. Levitt and K. M. Murphy, “Measuring crack cocaine and its impact,” Economic Inquiry, Vol. 51, No. 3, (July 2013), pp.1651-1681. 20 “[B]ecause each of our individual proxy measures is quite noisy, combining them into a single index substantially increases the signal-to-noise ratio” Fryer, R. G., P. S. Heaton, S. D. Levitt and K. M. Murphy, “Measuring crack cocaine and its impact,” Economic Inquiry, Vol. 51, No. 3, (July 2013), pp.1651-1681. 21 Page 17 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 545 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page21 of 40 CONFIDENTIAL 39. July 12, 2013 Absent experimental evidence, what we have to rely on are simple correlations and regressions (“partial” correlations which hold fixed other potentially important confounding effects). I have provided both. B. There is No “Reflection Problem” in My Analysis 40. 41. Still, there remains an issue regarding direction of causation which would more accurately be described as a “simultaneity problem.” As an illustration, consider the compensation of just two distinct individuals. Here there is no Manksi-type average group behavior to worry about and there is no way to use the correlation between A and B to distinguish the possibility that A affects B, or B affects A, or some outside force “causes” both A and B. 42. 22 Dr. Murphy uses Professor Manski’s somewhat vague definition of what he calls the “reflection problem” which is: “This identification problem arises because mean [average] behavior in the group is itself determined by the behavior of group members. Hence, data on outcomes do not reveal whether group behavior actually affects individual behavior, or group behavior is simply the aggregation of individual behaviors.”22 I have to some extent anticipated this issue by comparing compensation in each title, not simply with the Technical Class overall, but with the Technical Class overall with all the individuals in the title removed. This means I am comparing completely non-overlapping sets of individuals in each of my regressions. Correlations are informative regardless of the direction of causation, especially for the preemptive theory in which the issue is whether titles are “tied together.” However, even for causation, as Manski suggests,23 it is possible to use lagged values to see if A data tend to be followed by similar B data. A temporal ordering such as A routinely preceding B is known as “Granger causality.”24 As Murphy Supplemental Report, ¶ 35. 23 “One alternative supposes that the researcher observes the dynamics of a process in which individual behavior varies with lagged rather than contemporaneous values of group mean behavior.” Manski, C. F., “Economic Analysis of Social Interactions,” Journal of Economic Perspectives, Vol. 14, No. 3 (Summer 2000), pp. 115-136. 24 Enders, W., Applied Econometric Time Series, Hoboken: John Wiley & Sons, Inc., Third Edition (2010), pp. Page 18 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 546 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page22 of 40 CONFIDENTIAL July 12, 2013 the adjective suggests, this is an indication of causality (though not definitively). That is why I have used the lagged value of the title compensation compared with the rest-of-firm compensation to determine if departures of the title compensation from the normal relationship with compensation in the rest of the firm tend to predict corrective action – and I find that they do. 43. After quoting Manski regarding group behavior, Dr. Murphy diverts to the familiar left-out variable problem (which is different from the simultaneity problem): “Generally, when individuals in a group are subject to at least some common influences, it will appear that they are responding to each other even when they are not.”25 That is exactly the reason in my deposition I agreed that the high degree of co-movement of compensation title-by-title could hypothetically be coming from external market forces, although this seems highly unlikely.26 Hence, I have added two new variables that might be able to explain fully the intra-firm correlations. I chose variables to include in my model that measure what I regarded to be the two most promising explanations for the co-movement of title compensation: (1) revenue sharing, meaning that variability in firm revenue that was shared broadly with the workforce and (2) external market forces, which could affect more than one title at the same time. C. Dr. Murphy’s Theory of Regression toward the Mean Requires Randomness That Is Not Part of the Compensation Determination in the Technical Class 44. Dr. Murphy has made a reference to “regression toward the mean” as a way of dismissing my result that there is a lagged corrective effect measured by the ratio of the firm’s Technical Class average compensation (excluding a title) and the title’s average compensation, lagged one year. Regression toward the mean refers to sequences of repeated random draws from the same population, and thus the tendency for a draw that is abnormally high to be followed by something closer to the mean – thus regression toward the mean. Per Dr. 318-319. 25 Murphy Supplemental Report, ¶ 35. 26 Deposition of Edward Leamer Vol. 2, June 11, 2013 at pp. 528:7-16. Page 19 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 547 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page23 of 40 CONFIDENTIAL July 12, 2013 Murphy, “[t]he regression fallacy arises when an analyst examines a data series that is subject to shocks that are, at least to some extent, temporary, and ignores the tendency of such data to “regress” or revert to the mean of the distribution.”27 45. 46. The only example that Dr. Murphy provides is salespeople on commission. For salespeople the regression toward the mean phenomenon may arguably have some validity. But absent the evidence, I am not so sure that annual compensation even for salespeople exhibits regression toward the mean. Dayby-day randomness could be there, but averaged out over 365 days we may be getting mostly constant ability and variable external market sales opportunities. 47. But, in any case, there are no salespeople in the Technical Class. They have been excluded as indicated in Exhibit B of my October 1, 2012, report. Nor are there any employees who are paid based on random factors. Firm revenue to some extent may behave like a random variable, and some titles may share in revenues more than others, but I have included the firm revenue as a variable which should soak up that effect. 48. 27 The applicability of regression toward the mean to payroll records of Defendants seems to me extremely doubtful. Defendants do not set annual title compensation the way that Mother Nature chooses Chicago weather, day-byday. Compensation levels in the Technical Class are all determined thoughtfully by management, not by random devices. In sum, Dr. Murphy has produced a purely hypothetical claim about regression toward the mean which relies on an implausible firm approach to compensation setting.28 Murphy Supplemental Report, ¶ 45. On the other hand, as I discuss below, randomness in reported compensation is likely an important issue in the data collected by the American Community Survey (ACS) that Dr. Murphy used. 28 Page 20 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 548 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page24 of 40 CONFIDENTIAL July 12, 2013 D. Dr. Murphy’s Study of Chicago Daily Temperature is Flawed and Irrelevant 49. V. Dr. Murphy’s temperature regression model that seeks to explain Chicago temperature changes is another example of an analysis designed to illustrate an intended result. Chicago and Milwaukee are within two hours driving distance, so in the absence of any reasonable control variables, it should not be surprising that the regression shows a high degree of association. It would be a surprising result only if it were true for several far apart cities in totally different climate zones and it persisted even after using adequate control variables. Dr. Murphy’s Analysis of “Sharing” in the ACS Data is Flawed and Unreliable 50. Dr. Murphy mindlessly applies my analysis of co-movement to the economywide American Community Survey (“ACS”) compensation data collected by the U.S. Census Bureau. Dr. Murphy uses this analysis to support his claim that the analysis I performed would indicate relationships even where none existed. There is no support in Dr. Murphy’s work for this conclusion. There are important measurement error and reliability problems with the ACS data that render it inappropriate for the time series analysis that Dr. Murphy has performed. Additional and equally compelling methodological problems with his work are set forth below. 51. Beyond the issue of measurement problems the basic premise of this work is mistaken. Although Dr. Murphy claims that discovery of co-movement in his ACS analysis reflects a statistical anomaly that would infect any analysis of the type I have done, some co-movement due to market forces can be expected as individuals are attracted into high-paying occupations and as firms find substitutes for exceptionally expensive workers. 52. The word “Community” in the ACS title tells us the purpose for which this survey was designed, stated explicitly on the ACS website: “Data from the American Community Survey helps your community. The information that the Census Bureau collects helps to determine how more than $400 billion dollars Page 21 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 549 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page25 of 40 CONFIDENTIAL July 12, 2013 of federal funding each year is spent on infrastructure and services.”29 Thus the income and population data collected by the ACS helps to allocate federal spending at any point in time across American Communities and was not designed to trace occupational wages over time as Dr. Murphy has done. A. The ACS Data Suffer from Critical Measurement Errors That Make Them Unsuited to the Analysis that Dr. Murphy Has Carried Out 1. ACS Survey Practices Create Potentially Serious Response Errors 53. One serious problem with the ACS data is that the questionnaire asks for information about all residents at the address but is filled in by only one respondent, who may or may not be the primary income earner.30 This respondent is likely to provide more accurate information about his or herself than about other adults at the address. 54. Another serious problem is that the one respondent at each address is not encouraged to consult any records and most respondents presumably report from memory both for themselves and for each of the other adults.31 Unlike the defendants, who produced the equivalent of a check register showing what they actually paid employees, there is far less incentive for accurate reporting of these income figures by the household respondent. One incentive is to get the survey finished as quickly as possible but accuracy of the responses is not U.S. Census Bureau, “American Community Survey: Why should you participate?,” http://www.census.gov/acs/www/about_the_survey/why_should_you_participate/. 29 U.S. Census Bureau, “The American Community Survey: 2013,” p.2, http://www.census.gov/acs/www/Downloads/questionnaires/2013/Quest13.pdf, “Person 1 is the person living or staying here in whose name this house or apartment is owned, being bought, or rented. If there is no such person, start with the name of any adult living or staying here.” 30 U.S. Census Bureau, “The American Community Survey: 2013,” http://www.census.gov/acs/www/Downloads/questionnaires/2013/Quest13.pdf, The questionnaire asks for : 1) wages, salaries, commissions, bonuses, or tips from all jobs; 2) self-employment income; 3) interest, dividends, and rental income; 4) social security; 5) welfare payments; 6) retirement; 7) other income. The income variable used in Dr. Murphy’s analysis comes from reported total pre-tax wage and salary income (i.e. money received as an employee). Sources of income include wages, salaries, commissions, cash bonuses, tips, and other income received from an employer. 31 Page 22 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 550 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page26 of 40 CONFIDENTIAL July 12, 2013 monitored. Another incentive is to not tell the Federal Government anything that would bring suspicion on the household, which also encourages biased reporting. 2. The ACS Annual Data Mix Two Years of Information 55. A further and fatal problem with the ACS data is that each respondent is asked for income for each adult at the sampled address during the 365 day period ending the day when the respondent decides to complete the survey (not the previous month or the current month or the past calendar year). Respondents are unlikely to know their earnings during these unusual 365 day periods with accuracy, which contributes to the measurement error. In addition to recall error, each of these unusual 365 day reporting periods (except the ones ending on December 31) includes days from two adjacent years. For example, when a respondent reports income for the year ending on April 1, 2010, the Census Bureau makes no attempt to apportion the total between the two years to which the total applies, 2010 and 2009. Instead, the 2010 income figure reported by Census is an average (or sum) of the numbers collected in the 12 monthly surveys conducted during 2010. This means that the 2010 income figure is a mix of 2009 and 2010 data with the greatest emphasis at the beginning of the 2010 year, which is included in the income responses collected in each month throughout 2010. The Figure 2 below shows the approximate monthly sample weights, built on the assumption that the January 2010 survey collects data from February 2009 through January 2010.32 This anomaly occurs throughout all years of the data. The triangular shape of this figure is something that Dr. Murphy acknowledges in his deposition. Deposition of Kevin Murphy Vol. 2, July 5, 2013 at p. 546:8:14. 32 Page 23 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 551 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page27 of 40 552 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page28 of 40 CONFIDENTIAL July 12, 2013 wages”). This top histogram leans just slightly to the right. If all the correlations were exactly zero, the standard error would be about 0.378 based on the approximation: (1/(n-2))1/2 and n = 9. What we have is a mean of 0.18 and a standard error of 0.36, which is compatible with some commonalities, but not a whole lot. The bottom chart shows the distribution of correlations weighted by the size of occupation. This chart indicates that most of Dr. Murphy’s commonality results are driven by a few large occupations. 59. I contrast these figures with analogous distribution charts constructed using defendants’ payroll data. Figure 4 shows the distribution of correlations between Defendants’ title average real compensation growth and real reference compensation growth. The substantial commonality in the Defendants’ payroll data is clear. The top histogram leans heavily to the right. The mean correlation is 0.61 and the standard error is 0.37, which indicates substantial commonality. The bottom chart which shows the distribution weighted by employee years indicates that the commonality results are broad and deep. Weighted by conduct period employee years, the mean correlation is 0.82. The contrast between the weak correlations in the ACS data and the much stronger correlations in the Defendant data is further confirmation of the role that internal equity played in setting compensation levels and the extent to which Dr. Murphy’s ACS regression analysis is nonsensical. Page 25 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 553 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page29 of 40 CONFIDENTIAL July 12, 2013 Figure 3: Correlations of ACS Occupation Real Wage Growth with ACS Reference Wage Growth Distribution of ACS Wage Change Correlations Share of Occupations (%) 15 10 5 0 -.8 -.7 -.6 -.5 -.4 -3 -2 -.1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 Source: ACS Data from Murphy Backup Page 26 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 554 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page30 of 40 CONFIDENTIAL July 12, 2013 Figure 4: Correlations of Annual Real Growth of Defendant Title Compensation with Real Reference Compensation Growth Distribution of Defendant Compensation Change Correlation 20 Share of Titles (%) 15 10 5 0 -1 -9 -.8 -.7 -.6 -.5 -.4 -.3 -.2 -.1 0 .1 2 .3 .4 .5 .6 .7 8 9 Source: Defendant Employee Data; Correlation Analysis Distribution of Defendant Compensation Change Correlation Weighted by Class-Period Employee Years 50 Share of Titles (%) 40 30 20 10 0 -1 -9 -.8 -.7 -.6 -.5 -.4 -.3 -.2 -.1 0 .1 2 .3 .4 .5 .6 .7 8 9 Source: Defendant Employee Data; Correlation Analysis Page 27 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 555 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page31 of 40 CONFIDENTIAL July 12, 2013 C. Other Flaws in the ACS Data for Dr. Murphy’s Analysis 60. VI. There are a number of additional problems with the ACS data used in Dr. Murphy’s analysis. First, ACS does not allow accurate computation of “current year” dollars. The ACS annual data includes income earned in two adjacent years at two different price levels.33 Second, the ACS survey does not collect enough information to determine in which year work occurred when the individual was not employed in every one of the preceding 52 weeks. Finally, the mapping of employment information from surveys to occupation categories (OCC codes) can be an additional source of measurement error. To identify the individual’s employment category, respondents are asked to answer the question “What kind of work was this person doing?” The employment responses go through a process of classification into OCC codes, which is performed by the clerical staff trained in using the classification system.34 This fuzzy mapping of respondent answers into occupations is prone to misclassification errors. Dr. Murphy’s Concerns about Common Effects Excluded from My Work Are Strictly Hypothetical 61. Dr. Murphy emphasized that left-out variables can cause problems with regression analysis, but he has not put forward any specific example of such an effect. While I controlled for the external and internal non-sharing effects he claims pollute my results, he has not presented any analysis showing that omitted non-sharing external or internal effects are responsible for the positive sharing “The Census Bureau provides a separate variable called ADJUST, which adjusts dollar amounts to the amount that they would have been had they been earned entirely during the calendar year. Ideally, this adjustment factor would be unique to each month of data. Consider the example of the 2008 ACS, released in the fall of 2009 but gathered throughout 2008: people surveyed in January 2008 earned all of their stated income during 2007 (January 2007 to December 2007), while people surveyed in December earned most of their stated income during 2008 (December 2007 to November 2008). However, month-specific adjustment factors would make it easier for individuals to be identified, so the Census Bureau does not provide them.” Minnesota Population Center, University of Minnesota, “Note on the Standardization of ACS/PRCS Income Variables and Other Dollar Amount Variables,” https://usa.ipums.org/usa/acsincadj.shtml. 33 U.S. Census Bureau, “ACS Design and Methodology: Data Preparation and Processing for Housing Units and Group Quarters,” pp 7-8, http://www.census.gov/acs/www/Downloads/survey_methodology/acs_design_methodology_ch10.pdf, “Automated coding programs were used for these items for the 2000 Decennial Census, but it was determined that using trained clerical coders would prove more efficient.” 34 Page 28 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 556 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page32 of 40 CONFIDENTIAL July 12, 2013 in my results. He has not elaborated on what his claimed “other common factors” could be. 62. One of Dr. Murphy’s innovations to my conduct analysis was his addition of a stock price variable (namely, the S&P 500 Index) as a common explanatory factor. He claims to use this variable regularly to check regressions. He also has said in his deposition that there may be any number of firm success factors that are not reflected in firm revenue.35 Stock prices provide an indication of the market’s assessment of a firm’s future success and may contain compensationrelevant information. Thus, as a robustness check, I use each firm’s stock price data and check whether its addition to the compensation sharing regression explains away the observed co-movement. It doesn’t. Deposition of Kevin Murphy Vol. 1, December 3, 2012 at p. 316:11:21; Deposition of Kevin Murphy Vol. 2, July 5, 2013 at p. 485-486. 35 Page 29 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 557 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page33 of 40 CONFIDENTIAL July 12, 2013 Figure 5 VII. Conduct Regression 63. Dr. Murphy expresses his concern that I did not comment on his “more parsimonious model that included fewer explanatory variables but which still permitted measurement of separate Defendant-specific conduct effects.” 64. The conduct regression I presented in my original report differentiates the conduct effect across years and across defendants by including interactions of conduct with age, age squared, and the hiring variables. In his ‘parsimonious’ model, Dr. Murphy substitutes these interactions with a single conduct variable interacted with employer dummies. 65. This is just a restricted version of my model because, 1) it makes no differentiation between individuals by eliminating the age interaction, 2) it allows less employer differentiation by using a single dummy variable, and 3) it does Page 30 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 558 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page34 of 40 CONFIDENTIAL July 12, 2013 not capture business cycle effects as my model does via the hiring variable that reflects changes in the economic environment. Hence, it appears that Dr. Murphy’s ‘parsimonious’ model may be a little too restrictive to do justice to the challenges presented by this data. 66. I have considered whether to add any variables and I am not aware of any I need to add at the present time. In my previous report, I discussed the logic behind my use of basic observable employee characteristics such as age, company tenure, gender, location, title, and employer along with firm-wide and economy-wide control variables. I also cited economic literature that uses similar modeling techniques.36 In my Reply report, I discussed the lack of sensitivity of my findings to inclusion of alternative external control variables such as firm stock prices and to a different level of aggregation.37 The work I have done so far establishes the robustness of my damages model, hence I stand by my earlier report which demonstrates a method by which class-wide damages can be computed. VIII. Almost All Employees Received Supplemental Compensation or Salary Increases 67. I was asked to address a claim I understand that Defendants’ expert Dr. Shaw has made that there may be Class members whose job performance was so poor they would not have received any increase in pay, regardless of steps the Defendants would have taken to increase pay in response to increased competition.38 At her deposition, Dr. Shaw asserts individual managers “were given guidelines to give zero increases to low performers,” but she says there is “no way of knowing” how many employees would fall into this category Leamer Report pp. 53 and 64-65. The adequacy of such variables is echoed by one of Defendants’ experts, Dr. Shaw, who published an article that used an almost identical set of variables to explain the pattern of wage variability observed in a survey dataset. See Shaw, Kathryn L., “Wage Variability in the 1970s: Sectoral Shifts or Cyclical Sensitivity?” The Review of Economics and Statistics, Vol. 71, No. 1 (Feb., 1989), pp. 26-36. Dr. Shaw builds a regression model that uses individual characteristics such as experience, tenure, marital status, race and regional dummies etc along with external control variables such as projected employment growth. 36 37 38 Leamer Reply Report pp. 44-45 and 49-54. Expert Report of Kathryn Shaw, Ph.D., June 21, 2013. Page 31 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 559 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page35 of 40 560 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page36 of 40 561 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page37 of 40 CONFIDENTIAL July 12, 2013 Figure 6 Percentage of Adobe Technical Class Employees with Base Compensation within Salary Range Page 34 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 562 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page38 of 40 CONFIDENTIAL July 12, 2013 Figure 7 Percentage of Apple Technical Class Employees with Base Compensation within Salary Range Source: 231APPLE004236, 231APPLE007258, 231APPLE008537, 231APPLE008912, 231APPLE011618, 231APPLE100713. Page 35 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 563 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page39 of 40 CONFIDENTIAL July 12, 2013 Figure 8 Percentage of Google Technical Class Employees with Base Compensation within Salary Range Source: Google compensation data, GOOG-HIGH TECH-00182929, GOOG-HIGH-TECH-00395420, GOOG-HIGH-TECH00625147, GOOG-HIGH-TECH-00625148. Page 36 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 564 Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page40 of 40 CONFIDENTIAL July 12, 2013 Figure 9 Percentage of Intel Technical Class Employees with Base Compensation within Salary Range Page 37 Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. 565 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page1 of 120 In re High-Tech Employee Antitrust Litigation Expert Witness Report of Kevin F. Hallock May 10, 2013 May 10, 2013 Expert Witness Report of Kevin F. Hallock [REDACTED] 566 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page2 of 120 TABLE OF CONTENTS Page I. Qualifications ................................................................................................................................... 1 II. Assignment and Summary of Conclusions ...................................................................................... 2 III. Prior Testimony ............................................................................................................................... 4 IV. Compensation System Design ......................................................................................................... 5 V. The Defendants Had Formalized Pay Systems .............................................................................. 15 VI. Issues of Internal Equity ................................................................................................................ 33 VII. Internal Equity and Pay for Performance Are Not Mutually Exclusive ........................................ 54 VIII. How Restricting Cold Calling Can Restrict Information and Pay ................................................. 57 IX. How A Structured Compensation System Can Be Related to Systematic Compensation Effects ............................................................................................................................................ 60 X. Examples of How Market Pressure Led to Pay Changes at Defendants........................................ 62 XI. Agreements of the Kind Described in this Case Could Limit Recruiting and Have Negative Consequences on Compensation for Employees of Defendant Firms ............................ 66 XII. Given the Defendants’ Formalized Pay Structures and Compensation Design, Effects on Compensation Could be Widely Felt ............................................................................................. 69 XIII. The Technical Class ....................................................................................................................... 70 XIV. Conclusions .................................................................................................................................... 71 May 10, 2013 Expert Witness Report of Kevin F. Hallock 567 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page3 of 120 1 I. Qualifications 1. I am the Donald C. Opatrny ’74 Chair of the Department of Economics, the Joseph R. Rich ’80 Professor, Professor of Economics and Human Resource Studies and Director of the Institute for Compensation Studies at Cornell University in Ithaca, NY. I am also a Research Associate at the National Bureau of Economic Research in Cambridge, MA and a Distinguished Principal Researcher at The Conference Board in New York, NY. Additionally, I serve on the Compensation Committee of Guthrie Health in Sayre, PA and on the Board of Directors of the Society of Certified Professionals at WorldatWork in Scottsdale, AZ. I earned a B.A. in Economics at the University of Massachusetts at Amherst in 1991 and a Ph.D. in Economics from Princeton University in 1995. I previously taught at the University of Illinois at Urbana-Champaign from 1995-2005 and have been at Cornell University since 2005. 2. My work has covered a variety of fields including compensation design, executive compensation, the relationship between labor and financial markets, wage differentials and inequality, the effects of job loss, and labor economics. My work has been published in a variety of outlets including The American Economic Review, The Journal of Economic Perspectives, the Journal of Labor Economics, the Journal of Public Economics, the Journal of Corporate Finance, Labour Economics, the Industrial and Labor Relations Review, Research in Personnel and Human Resources Management, and Research in Labor Economics. I have edited or coedited a variety of volumes including co-editing Labor Economics (1995) and The Economics of Executive Compensation (1999). My book regarding compensation, Pay, was published in 2012. 3. I have served as a referee for over 40 different academic journals, I previously served as an Associate Editor at the Journal of Labor Economics and at Economics Bulletin and am currently an Associate Editor at Labour Economics, am on the editorial board of the Industrial and Labor Relations Review, and am on the advisory boards of the Journal of People May 10, 2013 Expert Witness Report of Kevin F. Hallock 568 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page4 of 120 2 and Organizational Effectiveness and Compensation and Benefits Review. I have given lectures at over 30 different Universities. I have taught courses at Cornell on Managing Compensation, Executive Compensation, Pay, Finance for Human Resources, and Labor Economics. A more complete description of my qualifications is included in my curriculum vitae in Appendix A. 4. In connection with this matter, I reviewed and considered materials from this case, including the consolidated amended complaint, depositions, deposition exhibits, and salary or market pay range materials produced by or compiled from materials of each defendant. Information that I considered in forming my opinions include the items listed in Appendix B or listed in this report and any attached exhibits. The bases for my opinions are described in this report and any attached exhibits. I reserve the right to supplement this report in view of any new material or information provided to me after the date of this report. 5. My compensation for my work in this matter is not contingent upon my findings or the outcome of this litigation. I am being compensated at my current hourly rate of $750 per hour. II. Assignment and Summary of Conclusions 6. I understand that plaintiffs are seeking certification of a class of salaried technical, creative, and research and development employees (the “Class” or “Technical Class”), consisting of those described in Appendix B to the October 1, 2012 Expert Report of Dr. Edward E. Leamer, and who worked for a defendant while that defendant participated in at least one “no cold-call” agreement with another defendant. 7. I have been asked by counsel for the plaintiffs to: a. Analyze defendants’ pay practices to determine whether defendants used formal administrative pay systems; and May 10, 2013 Expert Witness Report of Kevin F. Hallock 569 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page5 of 120 3 b. Determine whether suppressing recruiting of defendants’ workers, including technical workers, are predicted to have led to the result of suppressing the pay of their employees, including all or nearly all members of the Technical Class, including those with different job titles. 8. As a result of my work to date, the following are among my conclusions. a. The defendants had formalized compensation systems. These include using market surveys, having clear structures, using market pay lines, grades and many other features of formalized compensation systems. b. The defendants made use of the ideas of compensation beyond salary. These other forms of compensation include components such as bonuses and stock. c. Issues of internal equity and equity in general were important to defendant firms. Whether they used the terms or not, the concepts of internal equity and also generally treating similar employees similarly were important to defendant firms. d. Pay moved in defendant firms in systematic and structured ways. e. Restrictions on cold-calling clearly had impacts on employees among the defendant firms. In particular, restrictions on cold-calling hamper compensation levels for employees. The restrictions could be expected to hamper levels of compensation for those who would have been cold-called and for all or nearly all salaried employees of defendant firms. f. Agreements such as restrictions on cold-calling could be expected to limit and have negative consequences on employee compensation for those May 10, 2013 Expert Witness Report of Kevin F. Hallock 570 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page6 of 120 4 workers directly involved and for nearly all salaried employees. Given the formalized pay structures and compensation design in defendant firms, nearly all salaried employees could be expected to have pay that would otherwise be higher. g. The formalized systems in place at the defendants relied on structures, external data from the market and the like, and notions of equity were present at defendants. As a result, those effects cycle on to other employees and their levels of compensation. Therefore, the formal compensation structures could be expected to lead to an effect on nearly all class members. h. Although I have not been asked to estimate the magnitude of damages in this case, based on my knowledge of compensations systems and the materials considered, I believe that agreements against cold calling, such as the agreements at issue in this case, are predicted to suppress the compensation of all or nearly all members of plaintiffs’ proposed Technical Employee Class, including those with different job titles. III. Prior Testimony 9. I have testified at a deposition twice and have not testified at a trial. During the previous four years, I have testified as an expert at a deposition in the following case: William Hale Hubbell vs. G.J. Ratcliffe, Richard W. Davies, Andrew NcNally IV., individually and as trustees. I have never before testified as an expert in a class action lawsuit. May 10, 2013 Expert Witness Report of Kevin F. Hallock 571 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page7 of 120 5 IV. Compensation System Design 10. Many firms use administrative pay systems.1 These systems typically include standardized features, such as job analysis, job evaluation, use of market surveys and external market data, market pay lines and salary bands and zones or grades and ranges. This section briefly outlines the features of these systems. 11. It is noteworthy that an important feature of these systems is that often the internal structure is set in advance of using external compensation information. When setting up these systems the internal structure is set and then external data is then matched to the internal structure to set pay levels. 12. Many organizations have a business strategy that is then linked with a compensation strategy and philosophy. Organizations often start with their own compensation strategy, which of course can evolve over time, before setting up the more technical features of the pay system. 13. Job analysis is the “systematic process of collecting information that identifies similarities and differences in the work”.2 Harvey (1991) notes two important features of job analysis. First, job analysis should describe observable characteristics of jobs. Second, individual people in those jobs should be kept separate from the job analysis. To be sure, individual differences matter in compensation design but are not used at this point in the evolution of a compensation system. 14. Job analysis can become very specific and detailed. In fact, Martocchio (2004) points out very specific details of job elements in job analysis such as element, task, position, 1 2 See, for example, Milkovich, Newman and Gerhart (2011, 2014), Martocchio (2004), or Hallock (2012). Milkovich, Newman and Gerhart (2011), p. 97. May 10, 2013 Expert Witness Report of Kevin F. Hallock 572 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page8 of 120 6 job, job family, and occupation.3 This begins with an “element,” which could be as simple as putting a piece of paper in a scanner to scan a document all the way up to a “job family”. The rest of the list from Martocchio (2004) just aggregates to higher and higher levels. A “Task” is the next up from an element. A position is a group of tasks that make up the activities that a specific employee might perform. For example a junior administrative assistant might make flight reservations, distribute mail, answer phones and perform related activities. A job may be reflected in a set of positions. For example, there might be many different junior administrative assistants all doing a very similar job. The job family is the next level up.4 A job family might be administrative jobs, or technical jobs, or marketing jobs. Different organizations may do this differently. Overall structure is what is important. 15. An additional step in performing a job analysis involves collecting information on job content (e.g. tasks, activities, work demands), characteristics of employees who hold these sorts of jobs (e.g. technical skills, manual dexterity, leadership), internal relationships (e.g. supervisors, peers), and external relationships (e.g. regulators, customers, suppliers).5 Henderson (2006) describes a series of examples of questionnaires that are used by firms to collect this kind of information in their organizations. O*NET6 --a revision of the U.S. Department of Labor Dictionary of Occupational Titles--is an example of these systems. O*NET has extraordinary detail of the characteristics of hundreds of jobs but includes a set of overarching descriptors: knowledge, skills, abilities, work activities, interests, work content, and work values. 16. Job evaluation in the next step in setting up a pay system using a job-based structure as described here. Job evaluation “is the process of systematically determining the 3 Martocchio (2004), page 198. Hallock (2012), page 63-64. 5 Milkovich, Newman and Gerhart (2011), Hallock (2012) and others discuss these issues. 6 See http://online.ontcenter.org. 4 May 10, 2013 Expert Witness Report of Kevin F. Hallock 573 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page9 of 120 7 relative worth of jobs to create a job structure for the organization. The evaluation is based on a combination of job content, skills required, value to the organization, organizational culture, and the external market. This potential to blend organizational forces and external market forces is both a strength and a challenge of job evaluation”.7 17. Companies sometimes use formulaic approaches to identify relative differences in their jobs before benchmarking them to external data. One approach to this is sometimes called the “point method,” in which each job in the organization is assigned a set of “points” as I will describe further below. For example, suppose that the Engineer I job is assigned8 530 points, the Engineer II job is assigned 640 points and the Senior Engineer job is assigned 935 points. This necessarily suggests that the Engineer II job contributes less than the Senior Engineer job but more than the Engineer I job. It is important to note that the points don’t necessarily ultimately result in a linear scale in terms of pay. 18. Obviously there are many ways to order or rank jobs. One example of a formalized system is that used in classification of U.S. Government jobs as displayed in Figure 1.9 19. The point system has many important features, including compensable factors, scaling, weighting, and degrees. Benchmark jobs are important since they are jobs that will ultimately be used to match the internal structure that is now being discussed with the external market. Benchmark jobs are typically jobs that are relatively well-known and are common so that information can be collected about them internally and externally. However, even in the absence of perfect benchmark jobs, these systems can operate. 7 Milkovich, Newman and Gerhart (2011), pp 129-130. I describe where these points in this hypothetical example come from below. More detail can be seen in Chapter 6 of Hallock (2012). 9 Source: United States Office of Personnel Management: http://www.opm.gov/oca/11tables/pdf/DCB.pdf See Hallock (2012), p 69. 8 May 10, 2013 Expert Witness Report of Kevin F. Hallock 574 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page10 of 120 8 20. In developing a point system, the next step is to identify “compensable factors,” i.e., the factors for which the company sees value. These might include, for example: technical ability, leadership, responsibility, communications, and working conditions.10 The idea is that more of each factor should be linked to more productivity and (ultimately) higher pay. Note, however, that we still aren’t yet focused on pay levels – just on differentiating jobs. Also note that one of the factors, working conditions, is unique in that poorer conditions may lead to higher pay as a compensating differential.11 Working conditions, per se, are not necessarily a positive attribute of work but they are a factor that may need to be compensated. 21. Once each compensable factor for a job is defined, a set of degrees for each factor is created. There does not have to be a common set of degrees for each factor. Martocchio (2004) includes examples of degrees for the compensable factor he defines as writing ability. These range from degree one that includes “simple phrases and sentences” up to degree five that includes “manuals and speeches”.12 It is important to note that the degrees need not be evenly or linearly spaced. For example, one could set aside 100 points for writing ability and have five degrees of writing ability. One could assign a job with writing ability as follows: writing ability “one” gets 20 points, writing ability “two” gets 40 points, “three” gets 60 points, “four” gets 80 points, right up to writing ability “five” at 100 points. But this does not have to increase in lockstep. As an alternative, one could assign writing ability “one” 40 points, writing ability “two” 80 points, writing ability “three” 90 points, writing ability “four” 95 points and writing ability “five” 100 points, of course depending on how the each level of writing ability is defined. 10 These are precisely the five compensable factors I use in Chapter 6 of Hallock (2012). See Rosen (1986). 12 Martocchio (2004), page 219. 11 May 10, 2013 Expert Witness Report of Kevin F. Hallock 575 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page11 of 120 9 22. The next step is to define the weight of each factor. For example, in the hypothetical example I created with five compensable factors, let’s define technical ability 50%, leadership 20%, responsibility 15%, communications 10% and working conditions 5%. 23. Next suppose that the firm defines that the maximum number of points any job can get is 1000. This is an entirely arbitrary number. It could be any number but this is a nice round number and makes the discussion easier to understand. 24. So, we have defined that there are 1000 total possible points. We have also created our weights so that means there are 500 possible points for technical ability (50% of 1000), 200 possible points for leadership (20% of 1000), 150 possible points for responsibility, 100 possible points for communication and 50 possible points for working conditions. In Figure 2, I have included a sample worksheet for assigning points to jobs. 25. The worksheet in Figure 2 could be used, for example, for all jobs within a particular “job family”. Consider the Engineer I, Engineer II and Senior Engineer jobs mentioned previously. This worksheet could be filled out for any of those jobs and any other jobs in the “engineering” job family. 26. In Figure 3, the worksheet is filled out for a hypothetical Engineer II job which has degree 4 technical ability (worth 400 points), degree 2 leadership ability (worth 80 points), degree 3 responsibility (worth 90 points), degree 3 communications ability (worth 60 points) and degree 1 for working conditions (worth 10 points). The sum of these is 640 points. To show a concrete, related example, Pixar has an “Engineering Job Matrix” where it lists “knowledge,” “job complexity,” “supervision & collaboration” and “experience”. They then list six levels of each.13 13 Engineering Job Matrix, Pixar, PIX00049042, exhibit 1305. May 10, 2013 Expert Witness Report of Kevin F. Hallock 576 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page12 of 120 10 27. This differentiation process is then repeated for all jobs in the job family, and in all job families. In the hypothetical example in Figure 4, 530 points were assigned for the Engineer I job, 640 for the Engineer II job and 935 for the Senior Engineer job. In Figure 5, I have added two other job families (the Attorney job family and the Administrative job family) and three jobs to slightly increase the complexity of this example. The Attorney and Administrative job families could have had the same compensable factors, scales and weights as the Engineer job family, but that is not necessarily so in this hypothetical example. 28. Note that Figure 5 shows a relative ranking (or number of job evaluation points) for many different jobs. This is done entirely internally to the organization. No external data was used and no information on compensation of any kind was used in creating this. 29. A next step in a formal pay system is to match the set internal structure to external market data. This is something that defendants in this case have done for many years. Finding the right market data and the appropriate survey is described in the literature, including Cardinal and Florin (2012). Benchmark jobs are important since they are jobs that will ultimately be used to match the internal structure that has been identified (using all or many of the features discussed above) with the external market. Benchmark jobs are typically jobs that are relatively well-known and are common so that information can be collected about them internally and externally. However, even in the absence of perfect benchmark jobs, formal pay systems can operate. 30. Internal comparisons among workers are clearly important to workers and to organizations. This is the case both when organizations are organizing their structures and when making individual pay decisions. Organizations are also concerned with individual pay May 10, 2013 Expert Witness Report of Kevin F. Hallock 577 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page13 of 120 11 comparisons, pay and equity and internal equity as confirmed in this case at each defendant organization, documented below. 31. Internal comparisons are also studied by academics from different disciplines. These include a set of studies on fairness (Levine, 1993), and pay secrecy (Milkovich and Anderson, 1972, Lawler, 1967, Card, Mas, Moretti and Saez, 2012). 32. A next step in a formal pay system is to match the set internal structure to external market data. Finding the right market data and the appropriate survey is not a simple task. More information on that can be found in a variety of sources, including Cardinal and Florin (2012). 33. Suppose that we have five internal jobs in a particular job family and that they have different levels of job evaluation points assigned to them. Call the five jobs Associate 1, Associate 2, Associate 3, Associate 4, and Associate 5. Further assume these five jobs have been assigned the following job evaluation points internally: 185, 200, 335, 400 and 460, respectively. 34. Further assume that the external data include information from a set of employers on each of the five jobs: Associate 1 – Associate 5. In this case (as in most cases) not all external organizations that have provided information to the survey consultant are paying each of the jobs equally. There is dispersion of compensation for each job. Figure 6 is an example that illustrates how this would look in practice. Note that the external firms all pay jobs in the Associate 2 position quite similarly, while there is a great deal of dispersion in how external competitors pay the Associate 4 and 5 jobs.14 14 Note, for example, the testimony of Intuit’s Senior Vice President, Chief of Human Resources, Sherry Whiteley: Deposition of Ms. Sherry Whiteley, March 14, 2013, page 97. May 10, 2013 Expert Witness Report of Kevin F. Hallock 578 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page14 of 120 12 35. After the external market data are overlaid on the internal structure, a “market pay line” can be created. This can be done in a number of ways. One way, and the one I use in this example, is to create the “line of best fit” as I have done in Figure 6. In this case, the line is simply the “ordinary least squares regression line”. It is the line that minimizes the sum of the squared distances from each point and the line. This shows how the company, given its strategy, compensable factors, scales, weights, etc., pays, given internal and external market forces. Individual companies can always pay more or less, depending on their circumstances and interests. The ordinary least squares regression line15 that comes from Figure 6 is -39,651.77 + 556.93*(Job Evaluation Points). 36. The market pay line is effectively showing, given the external market, how this company will pay at a point for a given job. Take, for example, the Associate 2 job in Figure 6. That job was assigned 200 job evaluation points. So to find the level of pay for an Associate 2 in the firm, after taking into account the internal structure and the external market data, one would pay $71,734.43 = -39,651.77 + 556.93*(200). The typical payment for the other jobs can be found similarly. A useful feature of this system is that jobs that are not included as benchmark jobs, jobs that are unique to the firm, or jobs that are created after the system is set up can also be priced using the equation. Say, for example, a job unique to the firm is developed and the company goes through the job evaluation and job analysis process and finds it is worth 300 job evaluation points. Even though there is no external market data on that job, a price can be created for it. It is -39,651.77 + 556.93*(300) = $127,427.53.16 15 See page 80 in Hallock (2012). Note the explicit reference to a “Pay Line” in powerpoint on pay design, LUCAS 00188717, exhibit 715.10 and reference at Intel to “pay lines” in powerpoint called FY11 Preliminary Pay lines development update, May 5, 2010, 76582DOC000004_000004, exhibit 399.4. See also references to “pay line” in 2008 Focal Development Process Overview, 76582DOC000348, page 4 (Intel). 16 May 10, 2013 Expert Witness Report of Kevin F. Hallock 579 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page15 of 120 13 37. Even in a formal pay structure, it is likely that not all people doing the same job within a firm are all paid the same salary. There are a wide variety of reasons for this. This is why, in a final stage, firms create bands and zones or grades and ranges or other systems to essentially put “boxes” around each type of job.17 A clear example of this is the system for some Technical Jobs at Google in 2004.18 38. Figure 7 displays the information as of January 13, 2004 for Google Technical workers in job grades 1 – 9.19 The figure has features that are consistent with models taught in compensation textbooks such as Milkovich, Newman and Gerhart (2011),20 .21 39. Many organizations use various versions of what I have outlined in this section. 40. So far I have been focused on salaries. Wage and salary income is an important large part of labor compensation, as I will show below. But there are other components in total compensation, including bonuses, stock, stock options and other pay. 41. There is evidence that total compensation is correlated with salary. For example, 17 See Milkovich, Newman and Gerhart (2011), page 265. See spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data”. 19 Created from data in spreadsheet GOOG-HIGH-TECH-00221513.xxsx, tab “Employee Data”. 20 See, for example, page 265 of Milkovich, Newman and Gerhart (2011) in Exhibit 8.17. 21 Note, however, the horizontal axis for each job grade has some width so it is a “box” with a top and a bottom. But it can be characterized as a vertical line with no width, as in many subsequent figures. 18 May 10, 2013 Expert Witness Report of Kevin F. Hallock 580 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page16 of 120 14 .22 Elsewhere I will show the higher the job level the higher the salary in multiple organizations. Figure 8 is one example of a link between salary and equity. 42. spreadsheet, An additional example of the link comes from an Apple Spreadsheet.23 In this . With respect to this sheet, Apple Senior Director of Compensation Steve Burmeister was asked, “… ”.24 In Figure 9, I plot information from this sheet25 and use only three columns of the data: . In Figure 9, I have plotted three panels. In the first, it is clear that . To create the panel in the top right of the figure, I first calculated a new variable which is the “nonbase” cash which I defined as (total cash) minus base. The top right panel plots this ratio against total cash compensation. Clearly a . In the bottom left panel, I plot the bonus percentage against the base salary for . 43. I should note that there is substantial evidence in general, that stock (stock, stock options etc.) as a fraction of total compensation is correlated with job level and salary.26 44. There can be important credential effects to certain phenomena in labor markets, such as being associated with a college degree or being associated with well-known 22 Powerpoint, Apple Inc., Compensation Committee, Apple, August 5, 2009, 231APPLE10067, exhibit 1854.5. Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE 231APPLE098912, exhibit 1858.2. 24 Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 112. 25 Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE 231APPLE098912, exhibit 1858.2. 26 See, for example, Hallock (2012), page 92, for an example of the link between CEO cash compensation and CEO total compensation (including equity). 23 May 10, 2013 Expert Witness Report of Kevin F. Hallock 581 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page17 of 120 15 organizations. There is a large literature in economics on the economic returns to education (e.g. Card, 1999, 2001). There is also a literature on estimating the difference between productivity and the signaling effect of education on earnings (e.g., Spence, 1973, Hungerford and Solon, 1987 and Weiss, 1995). For example, do those with high levels of education have higher earnings because they learned more in school and are, therefore, more productive workers, or is the credential of the educational institution a signal to employers of their high ability or work ethic? Just as there could be signaling and productivity effects of education on earnings, there too could be productivity and signaling effects of the employer brand on earnings and future earnings. For example, working for a high-profile or well-known employer, including any of the seven defendants, could have positive benefits to an employee including monetary and nonmonetary compensation in the future. V. The Defendants Had Formalized Pay Systems 45. There is evidence in the testimony and documents I reviewed in this case that the defendants each had formalized or sophisticated human resource (HR) or compensation systems of one type or another. The systems are may not contain all features of the example I outlined above but they are certainly formalized compensation systems, as evidenced, for example, by their use of jobs, job families/grades, salaries or market ranges, and benchmark data. 46. Adobe: There is evidence that Adobe had formalized compensation systems. Included among the evidence that Adobe had formal structures is data Adobe produced to plaintiffs.27 That information shows that Adobe had many job families, many grades within job 27 See spreadsheet “Employee Type Count by Employer”. May 10, 2013 Expert Witness Report of Kevin F. Hallock 582 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page18 of 120 16 families and many job titles within grades. Additional data include a variety of compensation structure features including salary min, mid and max information.28 47. Additional evidence that Adobe had formalized pay systems is contained in the deposition of Ms. Donna Morris, Vice President of Global Human Resources until March 2007, when she became Senior Vice President of Global Human Resources. Ms. Morris noted with respect to salary ranges 29 48. Ms. Morris also testified, 30 49. Ms. Morris similarly affirms in her declaration, “The target [salary] midpoint has changed over the years and varied across job functions. For example, the 2005 target midpoint for various jobs in set forth in Exhibit 1 (ADOBE_015864), which is a true and correct copy of Adobe’s 2005 Performance, Salary & Stock Focal. The maximum and minimum of the salary range was then calculated by applying a spread, which also varied over the years and across job levels. The spread varied between 50% and 70% for different job levels during the class period”.31 50. Additional evidence that Adobe had formalized compensation and HR systems comes from the deposition of Ms. Rosemary Arriada-Keiper, who served as Adobe’s Manager of 28 Spreadsheet, “Adobe_Salary Ranges” (2002-2006); “ADOBE_DATA_000043_SalaryRanges_FY2008” (2008); “ADOBE_DATA_000044_SalaryRanges_FY2009” (2009); “ADOBE_DATA_000045_SalaryRanges_FY2010” (2010). 29 Deposition of Ms. Donna Morris, Adobe, August 21, 2012, page 154. 30 Deposition of Ms. Donna Morris, Adobe, August 21, 2012, page 155. 31 Declaration of Ms. Donna Morris of Adobe, September 13, 2011, exhibit 416.7. May 10, 2013 Expert Witness Report of Kevin F. Hallock 583 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page19 of 120 17 Global Compensation, and was asked ”32 51. As an example of the structure at Adobe, Ms. Arriada-Keiper mentioned her own career progression in the company. She said “So no, it was – analyst, senior analyst, program manager, career level manager, senior level manager, director. So just moving up in levels right? We have lots of levels at Adobe”.33 52. Additional evidence that Adobe had formalized compensation and HR systems was in reference to the “salary planning tool”. Ms. Arriada Keiper was asked “…can you tell me how the salary planning tool has worked?”34 She replied, “Yeah. So essentially the salary planning tool is populated with employee information for a particular manager, so the employees on their team. You have the ability to kind of look at their current compensation. It shows them what the range is for the current role that they’re in … The tool also has the ability to provide kind of the guidelines that we recommend in terms of how managers might want to think about their specific allocated budget”.35 32 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 24. Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 31. 34 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 82. 35 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, pages 82-3. 33 May 10, 2013 Expert Witness Report of Kevin F. Hallock 584 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page20 of 120 18 53. Additional evidence that Adobe had formalized HR and compensation systems is from the deposition of Mr. Jeffrey Vijungco, Adobe’s Director of Talent Acquisition, who was asked, “Well, was – in determining base compensation, were the – were ranges of base compensation established for particular job levels of job titles?” He answered, “There is, you know, levels and ranges for every single job at Adobe”.36 54. Additional evidence of formalized systems at Adobe is from the deposition of Mr. Bruce Chizen, Adobe’s President and CEO from 2000 to 2007, who noted, “For every position, we would have a salary range. So depending on a person’s individual experience, their role and responsibility, the job would pay externally between X and Y according to the data we had, and we said philosophically we wanted to pay within the X percent and Y percent of that range”. He went on to say, “And I wanted to make sure we were staying within that relative philosophy. There were always exceptions. Acquisitions, people who had incredible talent and were really providing a bigger role than their title did, so there were always exceptions. But for the most part, I took responsibility philosophically to comply with what I believed to be the right thing to do”.37 55. Adobe also used external market data. Mr. Chizen testified that salary ranges were informed by market data. “We – we relied heavily on external data. So it – I don’t – I don’t know which ones, but Radford would be an example of that, the Radford data”.38 56. There is also evidence that Adobe focused on particular markets for benchmarks. For example, Mr. Chizen was asked if there were particular markets that Adobe used as benchmarks or guidelines for setting salary ranges. He responded affirmatively, explaining, “I 36 Deposition of Mr. Jeffrey Vijungco, Adobe, October 5, 2012, page 29. Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 96. 38 Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 97. 37 May 10, 2013 Expert Witness Report of Kevin F. Hallock 585 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page21 of 120 19 don’t know specifics, but they tended to be software, high-tech, those that were geographically similar to wherever the position existed”.39 57. Adobe also used market surveys, gathered by Adobe’s “Total Rewards organization”.40 58. Additional evidence that Adobe had formalized HR and compensation systems comes from evidence of their systems of “ranking” employees as “High Performer,” “Solid Contributor,” and “Low Performer”.41 59. Adobe also had a salary range website for managers. Ms. Arriada-Keiper testified, “So a salary range website is a tool that we have available to managers whereby they can look at a salary range for an associate job”.42 60. Apple: There is evidence that Apple had formalized compensation systems.43 Additional data include a variety of compensation structure features including .44 61. Additional evidence that Apple had formalized HR and compensation systems comes from a document that lists in Figure 10.45 These are shown in the form of 39 Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 98. Deposition of Mr. Jeffrey Vijungco, Adobe, October 5, 2012, page 31. 41 Powerpoint, Adobe, Q1 Workforce Metrics, As of 4 March 2005, Adobe, ADOBE_000622, exhibit 210.12. 42 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, pages 159-60. 43 See spreadsheet “Employee Type Count by Employer”. “FY07 U.S. Base Pay Salary Structures,” 231APPLE007258-59 (2007); Spreadsheet, “Apple Titles and Grades” and Spreadsheet, “Apple Titles and Grades by Year”. 44 See, for example, Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5. 45 Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5. 40 May 10, 2013 Expert Witness Report of Kevin F. Hallock 586 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page22 of 120 20 graphs in Figure 11. .46 62. Additional evidence that Apple had formalized compensation and HR systems comes from the deposition of Mr. Mark Bentley, Apple’s Senior Director of Recruiting, who was asked, “From time to time, did Apple raise the compensation for a particular job category or job level? He replied “I believe that would be taken – I believe if and when that was done, it was done on an annual basis during compensation planning”.47 63. Mr. Bentley also described the merit process at Apple which is evidence of a formal HR and compensation system. He said, “The merit process is, I think, similar to many companies. 48 64. Additional evidence of a formal salary and HR system at Apple is from Senior Director of Compensation Steven Burmeister’s deposition. He testified, “My group is 46 Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5. Deposition of Mr. Mark Bentley, Apple, August 23, 2012, page 252. 48 Deposition of Mr. Mark Bentley, Apple, August 23, 2012, page 262-3. 47 May 10, 2013 Expert Witness Report of Kevin F. Hallock 587 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page23 of 120 21 responsible for the job structure, the salary range structure, bonus plan design, and equity plan design and administration for Apple.49 65. Mr. Burmeister also noted, “compensation budgets are three main compensation components: base salary, bonus, and stock. And we set the overall compensation budget for these three compensation elements and then provide them to the line of businesses, which then allocate them as appropriate to each of their employees based on performance and contribution”.50 66. Google: There is evidence that Google had formalized compensation systems. That information includes the fact that Google has job families, levels, and grades.51 For example, note again Figure 7 which was created from a Google spreadsheet and additional data include a variety of compensation structure features .52 This spreadsheet documented nine job grades. For each job grade . Google Director of Compensation Frank Wagner testified that he could locate the target salary for jobs at Google through an internal company website. He was asked, “And if you wanted to identify what the target salary would be for a certain job within a certain grade, could you go 49 Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 18. Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 50. 51 Spreadsheet: “Google Census Data, 9-Grade Structure,” GOOG-HIGH-TECH-00625160 and GOOG-HIGHTECH-00625200 (2003); Spreadsheet: “Google 2004 Salary Ranges,” Exhibit 1600; Spreadsheet: “2005 Global Salary Ranges,” GOOG-HIGH-TECH-00625148; Spreadsheet: “Salary Guidelines,” GOOG-HIGH-TECH00625147 (2006); and Spreadsheet: Market Reference Points, GOOG-HIGH-TECH-00182929 (2007-2012). Regarding the final spreadsheet covering the years 2007 through 2012, Mr. Frank Wagner verified that Deposition of Mr. Frank Wagner, Google, March 7, 2013, pages 56-59. 52 See spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data.” 50 May 10, 2013 Expert Witness Report of Kevin F. Hallock 588 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page24 of 120 22 online or go to some place in your office and pull up what that was for that job family and that grade?”53 He answered “Could I do it?...Yes”.54 67. Additional evidence that Google had formalized structures is in data Google produced to plaintiffs.55 . 68. Google former Senior Vice President of People Operations (HR) Shona Brown also confirmed . She was asked “ she replied .56 69. Google former Senior Vice President of Engineering Alan Eustace confirmed Google’s formalized pay systems in his deposition, 57 70. Intel: There is evidence that Intel had formalized compensation systems. Included among this is evidence that Intel had formal structures in data provided by Intel to 53 Deposition of Mr. Frank Wagner, March 7, 2013, page 57. Deposition of Mr. Frank Wagner, March 7, 2013, page 58. 55 See spreadsheet “Employee Type Count by Employer”. 56 Deposition of Dr. Shona Brown, January 30, 2013, page 253. 57 Deposition of Mr. Alan Eustace, February 2013, page 132. 54 May 10, 2013 Expert Witness Report of Kevin F. Hallock 589 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page25 of 120 23 58 That information shows that Intel had many job families, many grades within job families and many job titles within grades. Additional data include a variety of compensation structure features including salary min, mid and max information.59 71. Additional evidence that Intel had formalized pay systems comes from a document called “Compensation 201 Instructor Guide” which includes terms such as 60 72. Additional evidence that Intel had formalized HR and compensation systems comes from a document called “Intel Base Pay Comparison Report” which includes mentions of 61 73. Additional evidence that Intel had formalized pay systems comes from the deposition of Ms. Patricia Murray, Intel’s former Vice President of Human Resources (19962012). She was asked, “Okay. Can you describe for me the general annual process that was used to set compensation?”62 58 See spreadsheet “Employee Type Count by Employer”. Spreadsheet, “SAL_ADMIN_PLAN,” 76586DOC001450 (2004 – 2011); Spreadsheet, “Intel Job Titles and Grades”. 60 Compensation 201 Instructor Guide, Intel, 76583DOC007693, exhibit 2030, page 65. 61 Powerpoint, Intel Base Pay Comparison Report, Support Overview, WW04 2011, 765825DOC001211, exhibit 400, page 31. 62 Deposition of Ms. Patricia Murray, Intel, February 14, 2013, page 15. 59 May 10, 2013 Expert Witness Report of Kevin F. Hallock 590 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page26 of 120 24 63 74. There is additional evidence that Intel had formalized HR systems. Intel Senior Vice President of Human Resources Deborah Conrad testified, “Yes, we have a compensation structure”. She explained, .64 75. Ms. Conrad noted that .65 76. Additional evidence that Intel had formalized compensation and HR systems 66 includes reference to 67 , reference to four types of 68 77. , reference to a list of 69 Additional evidence that Intel had formalized pay systems comes from the deposition of Technology Development Manager Mr. Randall Goodwin who was asked, 63 Deposition of Ms. Patricia Murray, Intel, February 14, 2013, pages 15-16. Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, pages 23-4. 65 Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 34. 66 Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.13. 67 Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.16. 68 Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.28. 69 Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.19. 64 May 10, 2013 Expert Witness Report of Kevin F. Hallock 591 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page27 of 120 25 70 He replied, .71 78. Additional evidence that Intel had formalized compensation and HR systems came from the deposition of Compensation and Benefits Specialist Daniel McKell. Mr. McKell was asked “Can you list all of the different ratings that Intel uses?” He replied .72 79. There is additional evidence that Intel has formalized systems. Mr. McKell was asked “What are the job ranges that Intel currently has?” He answered . He was then asked Shortly thereafter he was asked “can you give me an estimate” of the number of job grades? He replied 73 80. 74 81. There is also evidence that Intel referred to job families in their structure. Mr. McKell noted, 75 82. Mr. McKell described internal benchmarking: 70 Deposition of Mr. Randall Goodwin, Intel, March 15, 2013, page 51. Deposition of Mr. Randall Goodwin, Intel, March 15, 2013, page 52. 72 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 47. 73 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 49. 74 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 56. 75 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 73. 71 May 10, 2013 Expert Witness Report of Kevin F. Hallock 592 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page28 of 120 26 76 83. There is additional evidence of formalized pay and HR systems at Intel. Mr. McKell was asked “Since you have been involved in compensation, have you received from time to time reports “showing whether Intel’s job codes are being paid relative to the midpoint of ”77 Mr. McKell also noted, the pay line?” He replied .78 He was then asked, He answered 84. .79 Mr. McKell affirmed at his deposition the statement in his declaration80 that Intel .81 Soon after Mr. McKell was asked, “Does Intel calculate a market rate for each of these job combinations?” He replied, 82 85. Intuit: There is evidence that Intuit had formalized compensation systems. Included among this is evidence such as salary low, mid and high information, job codes, and 76 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 87-8. Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 90. 78 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 91. 79 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 92. 80 Declaration of Mr. Danny McKell, Intel, September 13, 2011. 81 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 154. 82 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 155. 77 May 10, 2013 Expert Witness Report of Kevin F. Hallock 593 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page29 of 120 27 percentiles.83 That information shows that Intuit had many job families and many job titles within job families and other features of formal systems. 86. Additional evidence that Intuit had formalized HR and compensation systems is contained on one of the documents that notes a list of codes including 84 When Intuit Director of Talent Acquisition Chris Galy was asked about these codes, 85 87. Intuit also indicated other evidence of formal pay structures. Vice President of Human Resources Mason Stubblefield described his responsibility regarding base compensation work. “So I’d say it’s fairly broad from a base compensation perspective. It’s something we think of as job architecture. So the job codes that we use, the job titles that we use, the structure behind that job system that we have really around job codes, job families. And so helping structure that, set that up. The connections from that into the market data and how we provide market reference data to the organization to assist with making compensation decisions; the extension of that into the annual talent and pay process, the merit decisions, performance decisions and managing that process across the company”.86 .87 In addition, he noted, 83 Spreadsheet: “Market Data,” INTUIT_031024 (2009), INTUIT_048148_2005. Powerpoint, FY ’09 New Hire Equity Guidelines, Intuit, INTUIT_039756, exhibit 2140.4. 85 Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 193. 86 Deposition of Mr. Mason Stubblefield, Intuit, March 29, 2013, pages 20-1. 87 Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013, page 25. 84 May 10, 2013 Expert Witness Report of Kevin F. Hallock 594 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page30 of 120 28 88 88. Intuit also has formal bands by which jobs are categorized. These include five groups: 89 Related to that, Mr. Stubblefield noted, “Intuit uses the idea of development bands to help from a learning and development perspective. There are five bands inside the company … each job that we have fits into a band, and so this is just trying to display how, as you move up in the organization or move through different levels of jobs, the – that does move through our band structure, and also kind of the expectation of the scope …”.90 89. Lucasfilm: There is evidence that Lucasfilm had formalized compensation systems. Included among this is data provided by Lucasfilm to plaintiffs.91 That information shows that Lucasfilm had a variety of compensation structure features including salary min, mid and max information, grades and job titles. 90. Former Senior Director of Human Resources Ms. Sharon Coker testified that Lucasfilm had a salary structure.92 “We had – yes, we had identified levels of positions within our salary structure all the way through nonexempt up to the executive level”. She confirmed they were maintained in written form, stating, “They were maintained, yes, in a database”.93 91. Ms. Coker also confirmed Lucasfilm’s use of noted job families: “… So production family can start with a production assistant, which is the entry-level position, and 88 Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013, page 70. Powerpoint, Leveraging Compensation and Performance, Intuit, January 7, 2005, exhibit 1761.19. 90 Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013, page 87. 91 Spreadsheet LUCAS00221117 (2007 – 2012). 92 Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 242. 93 Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 242. 89 May 10, 2013 Expert Witness Report of Kevin F. Hallock 595 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page31 of 120 29 work all the way up to an executive producer. And that would be what I would call a job family. So it’s the production job family”.94 92. She testified that salary ranges were related to: “…It was almost like an intersection, if you picture the grid. So within a family of jobs, like if you were to look at like technical positions or if you were to look at the production family, I’ll stay with that for a moment, there’s a hierarchy, if you will, of complexity of roles within a family, and that might be the horizontal part of the grid. The vertical part of the grid would be, you know, how do you level those positions with – across the board, to compare them to people in different job families”.95 93. There is additional evidence that Lucasfilm had formalized HR and compensation systems. For example, an internal presentation noted “job families,” “levels or bands,” “job title structure,” and “slot incumbents into the framework”.96 94. Additional evidence of formalized compensation or HR systems include the document reference: “Benchmarking: Lucasfilm will benchmark total cash compensation at for most positions, using compensation surveys that are relevant to the specific job or job family. Positions that are defined as highly competitive and/or highly critical to achieving business objectives such as all studio and technical positions are to be benchmarked at 97 95. Additional evidence for formalized systems for compensation and HR at Lucasfilm include a series of competencies and scales. For example, for the function “ADMINISTRATION/PRODUCTION/DIG TECHNOLOGIES” the following levels are listed, 94 Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 249. Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 250-1. 96 Powerpoint, Global Compensation Project, Lucasfilm Ltd., September 22, 2005, exhibit 944.9. 97 Powerpoint, PAY FOR PERFORMANCE: 2009 Salary Budget Recommendation, Executive Review, January 21, 2009, Lucasfilm, LUCAS00189288, exhibit 945.13. 95 May 10, 2013 Expert Witness Report of Kevin F. Hallock 596 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page32 of 120 30 “LEVEL I – ENTRY,” “LEVEL II – INTERMEDIATE,” “LEVEL III – SENIOR,” and “LEVEL IV SPECIALIST,” and four sets of competencies are listed “scope/complexity,” “knowledge & skills,” and “Supervision/ Discretion”.98 96. There is additional evidence that Lucasfilm had formalized HR and compensation systems. For example, Senior Manager, Compensation Michelle Maupin was asked in her deposition, “Can you tell me the approximate salary range for grade believe the midpoint , which is what is around the high would probably be around 97. ?” She answered, “I The low would probably be around and ”.99 A Lucasfilm PowerPoint presentation has other reference to formalized systems, noting “job grading,” “job match to salary survey data,” and “internal equity/factors”.100 98. Pixar: There is evidence that Pixar had formalized compensation systems. Included among this is data provided by Pixar to plaintiffs.101 That information shows that Pixar had many job titles. Additionally Pixar uses compensation data in percentiles (e.g. 10th, 50th, 90th).102 99. For example, Vice President of Human Resources and Administration Lori McAdams noted in her deposition, “We establish salary ranges for each of our positions, and an employee is offered or paid usually within that salary range”. She confirmed, “We participate in salary surveys in the industry and – and in – in various fields, and use that information to determine the appropriate salary range”.103 98 LUCAS00188750-LUCAS00188753, exhibit 959.43-959.46. Deposition of Ms. Michelle Maupin, February 12, 2013, page 39. 100 Powerpoint on pay design, LUCAS 00188763, exhibit 715.56. 101 See spreadsheet “Employee Type Count by Employer”. 102 See, for example, Survey collection forms: PIX00088222 (2009); Market survey results: PIX00056267 (2009); Matching employees to survey results: PIX00088115 (2009). 103 Deposition of Ms. Lori McAdams, August 2, 2012, page 29. 99 May 10, 2013 Expert Witness Report of Kevin F. Hallock 597 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page33 of 120 31 100. Ms. McAdams also noted the structure of the size of the ranges at Pixar: .104 101. Ms. McAdams also noted information about adjustments at Pixar: “Well, the salary range adjustments is something that’s done by human resources so that we have ranges for all of our established positions. And then the managers are provided any updated salary range information so that when they are distributing their salary increase pool, they know if someone is below – you know, they know where their people are in those salary ranges and can provide, you know – can spend their pool accordingly”.105 102. Ms. McAdams also was asked about Pixar’s use of salary surveys. “The Croner Survey is an industry specific survey that surveys positions in the animation and visual effects industry”.106 103. While Croner collects data for a broader collection of companies, Pixar sometimes request subsets of the data. When asked about the minimum number of companies that can be provided by the Croner Survey, Ms. McAdams replied “I think it’s five”.107 104. Information from the Croner Survey, used by Pixar (and other organizations) notes “hierarchy,” “job families,” and “positions,” all terms used in formalized compensation systems.108 105. Additional evidence of formal pay systems at Pixar are from Manager of Human Resources Stephanie Sheehy’s deposition. She was asked, “How are base salaries determined for Pixar employees?” She replied, “We use survey data for the most part”. She was then asked 104 Deposition of Ms. Lori McAdams, August 2, 2012, page 32. Deposition of Ms. Lori McAdams, August 2, 2012, pages 40-41. 106 Deposition of Ms. Lori McAdams, August 2, 2012, page 60. 107 Deposition of Ms. Lori McAdams, August 2, 2012, page 61. 108 2009 Croner Animation and Visual Effects Survey, January 8, 2009, PIX00001263, exhibit 119. 105 May 10, 2013 Expert Witness Report of Kevin F. Hallock 598 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page34 of 120 32 “What do you do with the survey data?” She replied “We use it as a guideline to help us determine the minimum salary/maximum salary for a job”.109 106. Ms. Sheehy confirmed Pixar used salary ranges at Pixar”.110 Later she was asked about job families and replied, “Job families are also called job groups, which I referred to earlier…They’re a grouping of employees that sit together in our structure”.111 107. Ms. Sheehy also testified that Pixar used both Croner and Radford market survey data. When asked about “the steps that you follow to use that data and make the salary ranges”, Ms. Sheehy answered “Let me think, is there a big difference between them? No, we use them pretty much the same, both Croner and Radford. So we have met with each manager and gotten a match for all the matches that are matchable. The employees that are matchable to a job in one of the two surveys. And we submit our data at certain points during the year. And then when we get our data back, we compare where the employee match range was that – , and where the employee presently is in their salary, what their current salary is, and we see where they land inside that range”.112 108. Ms. Sheehy also noted job groups at Pixar.113 This is another part of the formal pay structure. 109. Pixar, like other defendant organizations, considered salary increase budgets each year in considering changes to its pay systems. Pixar was also interested in what was happening at other companies, particularly Lucasfilm. For example, Ms. McAdams sent an email to staff from Lucasfilm, among others: “Quick questions from me, for those of you who can share this 109 Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 49. Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 50. 111 Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 78. 112 Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 88. 113 Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 136. 110 May 10, 2013 Expert Witness Report of Kevin F. Hallock 599 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page35 of 120 33 info. What is your salary increase budget for FY ’07? Ours is 4%, but we may manage it closer to 3% on average. Are you doing anything close, more, or less?”114 VI. Issues of Internal Equity 110. In the best-known text in compensation, by Milkovich, Newman and Gerhart (2014), Compensation, notes in the glossary under “equity theory,” “A theory proposing that in any exchange relationship (such as employment) the equality of the outcome/input ratios between a person and a comparison other (a standard or relevant person/group) will determine fairness or equity. If the ratios diverge from each other, the person will experience reactions of unfairness and inequity”.115 Issues of equity are clearly important not only in setting up the original structure of a compensation system but also when managing it. 111. There is substantial evidence that issues of internal equity and pay fairness were important to defendant firms. 112. Adobe: There is evidence that Adobe followed principles of internal equity. For example, one document notes a section on the issue of a “Counter Offer”. It states “ .116 The capitalized “ALWAYS” is in the original. 114 Email from Lori McAdams, Pixar, November 17, 2006, LUCAS00184664, exhibit 122. Milkovich, Newman and Gerhart (2014), page 680. 116 Powerpoint, Retention/Transition Guidelines, Adobe, June 2008, ADOBE_050724, exhibit 216.5. 115 May 10, 2013 Expert Witness Report of Kevin F. Hallock 600 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page36 of 120 34 113. An additional mention of internal equity at Adobe is in the deposition of Mr. Digby Horner, Adobe’s Senior Vice President of Engineering. In reference to an email exchange he had with colleagues that discussed the possibility of raising the pay of an employee “off cycle,” a list of employees in similar positions at Adobe was included in the message.117 Mr. Horner was asked, “Is it fair to say that you want to consider how peers are being compensated to make sure that the compensation he receives is fair in comparison to them?” He replied, “Yeah. What I would – what I would say here is that, you know, the primary thing I look at is – so that – that’s a term that we use internally, which is internal equity.”118 114. Similarly, in 2008, Senior Vice President of Global Human Resources Donna Morris sent a message with the subject “final review of salaries,” indicating, “I have just finished the full review of all salary and stock, and would like to recommend some changes relative to your organization. ”119 115. Ms. Morris also references internal equity in a series of emails to Adobe’s CEO Shantanu Narayen. In the first, Ms. Morris wrote concerning a job candidate, 120 117 Email from Ms. Jocelyn Vosburgh, Adobe, October 25, 2010, ADOBE_011976-7, exhibit 1250.1-2. Deposition of Mr. Digby Horner, Adobe, March 1, 2013, page 200. 119 Email of Ms. Donna Morris, Adobe, January 18, 2008, ADOBE_009425, exhibit, 2501.1. 118 120 Email from Ms. Donna Morris, Adobe, March 4, 2007, ADOBE_005661, exhibit 1158. May 10, 2013 Expert Witness Report of Kevin F. Hallock 601 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page37 of 120 35 116. In a different email, Ms. Morris wrote Mr. Narayen, “Shantanu – Please find attached proposed promotional compensation packages for and taking into account market and internal equity ….”121 117. In another exchange between Ms. Morris and Adobe’s CEO Mr. Narayen, she wrote about the compensation for a potential new hire and then listed names and initials of four people and some details of their compensation, including base and total cash compensation, under the caption “internal equity.”122 118. At his deposition, Mr. Narayen was asked about this third email exchange and what he meant when he emailed Donna Morris, “Does that cause any internal inequities?”123 He testified, “I think it would have related to, from a scope point of view and a performance point of view, are you looking at that?”124 119. Ms. Rosemary Arriada-Keiper also confirmed that internal equity was a principle used at Adobe. “We use internal equity primarily in the capacity of looking at, again, typically new hires …”.125 She explained, “So myself, as an example, if I’m bringing in somebody from the outside and I’m thinking about what’s this offer that I want to make to this individual, I will generally look at my team and see where they’re positioned, you know, and kind of make a judgment call there. Because I do know that these individuals are going to be working side by side, and you know, it can potentially have implications for me as a manager if they’re performing exactly the same way and they feel like there is not a perceived fairness in terms of their pay, right?” She further stated, “A conversation to have to explain to the individual why I made the decision that I did, right? And there may be reasons for why I do that, and I’m 121 Email from Ms. Donna Morris, Adobe, June 5, 2010, ADOBE_019278, exhibit 1159. Email of Ms. Donna Morris, Adobe, June 13, 2011, ADOBE_9652, exhibit 1160. 123 Email of Mr. Shantanu Narayen, Adobe, June 14, 2011, ADOBE_9652, exhibit 1160. 124 Deposition of Mr. Shantanu Narayen, Adobe, February 28, 2013, page 319. 125 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 122. 122 May 10, 2013 Expert Witness Report of Kevin F. Hallock 602 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page38 of 120 36 perfectly comfortable with it. And in other instances, I may say you know what? It’s not worth it to me. I don’t want to create an issue where five people are going to be pissed off because this person, you know, makes more than them and haven’t been here to prove themselves. So I have to rationalize that as a manager.”126 120. Apple: There is evidence that Apple followed principles of internal equity. Mr. David Alvarez, Apple Recruiting Manager, testified that when making an offer to a new hire one of the factors to consider in compensation is internal equity. When asked, “What do you mean by ‘internal equity’”?127, Mr. Alvarez responded “What the population of – let’s say if a candidate’s coming in at a certain level, we look at someone in that organization at that level to see what everybody’s making. So who’s the low, the average and the high. That’s what internal equity is. There’s a lot of calibration to it, so there’s a lot of avenues that we take to come up with that recommendation”.128 121. Former recruiter Darrin Baja testified that he was familiar with the term “internal equity” and that it was a term used in discussing compensation at Apple.129 122. Mr. Baja was asked “So, for example, if you were hiring somebody onto a team, and they were doing a job function that was similar to what the other people on the team were doing, you would look to what the other people on the team were making for comparative purposes in setting the salary of the new hire?” He replied “That is one thing we would do, yes.”130 123. In an email message in response to a suggested level of compensation for a candidate, Mr. Rob York wrote 126 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, pages 124-5. Deposition of Mr. David Alvarez, Apple, March 5, 2013, page 30. 128 Deposition of Mr. David Alvarez, Apple, March 5, 2013, page 30. 129 Deposition of Mr. Darrin Baja, Apple, March 1, 2013, page 43. 130 Deposition of Mr. Darrin Baja, Apple, March 1, 2013, page 44. 127 May 10, 2013 Expert Witness Report of Kevin F. Hallock 603 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page39 of 120 37 131 Mr. David Alvarez was asked about this message: “So in setting salaries that would be components of offers for candidates Apple was interested in hiring, was what a candidates peer group was receiving an important consideration”? Mr. Alvarez responded “That’s what we call internal equity”.132 124. Internal equity is also discussed by Director of Executive Recruiting Mr. Richard Bechtel, although he noted that he uses “the term ‘internal parity’ just to stay away from the term ‘equity,’ which can also mean RSUs and options. But internal parity is – yeah, yes, it does come up”.133 Mr. Bechtel was later asked “So would it create a problem from the standpoint of internal parity to offer a new hire more in compensation than is being paid to that new hire’s peers who have the same job function?”134 Mr. Bechtel responded “Yeah. It’s – it’s something that – it’s something that we would definitely want to be aware of. We would want to be sensitive to it and we’d want to know why we were paying somebody more coming in than somebody who is, you know, their peer that’s performing at a good level. And there have been circumstances that we’ve done that, but there’s been business reasons for it”. He was then asked “Well, why would you want to be sensitive about that?” Mr. Bechtel responded “I – we – it – because people that are good employees at Apple, that are doing good work, that are wellrespected, and that are performing at a high level, you know, we – we want to – we want to make sure we’re doing right by them”.135 125. There is other information at Apple that indicated that internal comparisons and equity mattered. Former recruiter Patrick Burke, was asked “So during your time, you hired or recruited engineers, correct?” He said “That’s all I did. Yes”. He was then asked, “Now, for 131 Email from Mr. Rob York, Apple, on December 17, 2010, 231APPLE039427, exhibit 1376.2. Deposition of Mr. David Alvarez, Apple, March 5, 2013, page 208. 133 Deposition of Mr. Richard Bechtel, Apple, March 7, 2013, page 40. 134 Deposition of Mr. Richard Bechtel, Apple, March 7, 2013, pages 43-4. 135 Deposition of Mr. Richard Bechtel, Apple, March 7, 2013, page 44. 132 May 10, 2013 Expert Witness Report of Kevin F. Hallock 604 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page40 of 120 38 any particular engineering candidate, how was the salary range established for that potential candidate?” Mr. Burke replied “It wasn’t a salary range determined, it was what salary we were going to offer”.136 He then went on to say “And how that was determined was mostly asking the hiring manager who they compared to in the team, looking at the candidate’s education, experience, and knowledge within that experience, and comparing that to different people on their team. And these were the biggest deciphering things. . And that’s more what determined it. And then sometimes, depending on where – the number that we determined for a particular candidate, , and that’s where kind of sometimes HR would get involved to do it. But it was generally guided by other people on the team and how they compared to them”.137 126. Mr. Burke confirmed that it was important not to pay new people more than those already working at Apple.138 “That was a determining factor, but it was, again, more about how they compared to those people. And so the hiring manager would usually not want to pay more than a person with similar or more experience at Apple. So we called it internal equity or fair compensation. And we would want to kind of keep it fair to the team on board. Just because this person was asking for more money than someone with similar experience on the team didn’t mean we just gave it to him. We would keep it fair to the people, and .139 136 Deposition of Mr. Patrick Burke, Apple, February 26, 2013, page 37. Deposition of Mr. Patrick Burke, Apple, February 26, 2013, pages 37-8. 138 Deposition of Mr. Patrick Burke, Apple, February 26, 2013, pages 42-3. 139 Deposition of Mr. Patrick Burke, Apple, February 26, 2013, page 43. 137 May 10, 2013 Expert Witness Report of Kevin F. Hallock 605 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page41 of 120 39 127. Apple’s Senior Director of Compensation Mr. Steve Burmeister was asked “Have you heard the term ‘internal equity’”? He replied “I’ve – in a compensation speak language, we use the term ‘internal equity’”. He elaborated “Internal equity means, to me, that what you’re looking at, if you’re looking at compensation, that it’s fair based on the individual’s contribution relative to the other employees in your group, or across your organization, whatever your scope of management is”. When asked “Is there an internal equity component to determining starting salaries at Apple?”140 Mr. Burmeister replied “It – internal equity plays into a few, if not all, of these bullets for managers to consider when looking at a candidate to determine a new starting salary”.141 128. There are two other issues related to this issue in an Apple document. A document notes On the same page of that document, it is noted 142 129. Google: There is evidence that Google followed principles of internal equity. For example, a PowerPoint presentation about determining base salary shows 140 Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 63. Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, pages 63-4. 142 Powerpoint, Compensation Framework, Insuring Global Consistency, Apply, 231APPLE105345, exhibit 1856.4. 141 May 10, 2013 Expert Witness Report of Kevin F. Hallock 606 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page42 of 120 40 .143 130. Another Google document is related to equity issues. Figure 12 is a reproduction of a Google document.144 On the vertical axis is the employee performance rating. The document indicates that the ratings go from . On the horizontal axis the “pre-adjustment position” is listed. .145 131. . For example, consider someone with the very-highest performance rating his or her merit increase will be ). If that person has a pre-adjustment position of but if that person has a pre-adjustment position of his or he merit increase will be only performer Also consider someone who is rated as an average If that person is at a pre-adjustment position of merit increase will be his or her but if that person has a pre-adjustment position of his or her merit increase will be , .146 This system essentially is consistent with bringing salaries in a group back together over time. 132. The preceding example is a structured situation that shows that issues of equity need not immediately lead to compensation changes. However, equity can have serious and large implications for compensation over short, but not immediate, periods of time. 133. There is a reference to internal equity in an email from Compensation Team Member Ms. Tiffany Wu, indicating “ 143 Powerpoint, Compensation Components Setting a Base Salary, GOOG-HIGH-TECH-00036302, exhibit, 1606.16. 144 Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11. 145 Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11. 146 Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11. May 10, 2013 Expert Witness Report of Kevin F. Hallock 607 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page43 of 120 41 147 134. In another Google document the FAQ section contains this question and answer: 148 135. There is also evidence of this from other defendants but not in such a tabular form. Some of this is directly related to discussions of equity. There are other instances, for example at Apple. For example, Mr. Ron Okamoto wrote an email with respect to raises, .149 136. Mr. Okamoto was asked about this in his deposition. He said, “And so the question is, when that happens, what do you do? .150 147 Email from Tiffany Wu, September 7, 2007, Goog-High-Tech-00473658, exhibit 1613. Google document, GOOG-HIGH-TECH-00474908, exhibit 1618.12. 149 Email from Mr. Ron Okamoto, Apple, September 17, 2010, 231APPLE099371, exhibit 1130.1. 150 Deposition of Mr. Ron Okamoto, Apple, February 27, 2013, page 135. 148 May 10, 2013 Expert Witness Report of Kevin F. Hallock 608 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page44 of 120 42 137. Intel: There is evidence that Intel followed principles of internal equity. For example, in a PowerPoint document from 2002 titled, “NPG Human Resources Job Leveling & Pay Equity Review,” Intel noted, ”151 The same document states a few pages later: 152 and 153 138. Another Intel PowerPoint from 2005 describes a .154 139. has a section, Likewise, the document titled “Manage Offer Module Develop External offer” There it is noted The document also instructs, 151 Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388, exhibit 392.3. 152 Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388, exhibit 392.5. 153 Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388, exhibit 392.5. 154 Powerpoint, TMG Non-Tech Job Audit – HR, Intel, August 25th, 2005, 76583DOC008097_000003, exhibit 397.3. May 10, 2013 Expert Witness Report of Kevin F. Hallock 609 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page45 of 120 43 140. A document referencing internal equity is a spreadsheet stating .156 Another document notes a number of suggested actions that would seem to be directly consistent with equity. For example, So this suggests merit pay be reduced based on information about a person’s position in salary range in the job. This also suggests that relatively higher paid individuals (among a set of peers at Intel) would have relatively smaller raises. This continues similarly for other situations. For example, in the situation where a 157 141. A PowerPoint discussing “Base Pay Comparison,” notes that when 158 155 Document, HR Global Staffing, Manage Offer Module, Develop External Offer, document Version 1.3, February 13, 2009, 76579DOC005963, exhibit 398.8. 156 Intel spreadsheet 76579DOC005152_000017. 157 PowerPoint, Base Pay Comparison Report Support Overview WW 042011, 765825DOC001211, exhibit 400.17. 158 PowerPoint, Base Pay Comparison Report Support Overview WW 042011, 765825DOC001211, exhibit 400.17. May 10, 2013 Expert Witness Report of Kevin F. Hallock 610 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page46 of 120 44 142. An Intel document from 2008 questioned, “Are there specific areas where we are experiencing market/internal equity issues?”159 143. Similarly, in a document called “Worldwide Focal 2001 Questions and Answers. Intel Confidential,” the following question and answer appear: 144. 145. 160 146. In reference to the document mentioned above161, Worldwide Focal 2001 Questions and Answers, Intel Confidential, Deborah Conrad was asked, She replied ”162 147. Ms. Conrad testified that .163 “Yes, that could be – that could be one of the things that you would look at.”164 159 Powerpoint, Internal Climate, Intel, 76596DOC017025, exhibit 781.16. Worldwide Focal 2001 Questions and Answers Intel Confidential, Rev 13, Feb 26, 2001. 76583DOC003753, exhibit 391.4. 161 Worldwide Focal 2001 Questions and Answers Intel Confidential, Rev 13, Feb 26, 2001. 76583DOC003753, exhibit 391.4. 162 Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 202. 163 Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 204. 160 May 10, 2013 Expert Witness Report of Kevin F. Hallock 611 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page47 of 120 45 148. Ms. Conrad also testified about her understanding of the term internal equity. “I understand the term to mean people doing a relatively similar – complexity similar of their job are being compensated in a similar way. So we talked about the grade level example”. Ms. Conrad continued, “A grade-level engineer and – a grade level 12 engineer, a grade level 12 project manager, a grade level 12 software person are being compensated based on complexity of that role, and there’s a range that – of the compensation that is allocated to that grade, and that gives us equity across – internally across job function.”165 149. CEO Paul Otellini noted in an email, ”166 The fact that those with relatively high levels of pay as compared to their peers are exempt from raises is consistent with internal equity. 150. Ms. Renee James, Manager of Intel’s Software Services Group, testified that she understood internal equity to mean: “A set of criteria that we use to in aggregate check between different people in the same grade band across a variety of metrics, performance, pay, equity”.167 She also noted, “I think internal equity is aspirational. I think it is a guideline that helps you look at, you know, apples and oranges data and give you a sense of what’s going on, 164 Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 204-5. Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 50. 166 Email from Mr. Paul Otellini, Intel, January 22, 2010, 76616DOC012164, exhibit 478.1. 167 Deposition of Ms. Renee James, Intel, March 22, 2013, pages 242-3. 165 May 10, 2013 Expert Witness Report of Kevin F. Hallock 612 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page48 of 120 46 168 As I note elsewhere and I think is implied here, concepts of equity and pay and performance are not independent. They can also be used simultaneously. 151. Intel Vice President of Human Resources Ms. Patricia Murray also testified about her understanding of the term “internal equity.” “My general understanding of internal equity, it is a process by which a manager or group of managers or even a department judges whether people are being paid fairly next to one another inside the company.”169 152. Intel Compensation and Benefits Specialist Daniel McKell explained his understanding of the use of the term “internal equity” at Intel: “internal equity means fairness. Typically, when we talk about internal equity, it’s how employees are paid relative to each other. It can also be part of that – “egalitarian” is another term that we would say – so from an internal equity perspective, everybody participates in stock even though they have different grades. So it has multiple meanings depending on the specific context, but generally is mean fairness”.170 153. Mr. McKell testified about HR’s “ explaining, ”171 154. In a 2005 email, Mr. McKell wrote: ”172 Mr. McKell explained that 168 Deposition of Ms. Renee James, Intel, March 22, 2013, page 244. Deposition of Ms. Patricia Murray, Intel, February 14, 2013, page 40. 170 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 207. 171 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 210. 172 Email from Danny McKell, Intel, February 2005, 76657DOC004599, exhibit 2033. 169 May 10, 2013 Expert Witness Report of Kevin F. Hallock 613 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page49 of 120 47 173 155. In reference to the same e-mail, Mr. McKell testified that he had written that internal equity “looks pretty good” because “…the people that they had brought in were generally being paid about the same as existing Intel employees.”174 156. Mr. McKell also testified about Intel’s merit budgets. .175 Note that it is my understanding in this context that Q is referring to quartile in range with Q1 being the smallest quartile and Q4 being the largest (elsewhere in documentation from the defendants Q sometimes refers to quarter of the year). So this suggests that for a given level of performance (e.g. “successful”), those higher in the pay range in advance of the performance rating have a lower suggested raise. 157. Mr. McKell explained, “… so there’s a series of goodies that a manager can allocate, and peanut butter means trying to spread it out as far as it can go”.176 He was then asked, He replied, 173 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 227. Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 228. 175 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 100. 176 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 188. 174 May 10, 2013 Expert Witness Report of Kevin F. Hallock 614 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page50 of 120 48 177 Mr. McKell was asked, ”178 158. In my view it is certainly easily possible for organizations to have both a pay for performance system in place, while simultaneously stressing equity and related concepts. In fact, Intel’s Daniel McKell testified that the philosophies of both internal equity and meritocracy exist at Intel. “They do exist. I don’t believe that they’re mutually exclusive. I think meritocracy definitely exists in pay raises and bonus changes and stock grants, and that it is effective. I also think internal equity exists, because managers look at pay fairness relative to what each employee is making, and makes decisions based on that – whether somebody is too high or too low relative to their peers. So I think there are good checks and balances on each other.”179 159. Intuit: There is evidence that Intuit followed principles of internal equity. For example, Director of Talent Acquisition Chris Galy testified about Intuit’s practice of benchmarking and considering external and internal employees when setting new hire pay: Again, it’s a data point. 177 Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 189. Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 190. 179 Deposition, Mr. Daniel McKell, Intel, March 20, 2013, pages 269-70. 178 May 10, 2013 Expert Witness Report of Kevin F. Hallock 615 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page51 of 120 49 180 160. Another example that the pay of one person mattered relative to that of another is included in this testimony from Mr. Galy: Q. “Can you give me a personal example or example about which you have some personal knowledge of an off-cycle pay action?”181 A. Q. “I see. A. “Right. Q. “Okay. A. “ 182 Q. “Is it possible that this is one of the situations in which a manager might – or the business leader might have to go to his manager and ask for a bigger compensation budget?” A. “Yeah.”183 This very last part indicates that budgets are not always fixed for increases. In fact, sometimes additional resources are gathered and pay is even increased off-cycle. 180 Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 180-1. Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 194-5. 182 Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 195. 183 Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 195-6. 181 May 10, 2013 Expert Witness Report of Kevin F. Hallock 616 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page52 of 120 50 161. An email Mr. Galy forwarded also mentions internal equity. That email stated: 184 162. An Intuit document titled “Talent Acquisition Hiring Plan” also noted internal equity. In one section, this hiring plan noted 185 163. There is also mention of “internal equity” in another Intuit document from 2005 that mentions and notes, 186 164. An additional Intuit document mentions equity. On a page titled 187 165. Lucasfilm: There is evidence that Lucasfilm followed principles of internal equity. For example, Lucasfilm Senior Manager, Compensation Michelle Maupin was asked “Do you think fairness was considered at all prior to 2006 in setting employee salaries?” She replied “What do you mean by ‘fairness’”? She was then asked “Was internal equity considered at all prior to 2006 in setting employees’ salaries?” “Based on my knowledge and information that I have seen, documents I’ve looked at in the past, yes”.188 184 Email from Mr. Chris Galy, Intuit, March 3, 2010, INTUIT_039793, exhibit 2142.1. Document from Intuit, Talent Acquisition Hiring Plan, INTUIT_007866, exhibit 1107.2. 186 Powerpoint, INTUIT Total Rewards & Pay Decisions Toolkit, Intuit, May 2005, INTUIT_043560, exhibit 2739.31. 187 Powerpoint, Focal Decisions 2005, Communications Session for Senior Managers, June 2005, Intuit, INTUIT_052841, exhibit 2740.16. 188 Deposition of Ms. Michelle Maupin, February 12, 2013, page 85. 185 May 10, 2013 Expert Witness Report of Kevin F. Hallock 617 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page53 of 120 51 166. Ms. Maupin also testified, “I would anticipate that if a junior level or a junior- skilled employee was at the same or same pay level as a senior employee, that might cause dissatisfaction for even the manager of those employees.”189 167. Ms. Maupin was asked, “Can you explain the significance of peer relationships in setting compensation at Lucasfilm?” She replied, “The significance is to consider individual employees’ pay within a similar job and pay range using the same type of skill sets to appropriately align those employees relative to their peers and to market.”190 168. In her declaration, Ms. Maupin also noted equity: “Lucasfilm occasionally adjusts salaries outside of the April pay-for-performance process. These are referred to as outof-cycle increased and are given for promotions, and equity adjustments. An equity adjustment is intended to bring an employee’s compensation more in line with (but not necessarily equal to) internal peers or the targeted percentile or external peer compensation.”191 169. Ms. Michelle Maupin stated by email: “…Janetta has already told him I don’t agree with Unless we want to raise salaries of the other EA’s [sic], I think this is fair.”192 170. In questioning related to an email from Ms. Maupin to Chief Administrative Officer Jan van der Voort where Ms. Maupin wrote, “Internal equity is a concern, although we 189 Deposition of Ms. Michelle Maupin, February 12, 2013, page 175. Deposition of Ms. Michelle Maupin, February 12, 2013, page 178. 191 Declaration of Ms. Michelle Maupin, January 17, 2013, page 9. 192 Email from Ms. Michelle Maupin, November 4, 2010, LUCAS00198130, exhibit 729.1. 190 May 10, 2013 Expert Witness Report of Kevin F. Hallock 618 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page54 of 120 52 just hired …”193 Ms. Maupin was asked, “Was the internal equity concern that might be paid more than her colleagues?” She answered, “In some cases.”194 171. In another situation at Lucasfilm, Ms. Jan van der Voort wrote a message noting, “Steve, I think this needs Jim Ward’s buy-in … at this level, we’re getting in to some interesting internal equity issues, which I want Jim to be aware of before I decide.”195 172. Ms. Van der Voort testified about her familiarity with internal equity at Lucasfilm. “It means generally that you are aware of where similarly situated employees are from a compensation perspective, either within their division or across the company depending on what you are looking at.” Then she was asked, “Is internal equity a consideration in setting salary grades?” She replied, “It is a consideration, yes.”196 173. Senior Director of Human Resources Sharon Coker discussed internal equity in her deposition. “Internal equity is that people within the company, internally within the company – and it has nothing to do with what the market pays, if you want to be literal with it. But internal equity then means that at my company I’m paid comparably – not exactly, but I’m paid comparably to other people with the same set of experience and same level of performance for doing, the same work.”197 174. Ms. Coker was asked, “Did you understand the idea of – concept of Lucas – excuse me, the idea of internal equity to be something that all sorts of companies thought about when constructing or modifying their compensation structures”?198 She answered, “Absolutely. 193 Email from Ms. Michelle Maupin to Jan van der Voort, May 8, 2008, LUCAS00201069, exhibit 727.3. Deposition of Ms. Michelle Maupin, February 12, 2013, page 182. 195 Email from Ms. Jan van der Voort, July 9, 2007, LUCAS00060705, exhibit 728.1. 196 Deposition of Ms. Jan van der Voort, February 5, 2013, page 200. 197 Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 259. 198 Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 259-60. 194 May 10, 2013 Expert Witness Report of Kevin F. Hallock 619 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page55 of 120 53 And if the company didn’t, the employees would remind them. So, you know, again, I think it’s – it is – internal equity is a consideration in compensation decisions.”199 175. Ms. Coker also noted in her deposition, “… I would say that almost always when you made – not always, but often if you would make an individual decision, it could impact other employees in similar positions. So you had to look at that.”200 176. Ms. Coker testified about internal equity: “…internal equity would be – it could mean two things. One is it could mean that there were a group of employees in a job family doing similar work and at one company, perhaps even they were paying X or a range of X to Y for those positions. Across the street, more or less in one of the other divisions, they might be paying from X to Z for those positions. So it was within Lucas companies are there any – can we identify any areas where we have, you know, what I would call a ‘pay discrepancy,’ where we’re not paying within reason within ranges.”201 177. There are multiple references to “call out for equity” in an email from Ms. Vanessa Hall at Lucasfilm.202 178. Internal equity is also noted in an additional Lucasfilm document from 2004: “Evaluate Internal Candidates’ qualifications against market value and internal equity.”203 179. Likewise, a Lucas film document from 2006 mentions “Gathering input on comp issues” including “internal equity”.204 180. Pixar: There is also evidence that Pixar followed principles of internal equity. In her deposition, Pixar Vice President of Human Resources Lori McAdams was asked, “Now, how 199 Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 260. Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 245. 201 Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 283. 202 Email from Ms. Vanessa Hall, February 14, 2011, LUCAS00199905-6. 203 Compensation Analysis and Review Process, Internal Transfer, DRAFT Last Updated 11-23-04, LUCAS00185312, exhibit 716. 204 Powerpoint, Lucasfilm Ltd. Compensation Project Status Executive Review, Lucasfilm, December 7, 2006, LUCAS00027982, exhibit 359.4. 200 May 10, 2013 Expert Witness Report of Kevin F. Hallock 620 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page56 of 120 54 is the compensation of a new employee – how is the base salary of a new salaried employee determined?” She answered, “We look at their experience and education and how we evaluate them against existing employees – and make them an offer relative to their experience and – and our existing talent”.205 Note the reference to existing talent. 181. While not directly using the term “equity” the deposition of Stephanie Sheehy describes related issues. She notes, “The goal of this new salary proposal is to compensate the lowest paid team-members who are performing at the highest levels. This is a ‘pre-emptive strike’. We want to send a clear message to these engineers that we value them at least as much as some new hires who are seeing much more competitive offers from other companies.”206 VII. Internal Equity and Pay for Performance Are Not Mutually Exclusive 182. In this section I discuss the issues of pay for performance and internal equity. Both pay and performance and internal equity are often-discussed in the realm of compensation. I discuss here that it is possible to have a compensation system that is simultaneously consistent with pay for performance and also with internal equity. 183. The Google Figure 12 is quite interesting since it is an example in one space where one can see a system that reflect both “pay for performance” and equity concerns at the same time. 205 206 Deposition of Ms. Lori McAdams, August 2, 2012, page 32. Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 151. May 10, 2013 Expert Witness Report of Kevin F. Hallock 621 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page57 of 120 55 184. Adobe also has information that is very similar to the Google Figure 12. In Table 13, I have included the left 1/3 (the part that is relevant for the United States) on “salary increase matrices”.207 The table has two parts. The top is for managers. The bottom is for “individual contributors”208 (IC). It is clear from Table 13 for Adobe that, again, . 185. I found what appears to be similar information at Apple. In an Apple document209 there appears to be evidence that 186. From a different Adobe PowerPoint slide, I have used information to create Figure 15 which is a matrix the vertical axis of which (rows) appears that it could be performance rating with “HI” as highest, “SC” the middle ranking and “LP” the lowest ranking.211 In fact, Ms. Arriada-Keiper is asked at one point about three levels of performance: “What were the three levels of performance when there were three?” and she replied “HHI, solid and low”.212 The shorthand for all three appears to match three of the four in Figure 13. 207 Powerpoint, 2010 Annual Performance Review, Compensation Training for Managers, December 2009, ADOBE_100614, exhibit 2487.15. 208 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 165. 209 Powerpoint, Total Rewards Planning, FY07, September 2006, Apple, 231APPLE095052, exhibit 1855.107. 210 Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 122. 211 Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33. 212 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 96. May 10, 2013 Expert Witness Report of Kevin F. Hallock 622 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page58 of 120 56 This expresses the same concept as in previous examples for Google (Figure 12), Adobe (Figure 13) and Apple (Figure 14).213 187. Intel also has a document that appears to be consistent with these ideas but is not in a tabular format.214 In this document there are various and then that I have reproduced in Figure 16. .215 Each of these scenario and action pairs is consistent with the examples in Google (Figure 12), Adobe (Figure 13) and Apple (Figure 14). 188. So there is direct evidence of compatibility between principles of internal equity and pay-for-performance that I found from four of the defendant companies (Google in Figure 12, Adobe in Figure 13 (and perhaps Figure 15 if I have interpreted those data correctly), Apple in Figure 14 and Intel in Figure 16. These examples make explicit that the companies give relatively lower raises to those who are relatively more highly paid in a given grade for a given performance level. 189. There is also evidence of this from other defendants but not in such an express tabular form. Some of this is directly related to discussions of equity. There are other instances, for example at Apple. There, Mr. Ron Okamoto wrote an email with respect to raises, “An 213 Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33. Powerpoint, Base Pay Comparison report Support Overview WW 042011, 765825DOC001211, exhibit 400.17. 215 Powerpoint, Base Pay Comparison report Support Overview WW 042011, 765825DOC001211, exhibit 400.17. 214 May 10, 2013 Expert Witness Report of Kevin F. Hallock 623 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page59 of 120 57 216 190. Mr. Okamoto was asked about this in his deposition. He said “And so the question is, when that happens, what do you do? .217 191. It can be shown that pay and performance and issues of equity are not mutually exclusive in other ways. Consider two employees in a work group who are both paid a base salary and a “commission” or piece-rate for some level of output (say sales of some item such as a book or car). Arranging the system so that appropriately grouped workers have similar base salary and commission rate is certainly equitable. At the same time, this compensation system has a pay for performance component. VIII. How Restricting Cold Calling Can Restrict Information and Pay 192. Restricting cold calling can clearly restrict information and pay. In many markets, employees are hired due to cold calls.218 193. This can be illustrated by the findings of the Court in this case. “Plaintiffs have set forth evidence of Defendants’ anti-solicitation agreements, which were memorialized in CEO-to-CEO emails and other documents, such as ‘Do Not Call’ lists putting each firm’s 216 217 Email from Mr. Ron Okamoto, Apple, September 17, 2010, 231APPLE099371, exhibit 1130.1. Deposition of Mr. Ron Okamoto, Apple, February 27, 2013, page 135. 218 There is a difference between an organization’s product market competitors and its labor market competitors. Some organizations may not compete in the market for goods and services. Nevertheless, they may hire from among the same pool of workers. May 10, 2013 Expert Witness Report of Kevin F. Hallock 624 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page60 of 120 58 employees off-limits to other Defendants.”219 “The question presented by this case is not whether Defendants’ anti-solicitation agreements had an impact on any employees. Defendants concede that some employees may have been impacted. See Tr. at 144:11-12 (‘And I admit at the start, we are not saying that nobody was impacted.’).”220 194. In the instance of this case, the defendant firms limited the market for the employees by restricting cold calling. This clearly led to what would otherwise be higher levels of compensation for some of those in the firms, except that the restrictions were in place. 195. This situation of lower levels of compensation for some can directly lead to lower levels of others due to the very nature of the formalized pay systems in place at the defendants. This is even more likely among the technical class consisting of those described in Appendix B to the October 1, 2012 Expert Report of Dr. Edward E. Leamer, and who worked for a Defendant while that defendant participated in at least one “no cold-call” agreement with another defendant. 196. The formalized systems in place at the defendants relied on structures, external data from the market and the like, and notions of equity were present at defendants. As a result, those effects cycle on to other employees and their levels of compensation. Therefore, the formal compensation structures could lead to an effect on nearly all class members. 197. In a very strict simple supply and demand model with perfect competition and immediate complete information prices of all sorts can adjust immediately. But many markets don’t hold all of these characteristics or behave this way. Some economists discuss the idea that workers are paid their value at any given time. But we know of many instances where pay changes at discreet moments and surely this is not always coincident with discreet changes in productivity. 219 220 Order by Judge Lucy H. Koh, Case5:11-cv-02509-LHK Document382 Filed04/05/13, pages 11-12. Order by Judge Lucy H. Koh, Case5:11-cv-02509-LHK Document382 Filed04/05/13, page 13. May 10, 2013 Expert Witness Report of Kevin F. Hallock 625 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page61 of 120 59 198. An example of this is when someone gets a raise at a point in time or when he or she changes jobs for a higher level of compensation or when, in response to new information, compensation levels change. Take for example the email from Mr. Arnnon Geshuri from Google where he notes 221 ”.222 Surely, calling in to employees they previously were not contacting could have positive effects on the compensation of those to whom they would call, either at their current employer, elsewhere or at Google. 199. An additional example of a rapid change in compensation due to new information comes from Intuit. Mr. Alex Lintner was asked “Are you aware of any instances in which Intuit has identified employees who should be the focus of retention efforts?” He replied “Oh, yes. Lots of them. We go through that all the time. 221 222 GOOGLE-High_Tech-00379327, exhibit 614, email from Mr. Arnnon Geshuri on Saturday March 15, 2008. GOOGLE-High_Tech-00379327, exhibit 614, email from Mr. Arnnon Geshuri on Saturday March 15, 2008. May 10, 2013 Expert Witness Report of Kevin F. Hallock 626 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page62 of 120 60 .223 200. Again, not all markets react immediately since information is not always perfect to all parties to a transaction. In fact, due to issues of internal comparisons, sometimes individuals are hired from the outside (for example) and have relatively higher levels of compensation than others in their workgroup, even once performance is taken into account. As a result, they may see slower growth of pay, relative to others in a similar job as a way to bring compensation together. This is an interesting issue and suggests that issues of internal equity are not necessarily immediately solved. That is, whether bringing in a new person with a higher wage to a new workgroup or raising the wage of someone in a work group does not necessarily mean that the levels of compensation of everyone else need be raised immediately also. Equity in this sense does not mean that all needs to immediately adjust. But equity can still be an issue for the organization that they can solve over time. IX. How A Structured Compensation System Can Be Related to Systematic Compensation Effects 201. A structured compensation system of the type I have described here can lead to systematic pay effects. In fact, entire pay systems can change at once and everyone can be affected. The concept of equity is related; this is common in the compensation area and widely known by practitioners who design pay systems in organizations. 202. In a recent book (Hallock, 2012), I wrote about what is known as “equity theory,” among a set of psychological theories that are important to compensation. I wrote, “The idea behind equity theory (Adams, 1965) is that workers will be motivated when their perceived 223 Deposition of Mr. Alex Lintner, Intuit, March 25, 2013, pages 107-8. May 10, 2013 Expert Witness Report of Kevin F. Hallock 627 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page63 of 120 61 inputs (e.g. effort) match their perceived outputs (e.g. pay). If someone thinks she is being unfairly paid (e.g. others are being paid more for the same perceived effort), she will become uncomfortable and unmotivated”.224 203. Milkovich, Newman and Gerhart (2011) also discuss equity and fairness.225 In fact, issues related to internal equity are one important reason organizations set up internal pay structures as discussed above. Recall that those structures are typically set up internally, even before going to the external market data. 204. Milkovich, Newman and Gerhart (2011) note that “the research suggests that employers judge the fairness of their organization’s internal pay structure by making multiple comparisons” including “comparing to jobs similar to their own,” “comparing their jobs to others at the same employer,” and “comparing their jobs’ pay against external pay levels”.226 205. Google’s “big bang” compensation increase is an important example of how a stimulus that may appear on the face to affect only a subset of employees, affected all employees. In this example, all employees of Google were given an instantaneous raise of 10%. Google’s former Senior Vice President of People Operations (HR) Ms. Shona Brown notes “… we unilaterally, in other words, without a performance orientation to it, we looked across the whole company and we said we’re going to give a ten percent – it doesn’t – it was a percentile but still, we gave it to everybody”.227 206. Other organizations commonly move the entire pay structure all at once, at least annually. Refer again to Figure 1. This is an example from the U.S. Government’s salary table. This entire table can change from year to year. Other examples of this include unionized 224 Hallock (2012), page 121. See Milkovich, Newman and Gerhart (2011), page 83. 226 Milkovich, Newman and Gerhart (2011), page 83. 227 Deposition of Dr. Shona Brown, Google, January 30, 2013, page 232. 225 May 10, 2013 Expert Witness Report of Kevin F. Hallock 628 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page64 of 120 62 contracts for school teachers and firefighters where the entire schedule moves at once. In fact, entire structures move from year to year in all kinds of organizations, including at defendants over the recent past. I will show some examples below. 207. If it is the case, in a particular organization or organizations, that those at the top of a pay scale help determine the relative gains of those “below” them, then restricting the pay of those at the top of a grid necessarily affects those below. X. Examples of How Market Pressure Led to Pay Changes at Defendants 208. There are clear examples of how pay changed at some defendants. I will discuss a few examples here, including how market pressure led to pay changes at defendants. 209. One example is from Adobe. Mr. Chizen, commenting on his time as CEO, noted, “Typically the HR people would come to me and say, we really need to move the ranges based on the Radford data. Here is the Radford data. So it will be me approving a recommendation. Again, the philosophy of the company, which I said, we’re going to pay within this percentile for these – at a high level … for, you know, engineering product, we’ll pay this, for the rest of the organization we’re paying within the Radford, so if Radford moved automatically, the – that would move”.228 He was then asked “And that was my question, whether in order for the compensation for any particular people who fell within that range to move, did you have – did you have to validate Radford’s conclusions that it moved … 5 percent of that was just something - ”.229 Mr. Chizen replied “That was typically – no, with one caveat, we also had to live within our budget. So if Radford moved 20 percent, and we can only afford to do a merit increase for the company of 5 percent, we had to make a conscious decision of which positions we were going to let go to the 20 percent versus which ones you were going to 228 229 Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 100. Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, pages 100-1. May 10, 2013 Expert Witness Report of Kevin F. Hallock 629 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page65 of 120 63 keep at 2 percent. That’s when I would get involved”. He was then asked “Did that ever happen from time to time, that the market data came back in a way that you couldn’t afford?” He replied, “Typically not. Adobe was such a cash rich company, expense was not my number one concern”.230 210. Another example is from Google. Google has provided several sets of salary grids (including the one already discussed in Figure 7) and I will discuss only a few here. For example, I start with the 2005 salary structure and compare two sets of categories in two regions.231 The data are displayed in Figure 17. The regions are referred to as and and the categories are for another. For these two sets of jobs and regions in 2005, I created the spreadsheet in Figure 17. I repeated this tabulation in the same figure using data from Google in 2004.232 211. .233 212. Multiple comparisons are easily made from these data. For example, using only 2005 data, if one compares in Figure 18 to in Figure 18, it is clear to see that nearly every single element of the different from the “ are precisely This is true both when comparing each T grade and each E grade within 2005 and within 2004. The only exception is the maximum column in 2005 for the T grades. So of 180 possible numbers, are This implies 230 Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 101. GOOG-HIGH-TECH-00625148 Contains a courtesy reproduction of a compensation spreadsheet titled 2005 Global Ranges - for MQU May-06.xls. 232 Exhibit 1600.l “Google 2004 Salary Ranges”. 233 GOOG-HIGH-TECH-00625148 Contains a courtesy reproduction of a compensation spreadsheet titled 2005 Global Ranges - for MQU May-06.xls and Exhibit 1600.l “Google 2004 Salary Ranges”. 231 May 10, 2013 Expert Witness Report of Kevin F. Hallock 630 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page66 of 120 64 a formal structure that is standardized for the company for these pay grades, with a few exceptions. 213. In fact, Google was explicit in changing its salary structure at one point in time and did so universally with the “big bang” in which it increased salaries by 10% across the board. 214. 234 Google documents . 215. 235 216. At Lucasfilm Ms. Micheline Chau testified that over time Lucasfilm changed its of the external market benchmark.236 payment targets from 217. Ms. Chau clarified, , again, like I said, depending on the industry circumstance, sometimes was in the – sometimes it was economic conditions didn’t need it, it 218. for critical talent, and when ”.237 Data from Lucasfilm also show a systematic structure with pay changes and differences across levels. I created a figure using data on the 2008 and 2006 salary structure at Lucasfilm in Figure 18.238 234 Deposition of Mr. Frank Wagner, Google, March 7, 2013, page 216. Email from Anuj Chandarana, Google, December 2, 2010, exhibit 1629. 236 Deposition of Ms. Michelene Chau, Lucasfilm, February 21, 2013, page 126. 237 Deposition of Ms. Michelene Chau, Lucasfilm, February 21, 2013, page 127. 238 LUCAS00188913 (Exhibit 711.29) for 2008 and LUCAS00188912 (exhibit 360) for 2006. 235 May 10, 2013 Expert Witness Report of Kevin F. Hallock 631 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page67 of 120 65 219. In 2008 there are 23 Salary Grades reported for Lucasfilm and in 2006 there are 21 Salary Grades reported for Lucasfilm.239 As shown in Figure 18, for each of these grades there is a minimum salary, a midpoint salary and a maximum salary reported in each of the two years. There is interesting formality and symmetry to the Lucasfilm structure. 220. Further at Lucasfilm, within each grade, 221. In addition, at Lucasfilm, within the three metrics (minimum, midpoint or maximum), 222. Finally, at Lucasfilm, the entire structure 223. In the deposition of Stephanie Sheehy at Pixar, there is discussion of changes in pay for an entire group. Ms. Sheehy was asked, “Why did Pixar decide it was necessary for the tools group to have their base salaries on average at a higher than level?” She answered “We were competing with technology companies in the Bay Area, and our recruiting team was hearing from candidates that they were getting better offers elsewhere”.240 She was then asked “What was the percentile level that was the aspiration for this group of employees?” 239 240 LUCAS00188913 (Exhibit 711.29) for 2008 and LUCAS00188912 (exhibit 360) for 2006. Deposition of Ms. Stephanie Sheehy, March 5, 2013, page 106. May 10, 2013 Expert Witness Report of Kevin F. Hallock 632 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page68 of 120 66 241 ”.242 In the absence of the recruiting team hearing from She replied, “ candidates that those candidates were getting better offers elsewhere, there would have been less pressure to target a higher percentile. XI. Agreements of the Kind Described in this Case Could Limit Recruiting and Have Negative Consequences on Compensation for Employees of Defendant Firms 224. In this section I will discuss more about how the so called no cold calling agreements could have negative consequences, not only for those directly affected by the no cold-calling but also for nearly all others at the Defendant firms, particularly in the technical and creative areas. 225. Cold calling is an important part of recruiting in some industries. In fact, in some types of jobs, a large majority of the jobs are filled through this method. 226. At the same time, many employees can see their salaries increase and stay at their current employers by using a competing offer (or even the threat of a competing offer). This is true is many industries. 227. Restricting cold-calling can have negative consequences for the compensation of those who are cold called, could be cold called and potentially for nearly all others in their organization. 228. A consideration in this case is that the defendants represented very well-known, celebrated companies. For many reasons these could be thought of as “employers of choice”. By having restrictive recruiting practices at these firms and for those employees of those firms who were highly coveted by other employees, there could be negative consequences for pay and pay growth. 241 242 Deposition of Ms. Stephanie Sheehy, March 5, 2013, page 106-7. Deposition of Ms. Stephanie Sheehy, March 5, 2013, page 107. May 10, 2013 Expert Witness Report of Kevin F. Hallock 633 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page69 of 120 67 229. Important in this argument is the issue of equity as outlined earlier. To the extent that there is an internal structure, any restriction at the top could have a consequent cascading effect on those below. This can be seen even back in several of the Figures that either have job evaluation points or even grades as the horizontal axis. The horizontal axes in each of those Figures represents job evaluation points or what have been called the things that people do at work or the contributions that people are having to the organization.243 Taking the example of Figure 7, if the pay is restricted for any of the kinds of people who may be at the “top” of the boxes, then the boxes may stop growing from period to period and all employees – even those not at the top of the box can be affected. But, as indicated elsewhere cascading effects on others do not rely on the pay of the highest paid being restricted. 230. There is evidence in economics and in other areas that fairness in wage setting and considerations of peers in compensation matters (e.g. Levine, 1993 and Card, Mas, Moretti, and Saez, 2012). 231. There is substantial evidence from each of the defendants that fairness and equity considerations mattered. 232. In addition, it is not only the case that those who are paid at the “top of the box” are the ones who are being cold called. In the absence of any cold-calling restrictions or agreements, any employee can be cold called. Even if cold calling affecting pay is restricted at the mid-point, for example, due to the nature of the structure and use of external data, there can be negative compensation consequences for even those who would not be cold-called. 233. I also note that no workers have to move from one company to another for no- cold-call agreements to have a negative effect on compensation. This is plain to see. If a recruiter working for company X calls and asks an employee of firm Y of her potential interest in 243 See Hallock (2012) page 62. May 10, 2013 Expert Witness Report of Kevin F. Hallock 634 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page70 of 120 68 moving, her compensation can’t go down and may go up if she can use any potential or realized offer to bid up her own pay internally. So even if not a single employee moves, cold-calling agreements could have negative consequences for pay and pay growth. 234. It should also be noted performance is not always as easily measured as some argue. In fact, performance is sometimes very hard to measure and social scientists have devised ways to consider compensation in interesting ways precisely because performance is difficult to measure in some situations.244 235. Intuit also provides an example on competition. In a PowerPoint presentation, Intuit noted: “The more passive the candidate, the fewer competitors for talent”.245 236. Also at Intuit, Mr. Chris Galy was asked, “Okay. How – What kind of conversation would you typically have with candidates about compensation in an initial coldcall?” He replied, “It comes up. Again, generally driven – the goal of – the first, primary goal is to generate interest and awareness and see if there’s a match. But then the next thing is you don’t want to waste people’s time and they don’t want to waste yours. And so it’s – these days, it’s generally, you know, hey, give me a ballpark. Are we doing apples to apples, or are we – are you in Yankee Stadium and we’re in the Oakland Coliseum?”246 He was then asked, “So is that usually you asking them how much they make or them asking you what the ballpark is for the position, or could it be either way?” He replied, “It could be either way. But generally speaking, I like to leave it up to them to tell me what their experiences are. So … yeah, I mean, it could be either way”.247 244 See for example, Lazear and Rosen (1981). Powerpoint, Candidate Generation, Intuit, December 12, 2006, INTUIT_034255, exhibit 2135.25. 246 Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 165. 247 Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 166. 245 May 10, 2013 Expert Witness Report of Kevin F. Hallock 635 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page71 of 120 69 XII. Given the Defendants’ Formalized Pay Structures and Compensation Design, Effects on Compensation Could be Widely Felt 237. Given the defendants’ formalized pay structures and compensation design as well as issues of equity and fairness present in the defendant firms, there can be widespread and systematic effects on compensation connected to the do-not-call agreements. 238. Elsewhere in this report, it is documented that the defendant firms had formalized compensation systems. It is also documented that the defendant firms were interested in internal equity and issues of fairness. It is also documented how pay changed at defendant companies. A direct impact on pay could occur if an employee did not receive a cold call, or if the upward wage pressures on any of the employees in related groups or job families were disrupted. 239. One way that pay can be lowered at defendant firms for nearly all workers has to do with the “top” workers. The defendants were very interested in attracting and retaining many extraordinary workers. The defendant firms include very well-known and prestigious brands for employees. Some of the cold-calling restrictions were clearly targeted to this very high-end type of worker. I have shown previously that it is straightforward to show that cold-calling can have a direct impact on individual workers. Since the “top of the box” is, therefore, lowered in the presence of cold-calling restrictions, the entire box may be as well, thus effecting nearly all other workers. But, again, the restrictions need not only affect the highest paid workers for calling restriction to have effects on others. 240. Another interesting way in which wages can be influenced is external market data. Here, there is evidence that defendants benchmark their data to external sources, most commonly Radford or Croner. But here, to the extent that pay is lowered at other firms through anti-competitive and other behavior of firms, the market data they use for their own structure will May 10, 2013 Expert Witness Report of Kevin F. Hallock 636 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page72 of 120 70 be lower. And, as a result, their own pay levels will be lower than they would be in the absence of such agreements. XIII. The Technical Class 241. My understanding of the case is that the plaintiffs originally proposed two types of potential employee classes. The first has been called the “All-Salaried Employee Class” and the second has been called the “Technical Class”. My understanding is that the “Technical Class” is defined in Appendix B of Edward Leamer’s expert report. My findings above apply to both potential classes. However, I turn now to a specific examination of the proposed technical class. 242. In reviewing that list of titles included in the proposed “technical class,” I observed that it includes “Software Engineers,” “Hardware Engineers and Component Designers,” and “Employees classified as technical professionals by their employers.” Note that the following are not included among the “technical class”: employees in “marketing, accounting, finance, operations, etc.,” “senior executives,” and “non-US” employees, among others.248 I have examined the definition of the “technical” class and see it as distinct from the “all-salaried class”. It also seems to me to be a reasonable definition of the technical class based on the Defendants’ job families for their technical workers.249 243. It is common to have multiple job titles within job families. Similar jobs, job titles and occupations are often grouped within the same job family. Milkovich, Newman and Gerhart (2014) discuss one example of a way to categorize job families, jobs and tasks. They show a figure where display the relationships among job families, jobs and tasks. They indicate 248 249 Expert Report of Edward E. Leamer, October 3, 2012, pages 74-7. Expert Report of Edward E. Leamer, October 3, 2012, pages 74-7. May 10, 2013 Expert Witness Report of Kevin F. Hallock 637 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page73 of 120 71 that a “job family” is a “[g]rouping of related jobs with broadly similar content; e.g., marketing, engineering, office support, technical”.250 244. The job families as presented in Appendix B of Edward Leamer’s expert report also appear to have appropriate types of job titles grouped together, in a way that would be reasonable from the perspective of compensation design. 245. I understand that all members of the “technical class” are also members of the “all-salaried class” but, of course, not all members of the “all salaried class” are members of the “technical class”. 246. Based on my review of the evidence and my expertise in compensation design, my belief is that although the restrictions could affect all or nearly all salaried workers, there was more concentration and emphasis on the technical class. XIV. Conclusions 247. Based on the documents I have considered and my knowledge of labor markets and compensation systems I have a number of conclusions. These views are expressed in the report and some are summarized here. 248. The defendants had formalized compensation systems. These include using market surveys, having clear structures, using market pay lines, grades and many other features of formalized compensation systems. 249. The defendants made use of the ideas of compensation beyond salary. These other forms of compensation include components such as bonuses and stock. 250 Milkovich, Newman and Gerhart (2014), page 104. May 10, 2013 Expert Witness Report of Kevin F. Hallock 638 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page74 of 120 72 250. Issues of internal equity and equity in general were important to the defendant firms. Whether they used the terms or not, the concepts of internal equity and also generally treating similar employees similarly were important to defendant firms. 251. There is documented evidence that pay moved in defendant firms in systematic and structured ways. 252. A compensation system that includes pay for performance is not mutually exclusive from one that takes internal equity into account. 253. Restrictions on cold-calling clearly had impacts on employees among the defendant firms. In particular, restrictions on cold-calling hamper compensation levels for employees. The restrictions could be expected to hamper levels of compensation for those who would have been cold-called and for all or nearly all salaried employees of defendant firms. 254. Agreements such as restrictions on cold-calling could be expected to limit and have negative consequences on employee compensation for those workers directly involved and for nearly all employees. Given the formalized pay structures and compensation design in defendant firms nearly all salaried employees could be expected to have pay that would otherwise be higher. 255. The formalized systems in place at the defendants relied on structures, external data from the market and the like, and notions of equity were present at defendants. As a result, those effects cycle on to other employees and their levels of compensation. Therefore, the formal compensation structures could be expected to lead to an effect on nearly all class members. 256. Although I have not been asked to estimate the magnitude of damages in this case, based on my knowledge of compensations systems and the materials considered, I believe May 10, 2013 Expert Witness Report of Kevin F. Hallock 639 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page75 of 120 73 that agreements against cold calling, such as the agreements at issue in this case, are predicted to suppress the compensation of all or nearly all members of plaintiffs’ proposed Technical Employee Class, including those with different job titles. 257. I reserve the right to supplement this report in view of any new material or information provided to me after the date of this report. Kevin F. Hallock May 10, 2013 May 10, 2013 Expert Witness Report of Kevin F. Hallock 640 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page76 of 120 74 APPENDIX A Kevin F. Hallock CV May 10, 2013 Expert Witness Report of Kevin F. Hallock 641 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page77 of 120 75 KEVIN F. HALLOCK April 2013 OFFICE HOME Cornell University 256 Ives Faculty Building Ithaca, NY 14853 607 255-3193 (phone) 607 255-4496 (fax) e-mail: hallock@cornell.edu web: www.ilr.cornell.edu/ics www.economics.cornell.edu 103 Harvard Place Ithaca, NY 14850 607 319-0545 Born: March 10 1969, Palo Alto, CA Married: Tina Hallock in 1991 Children: Emily 1994, Tyler 1998 CURRENT POSITIONS Donald C. Opatrny ’74 Chair of the Department of Economics, Cornell University (2012 – present) Joseph R. Rich ’80 Professor, Cornell University (2011 – present) Professor, Department of Economics, Cornell University (2011 – present) Professor, Department of Human Resource Studies, Cornell University (2007 – present) Director, Institute for Compensation Studies (ICS), Cornell University (2009 – present) Compensation Committee Member, Guthrie Health, Sayre PA (2012 – present) House Fellow, Carl Becker House, Cornell University (2011 – present) Research Associate, Labor Studies, National Bureau of Economic Research (2003 - present) Member, Board of Directors of Society of Certified Professionals, WorldatWork (2012 - present) Faculty Fellow, Atkinson Center for a Sustainable Future (ACSF), (2012 – present) Distinguished Principal Researcher, The Conference Board (2011 – present) Fellow, Stanford University Center for the Study of Poverty and Inequality (2006 – present) Faculty Affiliate, Center for the Study of Inequality, Cornell University (2007 – present) EDUCATION Princeton University – Ph.D. Economics, 1995. Princeton University – M.A. Economics, 1993. University of Massachusetts at Amherst – B.A. Economics, Summa Cum Laude, 1991. Hopkins Academy, Hadley Massachusetts, Valedictorian, 1987. May 10, 2013 Expert Witness Report of Kevin F. Hallock 642 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page78 of 120 76 OTHER AND PREVIOUS POSITIONS Chair, Department of Labor Economics, Cornell University (2010 – 2011) Associate Chair, Department of Economics, Cornell University (2011 – 2012) Professor, Department of Labor Economics, Cornell University (2007 – 2011) Chair, Cornell University Financial Policy Committee (2007 – 2008) Director of Research, Center for Advanced Human Resource Studies (CAHRS), Cornell University (2007 – 2012) Senior Fellow, Executive Compensation, Board Compensation and Board Practices, The Conference Board (2008 – 2011) Member, Board of Directors, WorldatWork (2009 – 2011) Member, WorldatWork Executive Compensation Advisory Board (2007 – 2009) Faculty Member, Graduate Field of Economics, Cornell University (2005 - present) Faculty Member, Graduate Field of Industrial & Labor Relations, Cornell University (2006 – present) Associate Professor of Human Resource Studies, ILR School, Cornell University (2005 - 2007) Acting Chair, Department of Human Resource Studies, ILR School, Cornell University (Fall 2006) Associate Professor of Economics and of Labor and Industrial Relations, University of Illinois at Urbana-Champaign (2001 – 2005) Associate Professor of Finance, University of Illinois at Urbana-Champaign (2002 – 2005) Co-Director, Center for Human Resource Management, University of Illinois (2004 – 2005) Visiting Associate Professor, Institute of Government and Public Affairs, University of Illinois at Urbana-Champaign (2005) Research Consultant, Research Department, Federal Reserve Bank of Chicago (2003 – 2005) Visiting Assistant Professor, Department of Economics and Research Associate, Industrial Relations Section, Princeton University (1998 - 1999) Assistant Professor of Economics and of Labor and Industrial Relations, University of Illinois at Urbana-Champaign (1995 - 2001) May 10, 2013 Expert Witness Report of Kevin F. Hallock 643 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page79 of 120 77 HONORS AND FELLOWSHIPS John T. Dunlop Outstanding Young Scholar Award, Industrial Relations Research Association (Now Labor and Employment Relations Association), 2004. Outstanding Teaching Award (small class), University of Illinois Economics Graduate Student Association, 2001-2002. Faculty Teaching Excellence Award, University of Illinois Institute of Labor and Industrial Relations, 2000. Outstanding Teaching Award (small class), University of Illinois Economics Graduate Student Association, 2000-2001. Albert Rees Prize for Best Dissertation in Labor Economics from Princeton in the Last Six Years (awarded every two years), 1999. University of Illinois College of Commerce and Business Administration Award for Excellence in Research (first annual Assistant Professor award), 1999. University of Illinois list of teachers ranked excellent by their students, 1997, 1998, 1999, 2000, 2002. Princeton University Industrial Relations Section Fellowship, September 1991-May 1995. United States Department of Education Jacob K. Javits Fellowship, September 1991-May 1995. Massachusetts William Field Alumni Scholar, 1991. Phi Beta Kappa, 1990. Valedictorian, Hopkins Academy, Hadley Massachusetts, 1987. Paul Brown Senior Baseball Award, Hopkins Academy, Hadley Massachusetts, 1987. Massachusetts High School State Baseball Champions, 1985. Third base, Hopkins Academy. BOOKS Pay: Why People Earn What They Earn and What You Can Do Now to Make More, Cambridge University Press September 2012. Managing Layoffs: Why Firms Fire Workers and How it Affects the Bottom Line, Cambridge University Press, under contract. The Economics of Executive Compensation, Volume II, (co-editor with Kevin J. Murphy), Edward Elgar Publishing Limited, Cheltenham, England, 1999. The Economics of Executive Compensation, Volume I, (co-editor with Kevin J. Murphy), Edward Elgar Publishing Limited, Cheltenham, England, 1999. May 10, 2013 Expert Witness Report of Kevin F. Hallock 644 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page80 of 120 78 BOOKS (continued) Economic Institutions and The Demand and Supply of Labor: The Collected Essays of Orley Ashenfelter, Volume III, editor, Edward Elgar Publishing Limited, Cheltenham, England, 1997. Education, Training and Discrimination: The Collected Essays of Orley Ashenfelter, Volume II, editor, Edward Elgar Publishing Limited, Cheltenham, England, 1997. Employment, Labor Union, and Wages: The Collected Essays of Orley Ashenfelter, Volume I, editor, Edward Elgar Publishing Limited, Cheltenham, England, 1997. Labor Economics, Volume IV: Labor Market Discrimination, Labor Mobility and Compensating Wage Differentials, (co-editor with Orley Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995. Labor Economics, Volume III: Unemployment, Trade Unions and Dispute Resolution, (co-editor with Orley Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995. Labor Economics, Volume II: Employment, Wages and Education, (co-editor with Orley Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995. Labor Economics, Volume I: Labor Supply and Labor Demand, (co-editor with Orley Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995. PUBLISHED AND FORTHCOMING PAPERS “Data Improvement and Labor Economics,” Journal of Labor Economics, 31(2), Part 2, April 2013, S1-S16. “Adverse Selection and Incentives in an Early Retirement Incentive Program,” (with Kenneth Whelan, Ronald Ehrenberg and Ronald Seeber), Research in Labor Economics, Volume 36, 159190, 2012. “Job Loss and Effects of Firms and Workers,” (with Michael Strain and Doug Webber), in Cary Cooper, Alankrita Pandey and James Quick eds. Downsizing: Is Less Still More?, Cambridge University Press, 2012. “New Data for Answering Old Questions Regarding Employee Stock Options,” (with Craig Olson), in Labor and The New Economy, Katharine G. Abraham, James R. Spletzer and Michael Harper, editors, National Bureau of Economic Research, 2010. “Executive Pay and Firm Performance: Methodological Considerations and Future Directions,” (with Beth Florin and Douglas Webber), Research in Personnel and Human Resources Management, 2010. “The Geography of Giving: The Effect of Corporate Headquarters on Local Charities,” (with David Card and Enrico Moretti), Journal of Public Economics, April 2010, 94(3), 222 -234. “CEO Pay for Performance Heterogeneity: Examples Using Quantile Regression,” (with Clayton Reck and Regina Madalozzo), Financial Review, February 2010, 1-19. May 10, 2013 Expert Witness Report of Kevin F. Hallock 645 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page81 of 120 79 PUBLISHED AND FORTHCOMING PAPERS (continued) “Job Loss and the Fraying of the Implicit Employment Contract,” Journal of Economic Perspectives, 23(4), Fall 2009, 69-93. “The Changing Relationship Between Job Loss Announcements and Stock Prices: 1970-1999,” (with Henry Farber), Labour Economics, 16(1), January 2009, 1-11. “Layoffs in Large U.S. Firms from the Perspective of Senior Management,” Research in Personnel and Human Resources Management, volume 25, 2006. “Assessing the Impact of Job Loss on Workers and Firms,” (with Kristin Butcher), Chicago Fed Letter, Federal Reserve Bank of Chicago, April 2006. “Mass Layoffs and Management Turnover,” (with Sherrilyn Billger), Industrial Relations, 44(3), July 2005. “Bringing Together Policymakers, Researchers, and Practitioners to Discuss Job Loss,” (with Kristin Butcher), Economic Perspectives, Federal Reserve Bank of Chicago, 2nd Quarter, 2005. “Does Managed Care Change the Management of Nonprofit Hospitals? Evidence from the Executive Labor Market,” (with Marianne Bertrand and Richard Arnould), Industrial and Labor Relations Review, 58(3), April 2005. “Job Loss: Causes, Consequences, and Policy Responses,” (with Kristin F. Butcher), Chicago Fed Letter, Federal Reserve Bank of Chicago, Number 207, October 2004. “Managerial Pay in Nonprofit and For-Profit Organizations,” in Improving Leadership in Nonprofit Organizations, Sarah Smith-Orr and Ron Riggio, editors, Jossey-Bass, 2004, 76 – 101. “Managerial Pay and Governance in American Nonprofits,” Industrial Relations, 41(3), July 2002, 377-406. “When Unions ‘Mattered’: Assessing the Impact of Strikes on Financial Markets: 1925-1937,” (with John DiNardo), Industrial and Labor Relations Review, 55(2), January 2002, 219 - 233. “Quantile Regression,” (with Roger Koenker), The Journal of Economic Perspectives, 15(4), Fall 2001, 143-156. “The Gender Gap in Top Corporate Jobs,” (with Marianne Bertrand), Industrial and Labor Relations Review, 55(1), October 2001, 3-21. “Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression using Twins Data,” (with Omar Arias and Walter Sosa), Empirical Economics, 26(1), March 2001, 7-40. Reprinted in Economic Applications of Quantile Regression, Bernd Fitzenberger, Roger Koenker, and Jose A. F. Machado, Editors, Physica-Verlag. “Compensation in Nonprofit Organizations,” Research in Personnel and Human Resources Management, edited by Gerald R. Ferris, Elsevier Science, Volume 19, 2000, 243-294. May 10, 2013 Expert Witness Report of Kevin F. Hallock 646 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page82 of 120 80 PUBLISHED AND FORTHCOMING PAPERS (continued) “The Timeliness of Performance Information in Determining Executive Compensation,” (with Paul Oyer), Journal of Corporate Finance, 5(4), December 1999, 303-321. “Capital Markets and Job Loss: Evidence from North America,” (with Henry Farber), Wirtschafts Politische Blatter, 46(6), December 1999, 573-577. “Dual Agency: Corporate Boards with Reciprocally Interlocking Relationships,” in Executive Compensation and Shareholder Value: Theory and Evidence, edited by Jennifer Carpenter and David Yermack, Kluwer, 1999, 55-75. “Changing Stock Market Response to Announcements of Job Loss: Evidence from 1970-1997,” (with Henry Farber), Proceedings of the Industrial Relations Research Association, May 1999, 26-34. “Introduction,” in The Economics of Executive Compensation, Volume I, (edited by Kevin F. Hallock and Kevin J. Murphy), Edward Elgar Publishing Limited, Cheltenham, England, 1999, pp. ix - xxviii. “Layoffs, Top Executive Pay, and Firm Performance,” The American Economic Review, 88(4), September 1998, 711-723. “Discrimination by Gender and Disability Status: Do Worker Perceptions Match Statistical Measures?” (with Wallace Hendricks and Emer Broadbent), Southern Economic Journal, 65(2), October 1998, 245-263. “Reciprocally Interlocking Boards of Directors and Executive Compensation,” Journal of Financial and Quantitative Analysis, 32(3), September 1997, 331-344. Reprinted in Governance, Directors, and Boards, Mahmoud Ezzamel, editor, Edward Elgar Publishing Limited, UK. “Introduction,” in Employment, Labor Unions and Wages: The Collected Essays of Orley Ashenfelter, Volume I, Edward Elgar Publishing Limited, Cheltenham, England, ix – xxii. “Seniority and Monopsony in the Academic Labor Market: Comment,” The American Economic Review, 85(3), June 1995, 654-657. WORKING PAPERS “Employees’ Choice of Method of Pay,” (with Craig Olson), February 2012. “Executive Compensation in American Unions,” (with Felice Klein), January 2012. “Senior HR Leaders in the “Top 5”: Evidence on Pay, Relative Pay, and Performance Using Data from 1,500 Firms Over a Decade,” (with Matthew Allen and John Haggerty), January 2008. “The Value of Stock Options to Non-Executive Employees,” (with Craig Olson), March 2007. “Are Formal Corporate News Announcements Still Newsworthy?: Evidence from 30 Years of US Data on Earnings, Splits, and Dividends” (with Farzad Mashayekhi), July 2006. May 10, 2013 Expert Witness Report of Kevin F. Hallock 647 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page83 of 120 81 WORKING PAPERS (continued) “The Gender Pay Gap for Managers in Nonprofits,” January 2002. “Unions and the Labor Market for Managers,” (with John DiNardo, and Jorn-Steffen Pischke), August 2000. “A Simple Empirical Model of Welfare or Work Incentives for Single Mothers,” June 1995. BOOK REVIEWS Review of Personnel Economics in Imperfect Labour Markets, by Pietro Garibaldi, Oxford University Press, Journal of Economic Literature, December 2007. Review of Pay Without Performance: The Unfulfilled Promise of Executive Compensation, by Lucian Bebchuk and Jesse Fried, Harvard University Press, Industrial and Labor Relations Review, 59(4), July 2006, 672-674. OTHER WORK IN PROGRESS “The Pay Gap and the Total Compensation Gap by Disability Status,” (with Xin Jin and Linda Barrington) “Pay and Performance for University Presidents,” (with Orley Ashenfelter, Sherrilyn Billger and Ronald Ehrenberg) “The Illinois Historical Salary Census,” (with David Card) “Estimating the Expected Cost of Employee Stock Options” (with Craig Olson) “Job Matching and Employment Duration” (with Todd Elder) “The Night Shift” (with Darren Lubotsky and Douglas Webber) “Quantile Regression for Management” “Sleepy Traders and Stock Prices” (with Lawrence DeBrock and Joe Price) RESEARCH REPORTS The 2011 U.S. Top Executive Compensation Report, (with Judit Torok), The Conference Board, 2011. U.S. Salary Increase Budgets for 2012, (with Judit Torok), The Conference Board, 2011. The 2010 U.S. Top Executive Compensation Report, (with Judit Torok),The Conference Board, 2010. Top Executive Compensation in 2009, (with Judit Torok), The Conference Board, 2010. May 10, 2013 Expert Witness Report of Kevin F. Hallock 648 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page84 of 120 82 RESEARCH REPORTS (continued) Directors’ Compensation and Board Practices in 2009, (with Matteo Tonello and Judit Torok), The Conference Board, 2010. Top Executive Compensation 2009 – Key Findings, (with Judit Torok), The Conference Board, December 2009. Top Executive Compensation in 2008, (with Judit Torok), The Conference Board, 2008. Directors’ Compensation and Board Practices in 2008, (with Matteo Tonello and Judit Torok), The Conference Board, 2008. Top Executive Compensation 2008 – Key Findings, (with Judit Torok), The Conference Board, December 2008. Directors’ Compensation and Board Practices Report 2007, (with Linda Barrington and Judit Torok), The Conference Board, 2007. Top Executive Compensation 2007, (with Linda Barrington and Lisa Hunter), The Conference Board, 2007. 2007 Report on Top Executive Compensation—Key Findings, (with Linda Barrington and Lisa Hunter), The Conference Board, 2007. Layoffs, Top Executive Pay and Firm Performance, United States Department of Labor, 1996 COLUMNS “Pay in Nonprofits,” Workspan, April 2013, 12-13. “Valuing Employee Stock Options,” Workspan, March 2013, 10-11. “Pay and Relative Income Within Couples,” Workspan, February 2013, 12-13. “Presidential Pay,” Workspan, January 2013, 12-13. “Top Athlete Pay,” Workspan, December 2012, 12-13. “Economic Effects of the Minimum Wage,” Workspan, November 2012, 12-13. “How The Olympics Remind Us About Compensation,” Workspan, October 2012, 12-13. “CEOs Off the Clock,” Workspan, September 2012, 13-14. “Vacation as Compensation,” Workspan, August 2012, 13-14. “Paying Professors” Workspan, July 2012, 12-13. “Does Graduating in a Bad Economy Penalize Your Pay for Life?” Workspan, June 2012, 13-14. May 10, 2013 Expert Witness Report of Kevin F. Hallock 649 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page85 of 120 83 COLUMNS (continued) “Governance and Executive Pay in Nonprofits?” Workspan, May 2012, 13-14. “Why Do We Tip?” Workspan, April 2012, 12-13. “Massive Kinked Bonuses,” Workspan, March 2012, 12-13. “Go Big: The Firm-Size Pay (and Pay-Mix) Effect,” Workspan, February 2012, 12-13. “Nothing Lasts Forever: A Different Way to Structure Severance,” Workspan, January 2012, 12-13. “Is There Deadweight Loss in Holiday Rewards?” Workspan, December 2011, 11-12. “Pay System Gender Neutrality,” Workspan, November 2011, 11-12. “Does More Education Cause Higher Earnings,” Workspan, October 2011, 12-13. “Say On Pay and Compensation Design,” Workspan, September 2011, 10-11. “Lessons in Pay Design from the Farm,” Workspan, August 2011, 11-12. “Linking Compensation and Job Losses During a Recession,” Workspan, July 2011, 12-13. “Does That Pay Practice Really Have Any Impact?” Workspan, June 2011, 12-13. “Pay Ratios and Inequality,” Workspan, May 2011, 14-16. “Pay Secrecy and Relative Pay,” Workspan, April 2011, 10-11. “Motivating with Efficiency Wages and Delayed Payments,” Workspan, March 2011, 10-11. “The Relationship Between Company Size and CEO Pay,” Workspan, February 2011, 10-11. “The Disconnect Between Employer Cost and Employee Value,” Workspan, January 2011, 10-11. May 10, 2013 Expert Witness Report of Kevin F. Hallock 650 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page86 of 120 84 REFEREE AND EDITORIAL SERVICE (Advisory Board, Compensation and Benefits Review, 2012 – present) (Advisory Board, Journal of People and Organizational Effectiveness, 2012 – present) (Associate Editor, Journal of Labor Economics, 2008 – 2012) (Associate Editor, Labour Economics, 2008 – present) (Associate Editor, Economics Bulletin, 2005 – July 2010) (Editorial Board, Industrial and Labor Relations Review, 2006 – present) Academy of Management Journal, Advances in the Economics of Sport, American Economic Journal: Applied Economics, American Economic Review, British Journal of Industrial Relations, Economic Theory, Eastern Economic Review, Economic Inquiry, Economic Journal, Economics Bulletin, Economics of Education Review, Economics and Politics, Economics Letters, Education and Finance Policy, Empirical Economics, Explorations in Economic History, Financial Review, Industrial and Labor Relations Review, Industrial Relations, International Economic Review, International Journal of Manpower, International Journal of Organizational Analysis, International Migration Review, International Review of Economics and Finance, Journal of Business, Journal of Business and Economic Statistics, Journal of Corporate Finance, Journal of Human Resources, Journal of Economic Psychology, Journal of Finance, Journal of Industrial Economics, Journal of Labor Economics, Journal of Law Economics and Organization, Journal of Political Economy, Journal of Public Economics, Journal of Urban Economics, Labour Economics, The Manchester Review, Nonprofit and Voluntary Sector Quarterly, Nonprofit Management and Leadership, Quarterly Journal of Business and Economics, Quarterly Journal of Economics, Quarterly Journal of Economics and Finance, Review of Economics and Statistics National Science Foundation, Social Science and Humanities Research Council, United States Census Bureau, Various Publishers May 10, 2013 Expert Witness Report of Kevin F. Hallock 651 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page87 of 120 85 GRANTS United States Department of Education, National Institute on Disability and Rehabilitation Research (NIDRR), Rehabilitation Research Training Center (RRTC) on Employer Practices Related to Employment Outcomes for Individuals with Disabilities (co-PI, with Susanne Bruyere and Linda Barrington), $4 million, 2010 – 2015. Compensation in Asia, (CAHRS), 2011 – 2012. International Compensation, (CAHRS), 2010- 2011. Costs of Compensation versus Value to the Organization (CAHRS), 2009 – 2010. Why Managers Fire Workers and How it Affects the Bottom Line (CAHRS), 2008-2009. Managing Layoffs, Cornell Center for Human Resource Management (CAHRS), 2007-2008. Stock Options, (with Craig Olson), Cornell Center for Human Resource Management (CAHRS), 2006-2007. When and Why Do Firms Make Layoffs?, Alfred P. Sloan Foundation, 2001 - 2003. The Illinois Historical Salary Study, (with David Card), University of Illinois Campus Research Board, 2003. What Happens to Firms When Workers are Let Go?, Illinois Center for Human Resource Management, 2001-2002. Stock Options for Employees in Large U.S. Firms, Illinois Center for Human Resource Management, (with Craig Olson), 2001-2002. Studies in Executive Compensation, University of Illinois Campus Research Board, 2001-2002. What Drives Nonprofits? Evidence from Managerial Pay, Performance, and Market Competition in Nonprofit Hospitals, National Bureau of Economic Research, (with Richard Arnould, and Marianne Bertrand), 1999-2000. Computation Problems in Applied Economics, Intel Corporation, (with Lawrence DeBrock and Roger Koenker), 1998. Determinants of Managerial Compensation in American Charities, American Compensation Association, 1997-1998. Unions and Managerial Pay, American Compensation Association, (with John DiNardo and JornSteffen Pischke), 1997-1998. How to Make Incentive Pay Programs More Successful: Linking Sales Compensation Plans to Firm Performance, Center for Human Resource Management, University of Illinois, (with Paul Oyer), 1997-1998. Executive Compensation, Firm Layoffs, and Firm Performance, United States Department of Labor, 1996. May 10, 2013 Expert Witness Report of Kevin F. Hallock 652 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page88 of 120 86 SEMINARS AND PRESENTATIONS University of Arizona, Brigham Young University, University of California at Berkeley, University of California at Santa Barbara, Case Western Reserve University, University of Chicago, ClaremontMcKenna College, Cornell University, Harvard University, University of Illinois at Chicago, University of Illinois at Urbana-Champaign, Illinois State University, Kansas State University, University of Konstanz, Marquette University, Massachusetts Institute of Technology, McGill University, University of Michigan, Michigan State University, University of Missouri, New York University, Northwestern University, The Ohio State University, Princeton University, University of Pennsylvania, Indiana University – Purdue University at Indianapolis, Queen’s University, University of Rochester, Stanford University, Texas A&M University, University of Wisconsin at Madison, University of Wisconsin at Milwaukee, Yale University American Economic Association, Econometric Society, European Society of Labour Economists, Industrial Relations Research Association, Labor and Employment Relations Association, National Bureau of Economic Research, Society of Labor Economists, WorldatWork TEACHING Ph.D.Students advised, department, year of degree, and initial placement (* chair of committee): Pablo Acosta*, Economics, 2006, World Bank Ji-Young Ahn, ILIR, Illinois, 2009, Ehwa Women’s College, South Korea Carole Amidon, Economics, 2002, ERS Group, Florida Vic Anand, Accounting, 2013 (expected), Emory University Michelle Arthur, ILIR, 2000, Purdue University David Balan*, Economics, 2000, Federal Trade Commission Sherrilyn Billger*, Economics, 2000, Union College Paul Byrne, Economics, 2003, Wabash College John Deke*, Economics, 2000, Mathematica Policy Research, Princeton NJ Emre Ekinci, Economics, 2012, Universidad Carlos III Todd Fister*, ILIR, 2003, Kimberly-Clark, Atlanta R. Kaj Gittings, Economics, 2009 expected, Louisiana State University Lynn Gottschalk, Economics, 2005 Federal Trade Commission Weishi (Grace) Gu, Economics (current) Juliana Guimaraes*, Economics, 2001, Universidade Nova de Lisboa, Portugal John Haggerty, HR Studies, 2010, Cornell University Dan Hanner, Economics, 2005, Federal Trade Commission Jeffrey Hemmeter, Economics, 2004, University of California, Davis Xin Jin, Economics (current) Kandice Kapinos, ILIR, 2007, St. Olaf College David Kaplan, ILIR, 2000, James Madison University GiSeung Kim, Economics, 2001, LG Economics Research Group, Korea. Elizabeth Kiss, Ag. Economics, 2000, Purdue University Felice Klein*, HR Studies, 2012, Michigan State University Nolan Kopkin, Economics (2013), University of Wisconsin, Milwaukee. Gregory Kordas, Economics, 2000, University of Pennsylvania May 10, 2013 Expert Witness Report of Kevin F. Hallock 653 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page89 of 120 87 TEACHING (continued) Fidan Kurtulus*, Economics, 2007, University of Massachusetts at Amherst Regina Madalozzo*, Economics, 2002, Brazilian Institute of Capital Markets Farzad Mashayekhi*, Economics, 2003, Moody’s K M V, San Francisco Catherine McClean, Economics, 2012, University of Pennsylvania Daniel Morillo, Economics, 2000, PanAgora Asset Management, Boston Ben Ost, Economics, 2011, University of Illinois at Chicago Heather Radach, Economics, 2001, Lexecon, Chicago Clayton Reck*, Economics, 2004, ERS Group, Florida. Eduardo Ribeiro, Economics, 1995, Universidade Federal do Rio Grande do Sul, Brazil Laura Ripani*, Economics, 2004, World Bank. Patricia Simpson, ILIR, 1997, Loyola University, Chicago Michael Strain*, Economics, 2012, American Enterprise Institute Mary Taber, ILIR, 1999, Skidmore College Maria Tannuri, Economics, 2000, Universidade de Brasilia, Brazil Rosemary Walker, Economics, 2000, Wabash College Ying Wang, Economics (current) Douglas Webber, Economics, 2012, Temple University Leigh Wedenoja, Economics (current) Olga Yakusheva*, Economics, 2005, Marquette University Chen Zhao, Economics, 2013, Analysis Group Courses Taught: PAY (undergraduate) at Cornell Managing Compensation (MILR) at Cornell Executive Compensation (MILR) at Cornell Job Loss (Undergraduate) at Cornell Freshman Colloquium (Undergraduate) at Cornell Finance for Human Resources (M.H.R.I.R.) at Illinois and (MILR) at Cornell Labor Economics for Managers (M.H.R.I.R.) at Illinois Managerial Economics (Masters of Science in International Finance) at Illinois Labor Economics I (Ph.D.) and Labor Economics II (Ph.D.) at Illinois Applied Econometrics (Masters of Science in Policy Economics) at Illinois Microeconomic Principles (Undergraduate) at Illinois Labor Problems (Undergraduate) at Illinois Labor Economics (Undergraduate) at Illinois and Princeton May 10, 2013 Expert Witness Report of Kevin F. Hallock 654 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page90 of 120 88 UNIVERSITY SERVICE 2012 – 2013 (Cornell) Donald C. Opatrny ’74 Chair of the Department of Economics Director, Institute for Compensation Studies (ICS) Member, Search Committee for the Dean of the College of Arts and Sciences Member, Department of Economics Recruiting Committee Member, Cornell University Council on Mental Health and Welfare 2011 – 2012 (Cornell) Director, Institute for Compensation Studies (ICS) Chair, Recruiting Committee, Department of Economics Associate Chair, Department of Economics Director of Research and Board Member, Center for Advanced HR Studies (CAHRS) Member, Cornell University Council on Mental Health and Welfare 2010 – 2011 (Cornell): Chair, Department of Labor Economics Director, Institute for Compensation Studies (ICS) Chair, Recruiting Committee, Department of Labor Economics Recruiting Committee, Department of Policy Analysis and Management Recruiting Committee, Department of Human Resource Studies Director of Research and Board Member, Center for Advanced HR Studies (CAHRS) Member, Cornell University Council on Mental Health and Welfare Member, ILR Admissions Committee 2009 – 2010 (Cornell): Provost’s Budget Model Task Force Campus Task Group on Student Services Chair, ILR Task Group on Student Services Institute for the Advancement of Economics at Cornell Director, Compensation Research Initiative (CRI) Labor Economics Recruiting Committee Director of Research, Center for Advanced Human Resource Studies (CAHRS) Center for Advanced Human Resource Studies (CAHRS) Board 2008 – 2009 (Cornell): Cornell University Financial Policy Committee Institute for the Advancement of Economics at Cornell Director of Research, Center for Advanced Human Resources Studies (CAHRS) Undergraduate Committee, ILR School Center for Advanced Human Resources Studies (CAHRS) Board 2007-2008 (Cornell): Chair, Cornell University Financial Policies Committee Economics Field Review Committee Director of Research, Center for Advanced Human Resource Studies (CAHRS) Review Panel for Cornell Institute for the Social Sciences Center for Advanced Human Resource Studies (CAHRS) Board Undergraduate Committee, ILR School May 10, 2013 Expert Witness Report of Kevin F. Hallock 655 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page91 of 120 89 UNIVERSITY SERVICE (continued) 2006 – 2007 (Cornell): Interim-Chair, Human Resource Studies Department, ILR School Cornell (Fall) Cornell University Financial Policies Committee (2006 – 2009), Co-Chair (2006 - 2007) Labor Economics Search Committee Review Panel for Cornell Institute for the Social Sciences Center for Advanced Human Resource Studies (CAHRS) Board Undergraduate Committee, ILR School 2005 – 2006 (Cornell): Campus Financial Policies Committee (Spring) Committee on Faculty Recruitment and Retention in the Social Sciences ILR Committee to Evaluate the Math Requirement Departmental Tenure Review Committee Center for Advanced Human Resource Studies (CAHRS) Board 2004 – 2005 (Illinois): ILIR On-Campus Committee, Chair ILIR Executive Committee University of Illinois Center for Human Resource Management, Co-Director 2003 – 2004 (Illinois): Economics Junior Recruiting Committee, Chair Economics Advisory Committee to the Head ILIR On-Campus Committee, Chair University of Illinois Executive Board of Center for Human Resource Management 2002 – 2003: (Illinois) On sabbatical (fall) ILIR Executive Committee Economics Search Committee for new Head of Department University of Illinois Executive Board of Center for Human Resource Management Campus Admissions Committee College of Business Educational Policy Committee 2001 – 2002 (Illinois): ILIR Executive Committee ILIR Ph.D. Advisory Committee Economics/LIR Faculty Search Committee Economics Capricious Grading Committee Economics Labor Seminar College of Commerce Educational Policy Committee College of Commerce Teaching Advancement Board Campus Admissions Committee University of Illinois Executive Board of Center for Human Resource Management 2000 – 2001 (Illinois): ILIR Executive Committee ILIR On-Campus Committee Economics/ILIR Faculty Search Committee Economics Advisory Committee to the Head May 10, 2013 Expert Witness Report of Kevin F. Hallock 656 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page92 of 120 90 UNIVERSITY SERVICE (continued) 1999 – 2000 (Illinois): ILIR Ph.D. Advisory Committee ILIR Speaker-Scholars Committee Economics Advisory Committee to the Head Economics Graduate Admissions Committee Economics Labor Seminar 1998 – 1999: (On Leave all year at Princeton) Economics/ILIR Faculty Search Committee 1997 – 1998 (Illinois): ILIR Speaker-Scholars Committee ILIR Long Distance Learning Committee ILIR Admissions and Financial Aid Committee Economics Faculty Search Committee Economics Labor Seminar 1996 – 1997 (Illinois): ILIR Ph.D. Advisory Committee ILIR Speaker-Scholars Committee ILIR On-Campus Committee ILIR Computer Classroom Committee Economics Advisory Committee to the Head Economics Graduate Programs Committee Economics Labor Seminar 1995 – 1996 (Illinois): ILIR On Campus Committee, Speaker-Scholars Committee, Computer Classroom Committee PROFESSIONAL SOCIETY SERVICE Member, Board of Directors of the Society of Certified Professionals, WorldatWork, 2012 Member, Board of Directors, WorldatWork, 2009 - 2011 Board Member, WorldatWork Executive Compensation Advisory Board, 2007 - 2009 Member, Strategic Planning Committee, National Academy of Social Insurance, 2007-2008 Member, Awards Committee, Labor and Employment Relations Association, 2006 – 2010 May 10, 2013 Expert Witness Report of Kevin F. Hallock 657 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page93 of 120 91 CONFERENCE ORGANIZATION Emerging Scholars In Compensation Conference, Spring 2013, Ithaca NY (with Linda Barrington) 21st Century Human Resource Management Practices and Their Effects on Firms and Workers: ILIR Alumni Professorship Symposium, Institute of Labor & Industrial Relations, University of Illinois, November 11-12, 2005 (with Craig Olson and Kathryn Shaw) Job Loss: Causes, Consequences, and Policy Responses, Federal Reserve Bank of Chicago, November 18-19, 2004 (with Kristin Butcher and Daniel Sullivan) May 10, 2013 Expert Witness Report of Kevin F. Hallock 658 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page94 of 120 92 APPENDIX B Materials Considered Include The Following: Papers or Books Adams, J. Stacy, 1965, “Inequity in Social Exchange,” in L. Berkowitz, ed., Advances in Experimental Social Psychology, 2, 267 – 299. Card, David, 1999, “The Causal Effect of Education on Earnings,” in Orley Ashenfelter and David Card, Eds., Handbook of Labor Economics. Volume #a, Elsevier, 1801 – 1863. Card, David, 2001, “Estimating the Return to Schooling: Progress and Some Persistent Econometrics Problems,” Econometrica, 69, 1127 – 1160. Card, David, Alexandre Mas, Enrico Moretti, and Emmanuel Saez, 2012, “Inequality at Work: The Effect of Peer Salaries on Job Satisfaction,” The American Economic Review, 102(6), 29813003. Cardinal, Ken and Beth Florin, 2012, Handbook for Conducting Compensation and Benefits Surveys, WorldatWork Press. Hallock, Kevin F., 2012, Pay: Why People Earn What They Earn and What You Can Do Now to Make More, Cambridge University Press. Hallock, Kevin F. and Judit P. Torok, 2010, The 2010 U.S. Top Executive Pay Report, The Conference Board, New York, N.Y. Hungerford, Thomas and Gary Solon, 1987, “Sheepskin Effects in the Return to Education,” Review of Economics and Statistics, 69(1), February, 175 – 177. Levine, David I., 1993, “Fairness, Markets, and Ability to Pay: Evidence from Compensation Executives,” The American Economic Review, 83(5), December, 1241-1259. Lazear, Edward P. and Rosen, Sherwin. 1986, "Rank-Order Tournaments as Optimum Labor Contracts”. Journal of Political Economy, 89(5), October 1981, 841-864. Milkovich, George T. and Philip H. Anderson, 1972, “Management Compensation and Secrecy Policies,” Personnel Psychology, 25, 293-302. Milkovich, George T., Gerry M. Newman and Barry Gerhart, 2011, Compensation, 10th Ediction, McGraw-Hill Irwin. Milkovich, George T., Gerry M. Newman and Barry Gerhart, 2014, Compensation, 11th Ediction, McGraw-Hill Irwin. May 10, 2013 Expert Witness Report of Kevin F. Hallock 659 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page95 of 120 93 Rosen, Sherwin S., 1986, “The Theory of Equalizing Differences,” in Orley Ashenfelter and Richard Layard, Eds., The Handbook of Labor Economics, North Holland, 641 – 592. Spence, Michael, 1973, “Job Market Signaling,” Quarterly Journal of Economics, 87(3), August, 355-374. Weiss, Andrew, 1995, “Human Capital vs. Signaling Explanations for Wages,” Journal of Economic Perspectives, 9(4), 133 – 154. Data Sources and Other I was provided access to all deposition transcripts and exhibits in the case. The following are among the materials I considered: 2009 Croner Animation and Visual Effects Survey, January 8, 2009, PIX00001263, exhibit 119. Document, HR Global Staffing, Manage Offer Module, Develop External Offer, document Version 1.3, February 13, 2009, 76579DOC005963, exhibit 398.8. Document from Intuit, Talent Acquisition Hiring Plan, INTUIT_007866, exhibit 1107.2. Document, 2009 Salary Increase & LTI ‘Talking Points’, PIX00083585, exhibit, 1307.3 Declaration of Ms. Donna Morris of Adobe Systems, September 13, 2011. Declaration of Ms. Michelle Maupin, January 17, 2013. Declaration of Mr. Danny McKell, Intel, September 13, 2011. Declaration of Ms. Donna Morris, September 13, 2011. Deposition of Mr. David Alvarez, Apple, March 5, 2013 Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013. Deposition of Mr. Darrin Baja, Apple, March 1, 2013. Deposition of Mr. Richard Bechtel, Apple, March 7, 2013. Deposition of Dr. Shona Brown, January 30, 2013. Deposition of Mr. Patrick Burke, Apple, February 26, 2013. Deposition of Mr. Steven Burmeister, Apple, March 15, 2013. Deposition of Dr. Ed Catmull, January 24, 2013. May 10, 2013 Expert Witness Report of Kevin F. Hallock 660 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page96 of 120 94 Deposition of Ms. Michelene Chau, Lucasfilm, February 21, 2013. Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013. Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012. Deposition of Ms. Deborah Conrad, Intel, November 21, 2012. Deposition of Mr. Alan Eustace, February 27, 2013. Deposition of Mr. Chris Galy, Intuit, March 20, 2013. Deposition of Mr. Randall Goodwin, Intel, March 15, 2013. Deposition of Mr. Digby Horner, Adobe, March 1, 2013. Deposition of Ms. Renee James, Intel, March 22, 2013. Deposition of Ms. Danielle Lambert, Apple, October 2, 2013. Deposition of Mr. Alex Lintner, Intuit, March 25, 2013. Deposition of Michelle Maupin, February 12, 2013. Deposition of Ms. Lori McAdams, August 2, 2012. Deposition of Mr. Daniel McKell, Intel, March 20, 2013. Deposition of Ms. Jan van der Voort, February 5, 2013. Deposition of Ms. Donna Morris, August 21, 2012. Deposition of Ms. Patricia Murray, Intel, February 14, 2013. Deposition of Mr. Shantanu Narayen, Adobe, February 28, 2013. Deposition of Mr. Ron Okamoto, Apple, February 27, 2013. Deposition of Mr. Paul Otellini, Intel, January 29, 2013. Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013. Deposition of Mr. Brad Smith, Intuit, February 27, 2013. Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013. May 10, 2013 Expert Witness Report of Kevin F. Hallock 661 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page97 of 120 95 Deposition of Mr. Jeffrey Vijungco, Adobe, October 5, 2012. Deposition of Mr. Frank Wagner, March 7, 2013. Deposition of Ms. Sherry Whiteley, Intuit, March 14, 2013. Email from Ms. Jan van der Voort, July 9, 2007, LUCAS00060705, exhibit 728.1 Email from Ms. Michelle Maupin to Jan van der Voort, May 8, 2008, LUCAS00201069, exhibit 727.3. Email from Ms. Michelle Maupin, November 4, 2010, LUCAS00198130, exhibit 729.1. Email from Ms. Donna Morris, Adobe, March 4, 2007, ADOBE_005661, exhibit 1158. Email from Ms. Donna Morris, Adobe, June 5, 2010, ADOBE_019278, exhibit 1159. Email of Ms. Donna Morris, Adobe, June 13, 2011, ADOBE_9652, exhibit 1160. Email of Ms. Donna Morris, Adobe, January 18, 2008, ADOBE_009425, exhibit, 2501.1. Email of Mr. Shantanu Narayen, Adobe, June 14, 2011, ADOBE_9652, exhibit 1160. Email from Ms. Vanessa Hall, February 14, 2011, LUCAS00199905-6. Email from Arnnon Geshuri on Saturday March 15, 2008GOOGLE-High_Tech-00379327, exhibit 614. Email from Ms. Lori McAdams on November 17, 2006, LUCAS00184664, Exhibit 122. Email from Anuj Chandarana, Google, December 2, 2010, exhibit 1629. Email from Tiffany Wu, September 7, 2007, Goog-High-Tech-00473658, exhibit 1613. Email from Mr. Chris Galy, Intuit, March 3, 2010, INTUIT_039790, exhibit 2142.1. Email from Danny McKell, Intel, February 2005, 76657DOC004599, exhibit 2033. Email from Mr. Ron Okamoto, Apple, September 17, 2010, 231APPLE099371, exhibit 1130.1. Email from Mr. Paul Otellini, Intel, January 22, 2010, 76616DOC012164, exhibit 478.1. Email from Ms. Jocelyn Vosburch, Adobe, October 25, 2010, ADOBE_011976-7, exhibit 1250.1-2. May 10, 2013 Expert Witness Report of Kevin F. Hallock 662 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page98 of 120 96 Email from Mr. Odgen Reid, Intel, April 5, 2005, 76657DOC019264, exhibit, 2035.4. Email from Mr. Rob York, Apple, on December 17, 2010, 231APPLE039427, exhibit 1376.2. Google High Tech 00336879 from Deposition of Dr. Shona Brown, January 30, 2013, referencing exhibit 621. Great Places to Work website: http://www.greatplacetowork.com/. Powerpoint, “Recruiting and Human Resources Update,” Board of Directors Meeting, October 19, 2007, LUCAS00013707, exhibit 690.3. Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388, exhibit 392.3. Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388, exhibit 392.5. Powerpoint on pay design, LUCAS 00188717, exhibit 715.10. Powerpoint on pay design, LUCAS 00188763, exhibit 715.56. Powerpoint, Comp Basics for Recruiters, GOOG-HIH-TECH-00036292, exhibit 1606.6. Powerpoint, Compensation Components Setting a Base Salary, GOOG-HIGH-TECH-00036302, exhibit, 16016.16. Powerpoint, Intel Base Pay Comparison Report, Support Overview, WW04 2011, 765825DOC001211, exhibit 400.31. Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11. Powerpoint called FY11 Preliminary Pay lines development update, Intel, May 5, 2010, 76582DOC000004_000004, exhibit 399.4. Powerpoint, Candidate Generation, Intuit, December 12, 2006, INTUIT_034255, exhibit 2135.25. Powerpoint, FY ’09 New Hire Equity Guidelines, Intuit, INTUIT_039756, exhibit 2140.4. Powerpoint, Key Components of Intuit’s Total Rewards Portfolio, Intuit, January 7, 2005, INTUIT_52803, exhibit 1760.5. Powerpoint, Leveraging Compensation and Performance, Intuit, January 7, 2005, exhibit 1761.19. May 10, 2013 Expert Witness Report of Kevin F. Hallock 663 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page99 of 120 97 Powerpoint, INTUIT Total Rewards & Pay Decisions Toolkit, Intuit, May 2005, INTUIT_043560, exhibit 2739.13. Powerpoint, Focal Decisions 2005, Communications Session for Senior Managers, June 2005, Intuit, INTUIT_052841, exhibit 2740.16. Powerpoint, Lucasfilm Ltd. Compensation Project Status Executive Review, Lucasfilm, December 7, 2006, LUCAS00027982, exhibit 359.4. Powerpoint, Global Compensation Project, Lucasfilm Ltd., September 22, 2005, exhibit 944.9. Powerpoint, PAY FOR PERFORMANCE: 2009 Salary Budget Recommendation, Executive Review, January 21, 2009, Lucasfilm, LUCAS00189288, exhibit 945.13. Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.13. Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.16. Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.28. Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.19. Powerpoint, GAM SBS UPDATE, 2/11/09, INTEL, 76579DOC00124_000026, exhibit 396.26. Powerpoint, TMG Non-Tech Job Audit – HR, Intel, August 25th, 2005, 76583DOC008097_000003, exhibit 397.3. PowerPoint, Base Pay Comparison Report Support Overview WW 042011, Intel, 765825DOC001211, exhibit 400.17. Powerpoint, Internal Climate, Intel, 76596DOC017025, exhibit 781.16. Powerpoint, Base Pay Comparison Report Support Overview WW 04 2011, Intel, 765825DOC001211, exhibit 400.25. Powerpoint, Adobe, Q1 Workforce Metrics, As of 4 March 2005, Adobe, ADOBE_000622, exhibit 210.12. Powerpoint, Retention/Transition Guidelines, Adobe, June 2008, ADOBE_050724, exhibit 216.5. May 10, 2013 Expert Witness Report of Kevin F. Hallock 664 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page100 of 120 98 Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33. Powerpoint, 2010 Annual Performance Review, Compensation Training for Managers, December 2009, ADOBE_100614, exhibit 2487.15. Powerpoint, Compensation Framework, Insuring Global Consistency, Apple, 231APPLE105345, exhibit 1856.4 Powerpoint, Total Rewards Planning, FY07, September 2006, Apple, 231APPLE095052, exhibit 1855.107. Google document, Project Big Bang, Revised Comp Proposal – 9/7/2010, exhibit, 1625.2. Google document, GOOG-HIGH-TECH-00474908, exhibit 1618.12. LUCAS00188750-LUCAS00188753, exhibit 959.43-959.46. Intel spreadsheet printout 76579DOC005152_000017, exhibit 295.17. Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE 231APPLE098912, exhibit 1858.2. Compensation Analysis and Review Process, Internal Transfer, DRAFT Last Updated 11-23-04, LUCAS00185312, exhibit 716. Compensation 201 Instructor Guide, Intel, 76583DOC007693, exhibit 2030.65. Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5. Worldwide Focal 2001 Questions and Answers Intel Confidential, Rev 13, Feb 26, 2001. 76583DOC003753, exhibit 391.4. WorldatWork: The Total Rewards Association website: http://www.worldatwork.org/waw/aboutus/html/aboutus-whatis.html. Engineering Job Matrix, Pixar, PIX00049042, exhibit 1305. High-Tech Employee Antitrust Litigation, Consolidated Amended Complaint, September 2, 2011. Order by Judge Lucy H. Koh, Case5:11-cv-02509-LHK Document382 Filed04/05/13. Spreadsheet “Employee Type Count by Employer,” provided on February 22, 2013. Spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data”. May 10, 2013 Expert Witness Report of Kevin F. Hallock 665 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page101 of 120 99 GOOG-HIGH-TECH-00625148 Contains a courtesy reproduction of a compensation spreadsheet titled 2005 Global Ranges - for MQU May-06.xls. Exhibit 1600.l1 “Google 2004 Salary Ranges”Employer Costs for Employee Compensation – September 2012, United States Bureau of Labor Statistics, http://www.bls.gov/news.release/pdf/ecec.pdf. LUCAS00188913 (Exhibit 711.29) for 2008 Salary Structure. LUCAS00188912 (exhibit 360) for 2006 Salary Structure. May 10, 2013 Expert Witness Report of Kevin F. Hallock 666 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page102 of 120 100 APPENDIX C FIGURES May 10, 2013 Expert Witness Report of Kevin F. Hallock 667 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page103 of 120 101 Figure 1. Salary Table 2011-DCB Incorporating a locality payment of 24.22%, Rates Frozen at 2010 Levels For the locality pay area of Washington-Baltimore-Northern Virginia, DC-MD-VA-WV-PA Effective January 2011, Annual Rates by Grade and Step Grade Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8 Step 9 Step 10 1 22115 22854 23589 24321 25056 25489 26215 26948 26977 27663 2 24865 25456 26279 26977 27280 28082 28885 29687 30490 31292 3 27130 28034 28938 29843 30747 31651 32556 33460 34364 35269 4 30456 31471 32486 33501 34516 35531 36546 37560 38575 39590 5 34075 35210 36346 37481 38616 39752 40887 42022 43158 44293 6 37983 39249 40514 41780 43046 44312 45578 46843 48109 49375 7 42209 43616 45024 46431 47838 49246 50653 52061 53468 54875 8 46745 48303 49861 51418 52976 54534 56092 57649 59207 60765 9 51630 53350 55070 56791 58511 60232 61952 63673 65393 67114 10 56857 58752 60648 62544 64439 66335 68230 70126 72022 73917 11 62467 64548 66630 68712 70794 72876 74958 77040 79122 81204 12 74872 77368 79864 82359 84855 87350 89846 92341 94837 97333 13 89033 92001 94969 97936 100904 103872 106839 109807 112774 115742 14 105211 108717 112224 115731 119238 122744 126251 129758 133264 136771 15 123758 127883 132009 136134 140259 144385 148510 152635 155500 155500 Source: United States Office of Personnel Management: http://www.opm.gov/oca/11tables/pdf/DCB.pdf See Hallock (2012), p 69. May 10, 2013 Expert Witness Report of Kevin F. Hallock 668 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page104 of 120 102 Figure 2. Example of a Job Evaluation Worksheet Degree 1 Degree 2 Degree 3 Degree 4 Degree 5 Technical Ability 100 200 300 400 500 Leadership 40 80 120 160 200 Responsibility 30 60 90 120 150 Communications 20 40 60 80 100 Working Conditions 10 20 30 40 Total 50 See Hallock (2012), page 71. May 10, 2013 Expert Witness Report of Kevin F. Hallock 669 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page105 of 120 103 Figure 3. Example of a Job Evaluation Worksheet for a particular Job Degree 1 Degree 2 Degree 3 Degree 4 Degree 5 Total Technical Ability 100 200 300 400 500 400 Leadership 40 80 120 160 200 80 Responsibility 30 60 90 120 150 90 Communications 20 40 60 80 100 60 Working Conditions 10 20 30 40 50 10 640 Job Evaluation Points See Hallock (2012), page 72. May 10, 2013 Expert Witness Report of Kevin F. Hallock 670 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page106 of 120 104 Figure 4. Job Evaluation Points Engineer I (530 points) Engineer II (640 points) Senior Engineer (935 points) Job Evaluation Points See Hallock (2012), page 72. May 10, 2013 Expert Witness Report of Kevin F. Hallock 671 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page107 of 120 105 Figure 5. Evaluation Points in Different Job Families Engineer I (530 points) Engineer II (640 points) Senior Engineer (935 points) Job Evaluation Points Admin I (211 points) Admin II (411points) Admin Lead (657 points) Job Evaluation Points Legal Assistant (385 points) Junior Attorney (590 points) Senior Attorney (895 points) Job Evaluation Points See Hallock (2012), page 75. May 10, 2013 Expert Witness Report of Kevin F. Hallock 672 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page108 of 120 106 0 100000 200000 300000 400000 Figure 6. Market Pay Line 200 250 300 350 Job Evaluation Points Total Compensation 400 450 Fitted values See Hallock (2012), page 79. May 10, 2013 Expert Witness Report of Kevin F. Hallock 673 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page109 of 120 107 Figure 7. Example of an Internal Structure from Google in 2004 Source: Created from data in spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data”. May 10, 2013 Expert Witness Report of Kevin F. Hallock 674 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page110 of 120 108 Figure 8. From Apple Proposed FY10 Annual Grant Guidelines Source: Powerpoint, Apple Inc., Compensation Committee, Apple, August 5, 2009, 231APPLE10067, exhibit 1854.5. May 10, 2013 Expert Witness Report of Kevin F. Hallock 675 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page111 of 120 109 Figure 9. Apple Salary, Total Cash and Bonus Source: Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE 231APPLE098912, exhibit 1858.2 May 10, 2013 Expert Witness Report of Kevin F. Hallock 676 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page112 of 120 110 Figure 10. Apple Salary Structure in Table Note: Annual Salaries in Thousands. Source: Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5. May 10, 2013 Expert Witness Report of Kevin F. Hallock 677 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page113 of 120 111 Figure 11. Apple Salary Structure in Figure Source: Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5. May 10, 2013 Expert Witness Report of Kevin F. Hallock 678 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page114 of 120 112 Figure 12. Google, Merit Increase Matrix May 10, 2013 Expert Witness Report of Kevin F. Hallock 679 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page115 of 120 113 Figure 13. Adobe Salary Increase Matrices, 2009 Source: Powerpoint, 2010 Annual Performance Review, Compensation Training for Managers, December 2009, ADOBE_100614, exhibit 2487.15. May 10, 2013 Expert Witness Report of Kevin F. Hallock 680 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page116 of 120 114 Figure 14. Apple Total Rewards Planning Source: Powerpoint, Total Rewards Planning, FY07, September 2006, Apple, 231APPLE095052, exhibit, 1855.107. May 10, 2013 Expert Witness Report of Kevin F. Hallock 681 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page117 of 120 115 Figure 15. Excerpts from Adobe Global Market Analysis Salary Matrices Source: Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33. May 10, 2013 Expert Witness Report of Kevin F. Hallock 682 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page118 of 120 116 Figure 16. From Intel “Applying Pay Report to Focal Decisions” Source: PowerPoint, Base Pay Comparison Report Support Overview WW 042011, 765825DOC001211, exhibit 400.17. May 10, 2013 Expert Witness Report of Kevin F. Hallock 683 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page119 of 120 117 Figure 17 Google Data May 10, 2013 Expert Witness Report of Kevin F. Hallock 684 Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page120 of 120 118 Figure 18 May 10, 2013 Expert Witness Report of Kevin F. Hallock 685 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page1 of 29 Exhibit 71 686 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 1 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page2 of 29 687 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 2 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page3 of 29 688 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 3 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page4 of 29 689 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 4 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page5 of 29 690 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 5 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page6 of 29 691 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 6 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page7 of 29 692 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 7 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page8 of 29 693 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 8 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page9 of 29 694 Case5:11-cv-02509-LHK Document188-10 Filed 09/24/10 Page 9 ofof 29 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page10 22 695 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 10 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page11 of 29 696 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 11 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page12 of 29 697 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 12 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page13 of 29 698 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 13 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page14 of 29 699 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 14 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page15 of 29 700 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 15 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page16 of 29 701 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 16 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page17 of 29 702 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 17 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page18 of 29 703 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 18 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page19 of 29 704 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 19 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page20 of 29 705 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 20 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page21 of 29 706 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 21 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page22 of 29 707 Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 22 of 22 Case 1:10-cv-01629-RBW Document 2 Filed10/01/12 Page23 of 29 708 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page24 of 29 Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 1 6 709 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page25 of 29 Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 2 6 710 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page26 of 29 Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 3 6 711 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page27 of 29 Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 4 6 712 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page28 of 29 Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 5 6 713 Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page29 of 29 Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 6 6 714 Case5:11-cv-02509-LHK Document209 Filed11/12/12 Page1 of 32 715 Case5:11-cv-02509-LHK Document209 Filed11/12/12 Page29 of 32 716 Case5:11-cv-02509-LHK Document209 Filed11/12/12 Page30 of 32 717 Case: 12-80188 01/16/2013 ID: 8475821 DktEntry: 5 Page: 1 of 1 FILED UNITED STATES COURT OF APPEALS FOR THE NINTH CIRCUIT SHIRLEY RAE ELLIS, on behalf of herself and all others similarly situated, and LEAH HORSTMAN, Plaintiffs - Respondents, JAN 16 2013 MOLLY C. DWYER, CLERK U .S. C O U R T OF APPE ALS No. 12-80188 D.C. No. 3:04-cv-03341-MHP Northern District of California, San Francisco v. ORDER COSTCO WHOLESALE CORPORATION, Defendant - Petitioner. Before: CLIFTON and N.R. SMITH, Circuit Judges. The court, in its discretion, denies the petition for permission to appeal the district court’s September 25, 2012 order granting class action certification. See Fed. R. Civ. P. 23(f); Chamberlan v. Ford Motor Co., 402 F.3d 952 (9th Cir. 2005) (per curiam). KS/MOATT 718 SUPPLEMENTAL EXCERPTS OF RECORD SUBMITTED UNDER SEAL Pages 719-1128 ADRMOP,CONSOL,E-Filing,PRVADR,RELATE U.S. District Court California Northern District (San Jose) CIVIL DOCKET FOR CASE #: 5:11-cv-02509-LHK In re: High-Tech Employee Antitrust Litigation Assigned to: Hon. Lucy H. Koh Referred to: Magistrate Judge Paul Singh Grewal Relate Case Case: 5:12-cv-01262-LHK Case in other court: Alameda County Superior Court, RG 11574066 Cause: 28:1441 Petition for Removal Date Filed: 05/23/2011 Jury Demand: Both Nature of Suit: 442 Civil Rights: Jobs Jurisdiction: Federal Question In Re Attorney Palm Inc. Non-Parties Plaintiff Siddharth Hariharan individually and on behalf of all others similarly situated represented by Benjamin Patrick Smith Morgan, Lewis & Bockius, LLP One Market, Spear Street Tower San Francisco, CA 94105 415-442-1000 Fax: 415-442-1001 Email: bpsmith@morganlewis.com LEAD ATTORNEY ATTORNEY TO BE NOTICED represented by Anne Brackett Shaver Lieff, Cabraser, Heimann & Bernstein LLP 275 Battery Street. 29th Floor San Francisco, CA 94111 415-956-1000 Fax: 4159561008 Email: ashaver@lchb.com ATTORNEY TO BE NOTICED Brendan Patrick Glackin Lieff, Cabraser, Heimann & Bernstein LLP 275 Battery Street 29th Floor San Francisco, CA 94111-3339 415-956-1000 Fax: 415-956-1008 Email: bglackin@lchb.com ATTORNEY TO BE NOTICED Dean Michael Harvey Lieff, Cabraser, Heimann & Bernstein, LLP 275 Battery Street 29th Floor San Francisco, CA 94111-3339 415-956-1000 Email: dharvey@lchb.com ATTORNEY TO BE NOTICED Eric L. Cramer 1129 Berger & Montague, P.C. 1622 Locust Street Philadelphia, PA 19103 215-875-3000 Fax: 215-875-4604 Email: ecramer@bm.net PRO HAC VICE ATTORNEY TO BE NOTICED Eric B. Fastiff Lieff, Cabraser, Heimann & Bernstein,LLP 275 Battery Street 29th Floor San Francisco, CA 94111-3339 415-956-1000 Fax: 415-956-1008 Email: efastiff@lchb.com ATTORNEY TO BE NOTICED James Gerard Beebe Dallal Joseph Saveri Law Firm 255 California Street, Suite 450 San Francisco, CA 94111 (415) 500-6800 Email: jdallal@saverilawfirm.com ATTORNEY TO BE NOTICED John D. Radice Grant & Eisenhofer P.A. 485 Lexington Avenue 29th Floor New York, NY 10017 646-722-8500 Fax: 646-722-8501 TERMINATED: 06/14/2012 ATTORNEY TO BE NOTICED Joseph Peter Forderer Leiff Cabraser Heimann Bernstein LLP 275 Battery Street 29th Floor San Francisco, CA 94111-3339 415-956-1000 Email: jforderer@lchb.com ATTORNEY TO BE NOTICED Joseph R. Saveri Joseph Saveri Law Firm, Inc. 505 Montgomery Street Suite 625 San Francisco, CA 94111 (415) 500-6800 Fax: (415) 395-9940 Email: jsaveri@saverilawfirm.com ATTORNEY TO BE NOTICED Joshua P. Davis 1130 University of San Francisco School of Law 2130 Fulton Street San Francisco, CA 94117 415-422-6223 Email: davisj@usfca.edu ATTORNEY TO BE NOTICED Katherine M Lehe Law Foundation of Silicon Valley Fair Housing Law Project 152 N. Third St. 3rd Floor San Jose, CA 95112 408-280-2458 Fax: 408-293-0106 Email: katherine.lehe@lawfoundation.org TERMINATED: 03/23/2012 ATTORNEY TO BE NOTICED Kelly M. Dermody Leiff Cabraser Heimann & Bernstein LLP 275 Battery Street, 29th Floor San Francisco, CA 94111-3339 415-956-1000 Fax: 415-956-1008 Email: kdermody@lchb.com ATTORNEY TO BE NOTICED Kevin Edward Rayhill Joseph Saveri Law Firm, Inc. 505 Montgomery Street Suite 625 San Francisco, CA 94111 (415) 500-6800 Fax: (415) 395-9940 Email: krayhill@saverilawfirm.com ATTORNEY TO BE NOTICED Linda Phyllis Nussbaum Grant & Eisenhofer P.A. 485 Lexington Avenue 29th Floor New York, NY 10017 646-722-8500 Fax: 646-722-8501 Email: lnussbaum@gelaw.com PRO HAC VICE ATTORNEY TO BE NOTICED Lisa Janine Cisneros Lieff, Cabraser, Heimann and Bernstein, LLP 275 Battery Street, 29th Floor San Francisco, CA 94111-3339 415-956-1000 Email: lcisneros@lchb.com ATTORNEY TO BE NOTICED 1131 Peter A. Barile , III Grant & Eisenhofer, P.C. 485 Lexington Avenue New York, NY 10017 (646) 722-8500 Fax: (302) 622-7100 Email: pbarile@gelaw.com PRO HAC VICE ATTORNEY TO BE NOTICED Richard Martin Heimann Lieff Cabraser Heimann & Bernstein 275 Battery Street, 30th Floor San Francisco, CA 94111-3339 415-956-1000 Email: rheimann@lchb.com ATTORNEY TO BE NOTICED Sarah Rebecca Schalman-Bergen Berger and Montague, P.C. 1622 Locust Street Philadelphia, PA 19103 215-875-3053 Fax: 215-875-4604 Email: sschalman-bergen@bm.net PRO HAC VICE ATTORNEY TO BE NOTICED Shanon Jude Carson Berger & Montague, P.C. 1622 Locust Street Philadelphia, PA 19103 215-875-4656 Fax: 215-875-4604 Email: scarson@bm.net PRO HAC VICE ATTORNEY TO BE NOTICED Plaintiff Brandon Marshall represented by Anne Brackett Shaver (See above for address) ATTORNEY TO BE NOTICED Brendan Patrick Glackin (See above for address) ATTORNEY TO BE NOTICED Dean Michael Harvey (See above for address) ATTORNEY TO BE NOTICED Eric L. Cramer (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Eric B. Fastiff 1132 (See above for address) ATTORNEY TO BE NOTICED James Gerard Beebe Dallal (See above for address) ATTORNEY TO BE NOTICED John D. Radice (See above for address) TERMINATED: 06/14/2012 ATTORNEY TO BE NOTICED Joseph Peter Forderer (See above for address) ATTORNEY TO BE NOTICED Joseph R. Saveri (See above for address) ATTORNEY TO BE NOTICED Joshua P. Davis (See above for address) ATTORNEY TO BE NOTICED Katherine M Lehe (See above for address) TERMINATED: 03/23/2012 ATTORNEY TO BE NOTICED Kelly M. Dermody (See above for address) ATTORNEY TO BE NOTICED Kevin Edward Rayhill (See above for address) ATTORNEY TO BE NOTICED Linda Phyllis Nussbaum (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Lisa Janine Cisneros (See above for address) ATTORNEY TO BE NOTICED Peter A. Barile , III (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Richard Martin Heimann (See above for address) ATTORNEY TO BE NOTICED Sarah Rebecca Schalman-Bergen 1133 (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Shanon Jude Carson (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Plaintiff Michael Devine represented by Anne Brackett Shaver (See above for address) ATTORNEY TO BE NOTICED Brendan Patrick Glackin (See above for address) ATTORNEY TO BE NOTICED Dean Michael Harvey (See above for address) ATTORNEY TO BE NOTICED Eric L. Cramer (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Eric B. Fastiff (See above for address) ATTORNEY TO BE NOTICED James Gerard Beebe Dallal (See above for address) ATTORNEY TO BE NOTICED John D. Radice (See above for address) TERMINATED: 06/14/2012 ATTORNEY TO BE NOTICED Joseph Peter Forderer (See above for address) ATTORNEY TO BE NOTICED Joseph R. Saveri (See above for address) ATTORNEY TO BE NOTICED Joshua P. Davis (See above for address) ATTORNEY TO BE NOTICED Katherine M Lehe (See above for address) TERMINATED: 03/23/2012 ATTORNEY TO BE NOTICED Kelly M. Dermody 1134 (See above for address) ATTORNEY TO BE NOTICED Kevin Edward Rayhill (See above for address) ATTORNEY TO BE NOTICED Linda Phyllis Nussbaum (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Lisa Janine Cisneros (See above for address) ATTORNEY TO BE NOTICED Lisa Jennifer Leebove Joseph Saveri Law Firm 255 California Street Suite 450 San Francisco, CA 94111 415 500 6800 Fax: 415 500 6803 Email: lleebove@saverilawfirm.com ATTORNEY TO BE NOTICED Peter A. Barile , III (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Richard Martin Heimann (See above for address) ATTORNEY TO BE NOTICED Sarah Rebecca Schalman-Bergen (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Shanon Jude Carson (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Plaintiff Mark Fichtner represented by Anne Brackett Shaver (See above for address) ATTORNEY TO BE NOTICED Brendan Patrick Glackin (See above for address) ATTORNEY TO BE NOTICED Dean Michael Harvey (See above for address) 1135 ATTORNEY TO BE NOTICED Eric L. Cramer (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Eric B. Fastiff (See above for address) ATTORNEY TO BE NOTICED James Gerard Beebe Dallal (See above for address) ATTORNEY TO BE NOTICED John D. Radice (See above for address) TERMINATED: 06/14/2012 ATTORNEY TO BE NOTICED Joseph Peter Forderer (See above for address) ATTORNEY TO BE NOTICED Joseph R. Saveri (See above for address) ATTORNEY TO BE NOTICED Joshua P. Davis (See above for address) ATTORNEY TO BE NOTICED Katherine M Lehe (See above for address) TERMINATED: 03/23/2012 ATTORNEY TO BE NOTICED Kelly M. Dermody (See above for address) ATTORNEY TO BE NOTICED Kevin Edward Rayhill (See above for address) ATTORNEY TO BE NOTICED Linda Phyllis Nussbaum (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Lisa Janine Cisneros (See above for address) ATTORNEY TO BE NOTICED Peter A. Barile , III (See above for address) PRO HAC VICE 1136 ATTORNEY TO BE NOTICED Richard Martin Heimann (See above for address) ATTORNEY TO BE NOTICED Sarah Rebecca Schalman-Bergen (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Shanon Jude Carson (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Plaintiff Daniel Stover represented by Anne Brackett Shaver (See above for address) ATTORNEY TO BE NOTICED Brendan Patrick Glackin (See above for address) ATTORNEY TO BE NOTICED Dean Michael Harvey (See above for address) ATTORNEY TO BE NOTICED Eric L. Cramer (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Eric B. Fastiff (See above for address) ATTORNEY TO BE NOTICED James Gerard Beebe Dallal (See above for address) ATTORNEY TO BE NOTICED John D. Radice (See above for address) TERMINATED: 06/14/2012 ATTORNEY TO BE NOTICED Joseph Peter Forderer (See above for address) ATTORNEY TO BE NOTICED Joseph R. Saveri (See above for address) ATTORNEY TO BE NOTICED Joshua P. Davis (See above for address) 1137 ATTORNEY TO BE NOTICED Katherine M Lehe (See above for address) TERMINATED: 03/23/2012 ATTORNEY TO BE NOTICED Kelly M. Dermody (See above for address) ATTORNEY TO BE NOTICED Kevin Edward Rayhill (See above for address) ATTORNEY TO BE NOTICED Linda Phyllis Nussbaum (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Lisa Janine Cisneros (See above for address) ATTORNEY TO BE NOTICED Peter A. Barile , III (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Richard Martin Heimann (See above for address) ATTORNEY TO BE NOTICED Sarah Rebecca Schalman-Bergen (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Shanon Jude Carson (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Plaintiff UNITED STATES OF AMERICA V. represented by Anna Tryon Pletcher Department of Justice Antitrust Division 450 Golden Gate Avenue Box 36046 Room 10-0101 San Francisco, CA 94102 415-436-6727 Fax: 415-436-6687 Email: anna.pletcher@usdoj.gov ATTORNEY TO BE NOTICED 1138 Defendant Adobe Systems Inc. represented by Robert Addy Van Nest Keker & Van Nest LLP 633 Battery Street San Francisco, CA 94111-1809 415-391-5400 Fax: 415-397-7188 Email: rvannest@kvn.com LEAD ATTORNEY ATTORNEY TO BE NOTICED Craig Andrew Waldman Jones Day 555 California Street 26th Floor San Francisco, CA 94104 415-626-3939 Fax: 415-875-5700 Email: cwaldman@jonesday.com ATTORNEY TO BE NOTICED David Craig Kiernan Jones Day 555 California Street, 26th Floor San Francisco, CA 94104 (415) 626-3939 Fax: (415) 875-5700 Email: dkiernan@jonesday.com ATTORNEY TO BE NOTICED Robert Allan Mittelstaedt Jones Day 555 California Street, 26th Floor San Francisco, CA 94104 (415) 626-3939 Fax: (415) 875-5700 Email: ramittelstaedt@jonesday.com ATTORNEY TO BE NOTICED Lin W. Kahn Jones Day 555 California Street, 26th Floor San Francisco, CA 94104 (415) 875-5844 Fax: (415) 963-6825 Email: linkahn@jonesday.com ATTORNEY TO BE NOTICED Defendant Apple Inc. represented by George A. Riley O'Melveny & Myers LLP 2 Embarcadero Center 28th Floor San Francisco, CA 94111 415/984-8741 Fax: 415-984-8701 1139 Email: griley@omm.com LEAD ATTORNEY ATTORNEY TO BE NOTICED Robert Addy Van Nest (See above for address) LEAD ATTORNEY ATTORNEY TO BE NOTICED Amanda R. Conley O'Melveny and Myers Two Embarcadero Center 28th Floor San Francisco, CA 94111 415-984-8829 Email: aconley@omm.com ATTORNEY TO BE NOTICED Christina Joanne Brown O'Melveny & Myers Two Embarcadero Center, 28th Floor San Francisco, CA 94111-3823 415-984-8979 Fax: 415-984-8701 Email: cjbrown@omm.com ATTORNEY TO BE NOTICED Flora F Vigo O'Melveny & Myers LLP Two Embarcadero Center 28th Floor San Francisco, CA 94111 415.984.8700 Fax: 415.984.8701 Email: fvigo@omm.com ATTORNEY TO BE NOTICED George Riley O'Melveny Myers LLP Two Embarcadero Center 28th Floor San Francisco, CA 94111-3823 415-984-8741 Fax: 415-984-8701 Email: griley@omm.com PRO HAC VICE ATTORNEY TO BE NOTICED Michael Frederick Tubach O'Melveny & Myers LLP Two Embarcadero Center 28th Floor San Francisco, CA 94111-3305 415-984-8700 Fax: 415-984-8701 Email: mtubach@omm.com 1140 ATTORNEY TO BE NOTICED Defendant Google Inc. represented by Anne M Selin Mayer Brown LLP Two Palo Alto Square Suite 300 3000 El Camino Real Palo Alto, CA 94306 650-331-2000 Fax: 650-331-2060 Email: aselin@mayerbrown.com ATTORNEY TO BE NOTICED Daniel Edward Purcell Keker & Van Nest LLP 633 Battery Street San Francisco, CA 94111-1809 415-391-5400 Fax: 415-397-7188 Email: dpurcell@kvn.com ATTORNEY TO BE NOTICED Donald M. Falk Mayer Brown LLP Two Palo Alto Square Suite 300 Palo Alto, CA 94306-2112 650-331-2030 Fax: 650-331-2060 Email: dfalk@mayerbrown.com ATTORNEY TO BE NOTICED Edward D. Johnson Mayer Brown LLP Two Palo Alto Square Suite 300 Palo Alto, CA 94306-2112 650-331-2000 Fax: 650-331-2060 Email: wjohnson@mayerbrown.com ATTORNEY TO BE NOTICED Eric Evans Mayer Brown LLP Two Palo Alto Square, Suite 300 3000 El Camino Real Palo Alto, CA 94306-2112 650-331-2000 Fax: 650 331-2060 Email: eevans@mayerbrown.com ATTORNEY TO BE NOTICED Eugene Morris Paige Keker & Van Nest LLP 633 Battery Street San Francisco, CA 94111-1809 415-391-5400 1141 Fax: 415-397-7188 Email: EMP@kvn.com ATTORNEY TO BE NOTICED Justina Kahn Sessions Keker & Van Nest LLP 633 Battery Street San Francisco, CA 94111 415-391-5400 Fax: 415-397-7188 Email: jsessions@kvn.com ATTORNEY TO BE NOTICED Lee H. Rubin Mayer Brown LLP Two Palo Alto Square Suite 300 Palo Alto, CA 94306-2112 (650-331-2000 Fax: (650) 331-2060 Email: lrubin@mayerbrown.com ATTORNEY TO BE NOTICED Robert Addy Van Nest (See above for address) ATTORNEY TO BE NOTICED Defendant Intel Corp. represented by Gregory P. Stone Munger Tolles & Olson LLP 355 South Grand Avenue 35th Floor Los Angeles, CA 90071-1560 213-683-9100 Fax: 213-687-3702 Email: gregory.stone@mto.com LEAD ATTORNEY ATTORNEY TO BE NOTICED Robert Addy Van Nest (See above for address) LEAD ATTORNEY ATTORNEY TO BE NOTICED Angela Marie Munoz Bingham McCutchen 3 Embarcadero Center SF, CA 94111 415-393-2370 Fax: 415-393-2286 Email: angela.munoz@bingham.com TERMINATED: 04/26/2012 ATTORNEY TO BE NOTICED Bradley S. Phillips Munger Tolles & Olson LLP 1142 355 S. Grand Avenue 35th Floor Los Angeles, CA 90071-1569 213-683-9100 Fax: 213-683-3702 Email: phillipsbs@mto.com ATTORNEY TO BE NOTICED Donn P. Pickett Bingham McCutchen , LLP Three Embarcadero Center San Francisco, CA 94111-4067 415-393-2000 Fax: 415-393-2286 Email: donn.pickett@bingham.com TERMINATED: 10/20/2013 ATTORNEY TO BE NOTICED Frank H Busch Bingham McCutchen Three Embarcadero Center San Francisco, Ca 94111 United Sta 415-393-2074 Fax: 415-393-2286 Email: frank.busch@bingham.com TERMINATED: 10/20/2013 ATTORNEY TO BE NOTICED Frank Hinman Bingham McCutchen LLP Three Embarcadero Center, 18th Floor San Francisco, CA 94111 415-393-2462 Fax: 415-383-2286 Email: frank.hinman@bingham.com TERMINATED: 10/20/2013 ATTORNEY TO BE NOTICED Gregory M Sergi Munger Tolles & Olson LLP 355 South Grand Avenue Suite 3500 Los Angeles, CA 90071 213-683-9100 ATTORNEY TO BE NOTICED Holly A. House Paul Hastings LLP 55 Second Street Twenty-Fourth Floor San Francisco, CA 94105 415-856-7217 Fax: 415-856-7317 Email: hollyhouse@paulhastings.com TERMINATED: 09/27/2011 ATTORNEY TO BE NOTICED 1143 John P Mittelbach Munger Tolles Olson LLP 355 S. Grand Ave 35th Floor Los Angeles, CA 90071 213-683-9166 Email: john.mittelbach@mto.com ATTORNEY TO BE NOTICED Sujal Shah Bingham McCutchen LLP Three Embarcadero Center San Francisco, CA 94111-4067 (415) 393-2955 Fax: 415-393-2286 Email: sujal.shah@bingham.com TERMINATED: 10/20/2013 ATTORNEY TO BE NOTICED Zachary J. Alinder Bingham McCutchen, LLP Three Embarcadero Center San Francisco, CA 94111 (415) 393-2226 Fax: (415) 393-2286 Email: zachary.alinder@bingham.com TERMINATED: 04/26/2012 ATTORNEY TO BE NOTICED Krystal N. Bowen Bingham McCutchen Three Embarcadero Center San Francisco, CA 94611 415-393-2760 Fax: 415-393-2286 Email: krystal.bowen@bingham.com TERMINATED: 10/20/2013 ATTORNEY TO BE NOTICED Defendant Intuit Inc. represented by Catherine Tara Zeng Jones Day 1755 Embarcadero Rd Palo Alto, CA 94303 650-739-3939 Fax: 650-739-3900 Email: czeng@jonesday.com ATTORNEY TO BE NOTICED Craig Ellsworth Stewart Jones Day 555 California Street, 26th Floor San Francisco, CA 94104 (415) 626-3939 Fax: (415) 875-5700 Email: cestewart@jonesday.com 1144 ATTORNEY TO BE NOTICED David Craig Kiernan (See above for address) ATTORNEY TO BE NOTICED Robert Allan Mittelstaedt (See above for address) ATTORNEY TO BE NOTICED Defendant Lucasfilm Ltd. represented by Chinue Turner Richardson 1201 Pennsylvania Ave NW Washington, DC 20004 United Sta 202-662-5766 Fax: 202-778-5766 Email: crichardson@cov.com ATTORNEY TO BE NOTICED Cody Shawn Harris Keker and Van Nest LLP 633 Battery Street San Francisco, CA 94111-1809 415-391-5400 Fax: 415-397-7188 Email: charris@kvn.com ATTORNEY TO BE NOTICED Daniel Edward Purcell (See above for address) TERMINATED: 07/24/2013 ATTORNEY TO BE NOTICED Deborah A. Garza Covington and Burling LLP 1201 Pennsylvania Avenue, NW Washington, DC 20004 202-662-5146 Fax: 202-778-5146 Email: dgarza@cov.com ATTORNEY TO BE NOTICED Emily Johnson Henn Covington & Burling LLP 333 Twin Dolphin Drive Suite 700 Redwood Shores, CA 94065 650-632-4700 Email: ehenn@cov.com ATTORNEY TO BE NOTICED Eugene Morris Paige (See above for address) TERMINATED: 07/24/2013 ATTORNEY TO BE NOTICED John Watkins Keker 1145 Keker & Van Nest LLP 633 Battery Street San Francisco, CA 94111-1809 415/391-5400 Fax: 415-397-7188 Email: jwk@kvn.com TERMINATED: 07/24/2013 ATTORNEY TO BE NOTICED John W. Nields , Jr. Covington and Burling LLC 1201 Pennsylvania Avenue, N.W. Washington, DC 20004 202-662-5058 Email: jnields@cov.com ATTORNEY TO BE NOTICED Justina Kahn Sessions (See above for address) TERMINATED: 07/24/2013 ATTORNEY TO BE NOTICED Paula Lenore Blizzard Keker & Van Nest LLP 633 Battery Street San Francisco, CA 94111 (415) 391-5400 Fax: (415) 397-7188 Email: plb@kvn.com ATTORNEY TO BE NOTICED Thomas A. Isaacson Covington & Burling LLP 3600 1201 Pennsylvania Avenue, N.W. Washington, DC 20004 202-783-0800 Fax: 202-383-6610 Email: tisaacson@cov.com ATTORNEY TO BE NOTICED Defendant Pixar represented by Robert T. Haslam , III Covington & Burling LLP 333 Twin Dolphin Drive Suite 700 Redwood Shores, CA 94065 (650) 632-4702 Fax: (650) 632-4800 Email: rhaslam@cov.com TERMINATED: 05/14/2013 LEAD ATTORNEY ATTORNEY TO BE NOTICED Chinue Turner Richardson (See above for address) 1146 PRO HAC VICE ATTORNEY TO BE NOTICED Deborah A. Garza , Covington and Burling LLP 1201 Pennsylvania Avenue, NW Washington, DC 20004 202-662-5146 Fax: 202-778-5146 Email: dgarza@cov.com PRO HAC VICE ATTORNEY TO BE NOTICED Emily Johnson Henn Covington & Burling LLP 333 Twin Dolphin Drive Suite 700 Redwood Shores, CA 94065 650-632-4700 Email: ehenn@cov.com ATTORNEY TO BE NOTICED John W. Nields , Jr. (See above for address) PRO HAC VICE ATTORNEY TO BE NOTICED Jonathan A D Herczeg , Convington Burling LLP 1201 Pennsylvania Avenue, NW Washington, DC 20004 202-662-5052 Fax: Email: jherczeg@cov.com TERMINATED: 11/21/2012 PRO HAC VICE ATTORNEY TO BE NOTICED Thomas A. Isaacson Howrey LLP 3600 1299 Pennsylvania Avenue, N.W. Washington, DC 20004 202-783-0800 Fax: 202-383-6610 Email: tisaacson@cov.com PRO HAC VICE ATTORNEY TO BE NOTICED Date Filed # Docket Text 05/23/2011 1 JOINT NOTICE OF REMOVAL of Action from State Court; No Process from Alameda County Superior Court. Their case number is RG11574066. (Filing fee $350.00 receipt number 34611060153). Filed by Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Civil Cover Sheet) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 1147 05/23/2011 2 Declaration of Cody Harris in Support of 1 Notice of Removal (Alameda County Superior Court Complaint attach) filed by Lucasfilm Ltd.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 3 Declaration of David Anderman in Support of 1 Notice of Removal, filed by Lucasfilm Ltd.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 4 Declaration of Rhonda Hjort in Support of 1 Notice of Removal, filed by Lucasfilm Ltd.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 5 Declaration of Jack Gilmore in Support of 1 Notice of Removal, filed by Adobe Systems, Inc. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 6 Declaration of Joel Pdolyny in Support of 1 Notice of Removal, filed by Apple Inc. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 7 Declaration of Tadhg Bourke in Support of 1 Notice of Removal, filed by Google Inc. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 8 Declaration of James M. Kennedy in Support of 1 Notice of Removal, filed by Pixar. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 9 Declaration of Debbie R. Oldham-Auker in Support of 1 Notice of Removal, filed by Intel Corp.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 10 Certificate of Interested Entities by Lucasfilm Ltd. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 11 NOTICE of Corporate Disclosure Statement by Apple Inc. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 12 NOTICE of Corporate Disclosure Statement by Adobe Systems Inc. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 13 NOTICE of Corporate Disclosure Statement by Google Inc. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 14 NOTICE of Corporate Disclosure Statement by Intuit Inc. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 15 NOTICE of Corporate Disclosure Statement by Pixar (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 16 ADR SCHEDULING ORDER: Case Management Statement due by 8/26/2011. Case Management Conference set for 9/2/2011 01:30 PM in Courtroom A, 15th Floor, San Francisco. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/23/2011 CASE DESIGNATED for Electronic Filing. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011) 05/24/2011 18 AMENDED Declaration of Cody Harris in Support of 1 Notice of Removal, filed by Lucasfilm Ltd.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/24/2011) (Entered: 05/26/2011) 05/24/2011 19 NOTICE of Corporate Disclosure Statement by Intel Corp. (gba, COURT STAFF) (Filed on 5/24/2011) (Entered: 05/26/2011) 05/24/2011 20 CERTIFICATE OF SERVICE by Lucasfilm Ltd. re 7 Declaration in Support, 14 Notice (Other), 15 Notice (Other), 11 Notice (Other), 6 Declaration in Support, 1 Notice of Removal, 10 Certificate of Interested Entities, 3 Declaration in Support, 12 Notice (Other), 4 1148 Declaration in Support, 5 Declaration in Support, 9 Declaration in Support, 8 Declaration in Support, 13 Notice (Other), 2 Declaration in Support, 16 ADR Scheduling Order (gba, COURT STAFF) (Filed on 5/24/2011) (Entered: 05/26/2011) 05/24/2011 21 CERTIFICATE OF SERVICE by Lucasfilm Ltd. re 18 Declaration in Support, 19 Notice (Other) (gba, COURT STAFF) (Filed on 5/24/2011) (Entered: 05/26/2011) 05/26/2011 17 STIPULATION /Extending Time To Respond To Complaint by Adobe Systems Inc., Apple Inc., Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Tubach, Michael) (Filed on 5/26/2011) (Entered: 05/26/2011) 05/27/2011 22 Declination to Proceed Before a U.S. Magistrate Judge by Siddharth Hariharan. (Harvey, Dean) (Filed on 5/27/2011) (Entered: 05/27/2011) 05/31/2011 23 CLERK'S NOTICE of Impending Reassignment to U.S. District Judge (klhS, COURT STAFF) (Filed on 5/31/2011) (Entered: 05/31/2011) 06/01/2011 24 ORDER REASSIGNING CASE. Case reassigned to Judge Hon. Saundra Brown Armstrong for all further proceedings. Judge Magistrate Judge Joseph C. Spero no longer assigned to the case.. Signed by Executive Committee on 6/1/11. (as, COURT STAFF) (Filed on 6/1/2011) (Entered: 06/01/2011) 06/16/2011 25 MOTION for leave to appear in Pro Hac Vice for Deborah A. Garza ( Filing fee $ 275, receipt number 44611007160.) filed by Pixar. (Attachments: # 1 Proposed Order)(jlm, COURT STAFF) (Filed on 6/16/2011) (Entered: 06/17/2011) 06/16/2011 26 MOTION for leave to appear in Pro Hac Vice for Jonathan Herczeg ( Filing fee $ 275, receipt number 44611007160.) filed by Pixar. (Attachments: # 1 Proposed Order)(jlm, COURT STAFF) (Filed on 6/16/2011) (Entered: 06/17/2011) 06/20/2011 27 CASE MANAGEMENT SCHEDULING ORDER: Case Management Conference set for 9/15/2011 03:00 PM., via Telephone. Signed by Judge Saundra Brown Armstrong, on 6/20/11. (lrc, COURT STAFF) (Filed on 6/20/2011) Modified on 6/21/2011 (jlm, COURT STAFF). (Entered: 06/20/2011) 06/21/2011 28 ORDER by Judge Saundra Brown Armstrong GRANTING 25 Motion for Pro Hac Vice for Deborah A. Garza (jlm, COURT STAFF) (Filed on 6/21/2011) (Entered: 06/23/2011) 06/21/2011 29 ORDER by Judge Saundra Brown Armstrong GRANTING 26 Motion for Pro Hac Vice for Jonathan Herczeg (jlm, COURT STAFF) (Filed on 6/21/2011) (Entered: 06/23/2011) 06/28/2011 30 NOTICE of Filing of Declaration of Kumud Kokal in Support re 1 Notice of Removal, filed by Lucasfilm Ltd.. (Purcell, Daniel) (Filed on 6/28/2011) Modified on 6/30/2011 (jlm, COURT STAFF). (Entered: 06/28/2011) 06/28/2011 31 Declaration of Daniel Purcell in Support re 1 Notice of Removal filed by Lucasfilm Ltd.. (Attachments: # 1 Exhibit)(Purcell, Daniel) (Filed on 6/28/2011) Modified on 6/30/2011 (jlm, COURT STAFF). (Entered: 06/28/2011) 06/29/2011 32 NOTICE of Pendency of other Actions or Proceedings, filed by Siddharth Hariharan (Harvey, Dean) (Filed on 6/29/2011) Modified on 6/30/2011 (jlm, COURT STAFF). (Entered: 06/29/2011) 06/29/2011 33 Declaration of Dean M. Harvey in Support of 32 Notice of Pendency of Other Actions or Proceedings filed by Siddharth Hariharan. (Attachments: # 1 Exhibit A, # 2 Exhibit B) (Related document(s) 32 ) (Harvey, Dean) (Filed on 6/29/2011) Modified on 6/30/2011 (jlm, COURT STAFF). (Entered: 06/29/2011) 06/30/2011 34 Certificate of Interested Entities by Siddharth Hariharan (Harvey, Dean) (Filed on 6/30/2011) (Entered: 06/30/2011) 06/30/2011 35 1149 Second NOTICE of Pendency of Other Actions or Proceedings, filed by Siddharth Hariharan (Harvey, Dean) (Filed on 6/30/2011) Modified on 7/1/2011 (jlm, COURT STAFF). (Entered: 06/30/2011) 06/30/2011 36 Declaration of Dean M. Harvey in Support of 35 Second Notice of Pendency of Other Actions or Proceedings filed by Siddharth Hariharan. (Attachments: # 1 Exhibit A)(Related document(s) 35 ) (Harvey, Dean) (Filed on 6/30/2011) Modified on 7/1/2011 (jlm, COURT STAFF). (Entered: 06/30/2011) 07/06/2011 37 MOTION for leave to appear in Pro Hac Vice for John D. Radice ( Filing fee $ 275, receipt number 34611061838.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order) (jlm, COURT STAFF) (Filed on 7/6/2011) (Entered: 07/08/2011) 07/06/2011 38 MOTION for leave to appear in Pro Hac Vice for Linda P. Nussbaum ( Filing fee $ 275, receipt number 34611061839.), filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order)(jlm, COURT STAFF) (Filed on 7/6/2011) (Entered: 07/08/2011) 07/13/2011 39 ORDER by Judge Saundra Brown Armstrong GRANTING 37 Motion for Pro Hac Vice for John D. Radice (jlm, COURT STAFF) (Filed on 7/13/2011) (Entered: 07/14/2011) 07/13/2011 40 ORDER by Judge Saundra Brown Armstrong GRANTING 38 Motion for Pro Hac Vice for Linda P. Nussbaum (jlm, COURT STAFF) (Filed on 7/13/2011) (Entered: 07/14/2011) 07/19/2011 41 MOTION to Relate Cases: C-11-3539-HRL; C-11-3538-HRL; C-11-3540-PSG; C-11-3541PSG, filed by Intuit Inc.. (Broderick, Catherine) (Filed on 7/19/2011) Modified on 7/20/2011 (jlm, COURT STAFF). (Entered: 07/19/2011) 07/19/2011 42 Declaration of Catherine T. Broderick in Support of 41 Motion to Relate Cases filed by Intuit Inc.. (Related document(s) 41 ) (Broderick, Catherine) (Filed on 7/19/2011) Modified on 7/20/2011 (jlm, COURT STAFF). (Entered: 07/19/2011) 07/19/2011 43 EXHIBITS to 42 Declaration in Support of Catherine T. Broderick filed by Intuit Inc.. (Attachments: # 1 Exhibit Exhibit A, # 2 Exhibit Exhibit B, # 3 Exhibit Exhibit C, # 4 Exhibit Exhibit D)(Related document(s) 42 ) (Broderick, Catherine) (Filed on 7/19/2011) Modified on 7/20/2011 (jlm, COURT STAFF). (Entered: 07/19/2011) 07/20/2011 44 RESPONSE re 41 Motion to Relate Cases filed by Siddharth Hariharan. (Harvey, Dean) (Filed on 7/20/2011) Modified on 7/21/2011 (jlm, COURT STAFF). (Entered: 07/20/2011) 07/20/2011 45 Declaration of Dean M. Harvey in Support of 44 Response to Motion to Relate Cases, filed by Siddharth Hariharan. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C)(Related document(s) 44 ) (Harvey, Dean) (Filed on 7/20/2011) Modified on 7/21/2011 (jlm, COURT STAFF). (Entered: 07/20/2011) 07/20/2011 46 Proposed Order re 32 , 35 Notice of Pendency of other Actions or Proceedings, by Siddharth Hariharan. (Harvey, Dean) (Filed on 7/20/2011) Modified on 7/21/2011 (jlm, COURT STAFF). (Entered: 07/20/2011) 07/20/2011 47 CERTIFICATE OF SERVICE by Intuit Inc. re 41 MOTION to Relate Case (Broderick, Catherine) (Filed on 7/20/2011) (Entered: 07/20/2011) 07/22/2011 48 STIPULATION Extending Time to Respond to Complaint, filed by Apple Inc., Adobe Systems Inc., Siddharth Hariharan, Lucasfilm Ltd., Google Inc., Intel Corp., Intuit Inc., Pixar. (Tubach, Michael) (Filed on 7/22/2011) Modified on 7/25/2011 (jlm, COURT STAFF). (Entered: 07/22/2011) 07/26/2011 49 MOTION for leave to appear in Pro Hac Vice for Sarah R. Schalman-Bergen ( Filing fee $ 275, receipt number 44611007340.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order)(jlm, COURT STAFF) (Filed on 7/26/2011) (Entered: 07/26/2011) 07/26/2011 50 MOTION for leave to appear in Pro Hac Vice for Shanon J. Carson ( Filing fee $ 275, receipt number 44611007340.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order) 1150 (jlm, COURT STAFF) (Filed on 7/26/2011) (Entered: 07/26/2011) 07/26/2011 51 MOTION for leave to appear in Pro Hac Vice for Eric L. Cramer ( Filing fee $ 275, receipt number 44611007340.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order) (jlm, COURT STAFF) (Filed on 7/26/2011) (Entered: 07/26/2011) 07/27/2011 52 ORDER by Judge Saundra Brown Armstrong GRANTING 41 Motion to Relate Cases: C-113539-HRL; C-11-3538-HRL; C-11-3540-PSG; C-11-3541-PSG. Signed by Judge Saundra Brown Armstrong, on 07/25/11 (lrc, COURT STAFF) (Filed on 7/27/2011) Modified on 7/28/2011 (jlm, COURT STAFF). (Entered: 07/27/2011) 07/28/2011 53 ORDER by Judge Saundra Brown Armstrong GRANTING 51 Motion for Pro Hac Vice for Eric L. Cramer (jlm, COURT STAFF) (Filed on 7/28/2011) (Entered: 07/28/2011) 07/28/2011 54 ORDER by Judge Saundra Brown Armstrong GRANTING 50 Motion for Pro Hac Vice for Shanon J. Carson (jlm, COURT STAFF) (Filed on 7/28/2011) (Entered: 07/28/2011) 07/28/2011 55 ORDER by Judge Saundra Brown Armstrong GRANTING 49 Motion for Pro Hac Vice for Sarah R. Schalman-Bergen (jlm, COURT STAFF) (Filed on 7/28/2011) (Entered: 07/28/2011) 08/02/2011 56 MOTION to Transfer Case to the San Jose Division, filed by Siddharth Hariharan. Responses due by 8/8/2011. (Attachments: # 1 Proposed Order)(Fastiff, Eric) (Filed on 8/2/2011) Modified on 8/3/2011 (jlm, COURT STAFF). (Entered: 08/02/2011) 08/02/2011 57 Declaration of Eric B. Fastiff in Support of 56 Motion to Transfer Actions to the San Jose Division filed by Siddharth Hariharan. (Related document(s) 56 ) (Fastiff, Eric) (Filed on 8/2/2011) Modified on 8/3/2011 (jlm, COURT STAFF). (Entered: 08/02/2011) 08/04/2011 58 ORDER: That case numbers C-11-2509-SBA, C-11-3538-SBA, C-11-3539-SBA, C-113540-SBA and C-11-3541-SBA be TRANSFERRED to the San Jose Division re 35 Notice and 56 Motion to Transfer Case. Signed by Judge Saundra Brown Armstrong, on 7/28/11. (lrc, COURT STAFF) (Filed on 8/4/2011) Modified on 8/5/2011 (jlm, COURT STAFF). (Entered: 08/04/2011) 08/05/2011 59 NOTICE of Change of Address by Daniel Edward Purcell (Purcell, Daniel) (Filed on 8/5/2011) (Entered: 08/05/2011) 08/05/2011 60 ORDER REASSIGNING CASE. Case reassigned to Judge Hon. Lucy H. Koh for all further proceedings. Judge Hon. Saundra Brown Armstrong no longer assigned to the case. Signed by The Executive Committee, on 08/05/2011. (jlm, COURT STAFF) (Filed on 8/5/2011) (Entered: 08/05/2011) 08/08/2011 61 CLERKS NOTICE SETTING CASE MANAGEMENT CONFERENCE AFTER REASSIGNMENT Case Management Statement due by 10/19/2011. Case Management Conference set for 10/26/2011 02:00 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT STAFF) (Filed on 8/8/2011) (Entered: 08/08/2011) 08/08/2011 62 CERTIFICATE OF SERVICE by Siddharth Hariharan of Standing Order Regarding Case Management In Civil Cases For The Northern District Of California, San Jose Division (Harvey, Dean) (Filed on 8/8/2011) (Entered: 08/08/2011) 08/11/2011 Case Assigned to Magistrate Judge Howard R. Lloyd for all discovery matters. (tsh, COURT STAFF) (Filed on 8/11/2011) (Entered: 08/11/2011) 09/06/2011 63 Proposed Pretrial Order Number 1 by Adobe Systems Inc., Intel Corp., Siddharth Hariharan, Pixar, Lucasfilm Ltd., Google Inc., Apple Inc., Intuit Inc.. (Harvey, Dean) (Filed on 9/6/2011) (Entered: 09/06/2011) 09/12/2011 64 ORDER re 21 in 5:11-cv-03541-LHK: Adopting, as modified, Proposed Pretrial Order No. 1. Signed by Judge Koh on 9/12/2011. Case Numbers 11-CV-3538, 11-CV-3539, 11-CV-3540 1151 and 11-CV-3541 are hereby CONSOLIDATED under MASTER FILE No. 11-CV-2509 LHK. All docket entries regarding the Consolidated Action shall be docketed under Master File Number 11-CV-2509. If a document pertains to only one or some of the consolidated cases, it will be docketed on the Master Docket with the notation in the docket text as to the case number(s) to which it pertains. (lhklc3, COURT STAFF) (Filed on 9/12/2011) Modified text on 9/13/2011 (dhm, COURT STAFF). (Entered: 09/12/2011) 09/13/2011 65 AMENDED COMPLAINT Consolidated against Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. Filed bySiddharth Hariharan. (Saveri, Joseph) (Filed on 9/13/2011) (Entered: 09/13/2011) 09/22/2011 66 MOTION for Leave to File DEFENDANT LUCASFILM LTD.'S MOTION FOR ADMINISTRATIVE RELIEF REQUESTING LEAVE TO FILE A SEPARATE MOTION TO DISMISS; DECLARATION OF DANIEL PURCELL IN SUPPORT filed by Lucasfilm Ltd.. (Attachments: # 1 Proposed Order)(Purcell, Daniel) (Filed on 9/22/2011) (Entered: 09/22/2011) 09/26/2011 67 OPPOSITION to ( 66 MOTION for Administrative Relief Requesting Leave to File a Separate Motion to Dismiss ) ; Declaration of Eric B. Fastiff in Opposition, filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 9/26/2011) Modified text on 9/27/2011 (dhm, COURT STAFF). (Entered: 09/26/2011) 09/27/2011 68 NOTICE of Substitution of Counsel by Frank Hinman substituting in for Holly A. House as counsel for Intel Corporation (Hinman, Frank) (Filed on 9/27/2011) (Entered: 09/27/2011) 09/28/2011 69 Order by Hon. Lucy H. Koh granting in part and denying in part 66 Motion for Leave to File. (lhklc1, COURT STAFF) (Filed on 9/28/2011) (Entered: 09/28/2011) 10/04/2011 70 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Kiernan, David) (Filed on 10/4/2011) (Entered: 10/04/2011) 10/04/2011 71 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Broderick, Catherine) (Filed on 10/4/2011) (Entered: 10/04/2011) 10/05/2011 72 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Harvey, Dean) (Filed on 10/5/2011) (Entered: 10/05/2011) 10/05/2011 73 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Alinder, Zachary) (Filed on 10/5/2011) (Entered: 10/05/2011) 10/06/2011 74 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Tubach, Michael) (Filed on 10/6/2011) (Entered: 10/06/2011) 10/12/2011 75 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options by Henn and Kennedy for Pixar (Henn, Emily) (Filed on 10/12/2011) (Entered: 10/12/2011) 10/13/2011 76 Statement DISCOVERY DISPUTE JOINT REPORT #1 by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Saveri, Joseph) (Filed on 10/13/2011) (Entered: 10/13/2011) 10/13/2011 77 MOTION to Dismiss filed by Lucasfilm Ltd.. Motion Hearing set for 1/19/2012 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 10/27/2011. Replies due by 11/3/2011. (Purcell, Daniel) (Filed on 10/13/2011) (Entered: 10/13/2011) 10/13/2011 78 Proposed Order re 77 Motion to Dismiss, by Lucasfilm Ltd.. (Purcell, Daniel) (Filed on 10/13/2011) Modified on 10/14/2011 linking entry to document #77 (dhm, COURT STAFF). (Entered: 10/13/2011) 10/13/2011 79 MOTION to Dismiss Consolidated Amended Complaint filed by Apple Inc.. Motion Hearing 1152 set for 1/19/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 11/4/2011. Replies due by 12/2/2011. (Attachments: # 1 Declaration, # 2 Proposed Order)(Tubach, Michael) (Filed on 10/13/2011) (Entered: 10/13/2011) 10/13/2011 80 Joint MOTION to Stay Discovery filed by Google Inc.. Motion Hearing set for 12/8/2011 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 10/27/2011. Replies due by 11/3/2011. (Attachments: # 1 Declaration of Lee H. Rubin, # 2 Exhibit A, # 3 Exhibit B, # 4 Proposed Order)(Rubin, Lee) (Filed on 10/13/2011) (Entered: 10/13/2011) 10/14/2011 81 CERTIFICATE OF SERVICE by Apple Inc. re 79 MOTION to Dismiss Consolidated Amended Complaint (Tubach, Michael) (Filed on 10/14/2011) (Entered: 10/14/2011) 10/14/2011 82 CLERKS NOTICE Continuing Motion Hearing, Set/Reset Deadlines as to 79 MOTION to Dismiss Consolidated Amended Complaint, 77 MOTION to Dismiss. Motion Hearing set for 1/26/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 10/14/2011) (Entered: 10/14/2011) 10/17/2011 83 Amended MOTION to Dismiss filed by Lucasfilm Ltd.. Motion Hearing set for 1/26/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 10/27/2011. Replies due by 11/3/2011. (Purcell, Daniel) (Filed on 10/17/2011) (Entered: 10/17/2011) 10/19/2011 84 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Shaver, Anne) (Filed on 10/19/2011) (Entered: 10/19/2011) 10/20/2011 85 JOINT CASE MANAGEMENT STATEMENT Amended Joint Case Management Conference Statement filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Shaver, Anne) (Filed on 10/20/2011) (Entered: 10/20/2011) 10/25/2011 86 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options of Google Inc. (Rubin, Lee) (Filed on 10/25/2011) (Entered: 10/25/2011) 10/25/2011 87 ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Harris, Cody) (Filed on 10/25/2011) (Entered: 10/25/2011) 10/26/2011 88 Minute Entry and Case Management Order: Initial Case Management Conference held on 10/26/2011 before Judge Lucy H. Koh (Date Filed: 10/26/2011). Further Case Management Conference set for 1/26/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection set for 6/10/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury Trial set for 6/10/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Pretrial Conference set for 5/15/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 10/26/2011) (Entered: 10/28/2011) 11/03/2011 89 NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 65 Amended Complaint [NOTICE OF WITHDRAWAL OF PRAYER FOR INJUNCTIVE RELIEF] (Glackin, Brendan) (Filed on 11/3/2011) (Entered: 11/03/2011) 11/04/2011 90 STATUS REPORT Regarding Voluntary Dismissal of Related Case, Pursuant To The Courts October 26, 2011 Minute Order and Case Management Order (Dkt. 88) by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Lehe, Katherine) (Filed on 11/4/2011) (Entered: 11/04/2011) 11/04/2011 91 OPPOSITION to ( 83 AMENDED MOTION to Dismiss ) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Saveri, Joseph) (Filed on 11/4/2011) Modified text on 11/7/2011 (dhm, COURT STAFF). (Entered: 11/04/2011) 1153 11/04/2011 92 OPPOSITION to ( 79 JOINT MOTION to Dismiss Consolidated Amended Complaint ) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Saveri, Joseph) (Filed on 11/4/2011) Modified text on 11/7/2011 (dhm, COURT STAFF). (Entered: 11/04/2011) 11/04/2011 93 DECLARATION of Dean M. Harvey in Opposition to 79 MOTION to Dismiss Consolidated Amended Complaint filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6 Exhibit F)(Related document(s) 79 ) (Harvey, Dean) (Filed on 11/4/2011) (Entered: 11/04/2011) 11/07/2011 94 Transcript of Proceedings held on 10-27-11, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 2/6/2012. (las, ) (Filed on 11/7/2011) (Entered: 11/07/2011) 11/30/2011 95 STIPULATION Stipulated [Proposed] Protective Order by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 11/30/2011) (Entered: 11/30/2011) 12/01/2011 CLERKS NOTICE: The parties are advised to take notice of the new Standing Order Regarding Motions to File Under Seal in Civil Actions before U.S. District Judge Lucy H. Koh.THIS IS A TEXT ONLY DOCKET ENTRY, THERE IS NO DOCUMENT ASSOCIATED WITH THIS NOTICE (mpb, COURT STAFF) (Filed on 12/1/2011) (Entered: 12/01/2011) 12/01/2011 CLERKS NOTICE: The parties are advised to take notice of the new Standing Order Regarding Motions to File Under Seal in Civil Actions before U.S. District Judge Lucy H. Koh.THIS IS A TEXT ONLY DOCKET ENTRY, THERE IS NO DOCUMENT ASSOCIATED WITH THIS NOTICE. (mpb, COURT STAFF) (Filed on 12/1/2011) (Entered: 12/01/2011) 12/02/2011 96 REPLY (re 83 Amended MOTION to Dismiss ) DEFENDANT LUCASFILM LTD.'S REPLY IN SUPPORT OF MOTION TO DISMISS PLAINTIFFS' CONSOLIDATED AMENDED COMPLAINT filed byLucasfilm Ltd.. (Purcell, Daniel) (Filed on 12/2/2011) (Entered: 12/02/2011) 12/02/2011 97 REPLY (re 79 MOTION to Dismiss Consolidated Amended Complaint ) filed byApple Inc.. (Tubach, Michael) (Filed on 12/2/2011) (Entered: 12/02/2011) 12/05/2011 98 CERTIFICATE OF SERVICE by Apple Inc. re 97 Reply to Opposition/Response (Tubach, Michael) (Filed on 12/5/2011) (Entered: 12/05/2011) 12/05/2011 99 STIPULATION and [Proposed] Order Concerning Testifying Expert Discovery by Intuit Inc.. (Attachments: # 1 Certificate/Proof of Service Proof of Service by U.S. Mail) (Broderick, Catherine) (Filed on 12/5/2011) (Entered: 12/05/2011) 01/05/2012 100 NOTICE by Intuit Inc. of Attorney Name and Email Change (Broderick, Catherine) (Filed on 1/5/2012) (Entered: 01/05/2012) 01/18/2012 101 NOTICE of Appearance by Joshua P. Davis (Davis, Joshua) (Filed on 1/18/2012) (Entered: 01/18/2012) 01/19/2012 102 Administrative Motion to File Under Seal Joint Case Management Conference Statement filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel 1154 Stover. (Attachments: # 1 Exhibit Joint Case Management Conference Statement (Proposed Public Redacted Version))(Harvey, Dean) (Filed on 1/19/2012) (Entered: 01/19/2012) 01/19/2012 103 CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 102 Administrative Motion to File Under Seal Joint Case Management Conference Statement (Harvey, Dean) (Filed on 1/19/2012) (Entered: 01/19/2012) 01/23/2012 104 ORDER Concerning Testifying Expert Discovery. Signed by Judge Lucy H. Koh on 1/23/2012. (lhklc1, COURT STAFF) (Filed on 1/23/2012) (Entered: 01/23/2012) 01/24/2012 105 REQUEST by Apple Inc. to Bring Electronic Equipment into the Courtroom (Attachments: # 1 Proposed Order)(Brown, Christina) (Filed on 1/24/2012) Modified text on 1/25/2012 (dhm, COURT STAFF). (Entered: 01/24/2012) 01/24/2012 106 ORDER Granting 105 Request to Bring Electronic Equipment into the Courtroom, filed by Apple Inc.. Signed by Judge Lucy H. Koh on 1/24/12. (mpb, COURT STAFF) (Filed on 1/24/2012) Modified text on 1/25/2012 (dhm, COURT STAFF). (Entered: 01/24/2012) 01/24/2012 107 STIPULATION AND ORDER (MODIFIED BY THE COURT) re 95 . Signed by Magistrate Judge Howard R. Lloyd on 1/24/12. (hrllc1, COURT STAFF) (Filed on 1/24/2012) (Entered: 01/24/2012) 01/26/2012 108 Minute Entry and Case Management Order: Further Case Management Conference held on 1/26/2012 before Judge Lucy H. Koh (Date Filed: 1/26/2012). Further Case Management Conference set for 4/18/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/26/2012) (Entered: 01/27/2012) 01/26/2012 110 Minute Entry: Motion Hearing held on 1/26/2012 before Judge Lucy H. Koh (Date Filed: 1/26/2012) re 83 Amended MOTION to Dismiss filed by Lucasfilm Ltd., 79 MOTION to Dismiss Consolidated Amended Complaint filed by Apple Inc.. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/26/2012) (Entered: 01/27/2012) 01/27/2012 109 JOINT CASE MANAGEMENT STATEMENT filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 1/27/2012) (Entered: 01/27/2012) 01/30/2012 111 STATUS REPORT PLAINTIFFS STATUS REPORT REGARDING DISMISSAL WITHOUT PREJUDICE OF PRAYER FOR DECLARATORY RELIEF AND CAL. BUS. & PROF. CODE § 16600 CLAIM, PURSUANT TO THE COURTS JANUARY 26, 2012 MINUTE ORDER AND CASE MANAGEMENT ORDER (Dkt. 108) by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Lehe, Katherine) (Filed on 1/30/2012) (Entered: 01/30/2012) 01/31/2012 112 Transcript of Proceedings held on 1-26-12, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 4/30/2012. (las, ) (Filed on 1/31/2012) (Entered: 01/31/2012) 03/23/2012 113 MOTION to Withdraw as Attorney Motion for Leave to Withdraw as Counsel filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Responses due by 4/6/2012. Replies due by 4/13/2012. (Attachments: # 1 Proposed Order) (Lehe, Katherine) (Filed on 3/23/2012) (Entered: 03/23/2012) 03/30/2012 114 STIPULATION re: Production Format of Electronically Stored Information filed by Apple 1155 Inc.. (Brown, Christina) (Filed on 3/30/2012) (Entered: 03/30/2012) 04/11/2012 115 JOINT CASE MANAGEMENT STATEMENT filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 4/11/2012) (Entered: 04/11/2012) 04/17/2012 116 MOTION to Relate Case filed by Google Inc.. (Attachments: # 1 Proposed Order)(Rubin, Lee) (Filed on 4/17/2012) (Entered: 04/17/2012) 04/17/2012 117 Declaration of Lee H. Rubin in Support of 116 MOTION to Relate Case filed byGoogle Inc.. (Attachments: # 1 Exhibit A)(Related document(s) 116 ) (Rubin, Lee) (Filed on 4/17/2012) (Entered: 04/17/2012) 04/17/2012 118 Declaration of Lee H. Rubin in Support of 116 MOTION to Relate Case With Corrected Exhibit A filed byGoogle Inc.. (Attachments: # 1 Exhibit A)(Related document(s) 116 ) (Rubin, Lee) (Filed on 4/17/2012) (Entered: 04/17/2012) 04/18/2012 119 ORDER by Judge Lucy H. Koh granting in part and denying in part (79) Motion to Dismiss; denying (83) Motion to Dismiss in case 5:11-cv-02509-LHK. (lhklc1, COURT STAFF) (Filed on 4/18/2012) (Entered: 04/18/2012) 04/18/2012 120 Minute Entry and Case Management Order: Further Case Management Conference held on 4/18/2012 before Judge Lucy H. Koh (Date Filed: 4/18/2012). Further Case Management Conference set for 5/31/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Christine Bedard.) (mpb, COURT STAFF) (Date Filed: 4/18/2012) (Entered: 04/23/2012) 04/25/2012 121 Order by Hon. Lucy H. Koh granting (116) Motion to Relate Case in case 5:11-cv-02509LHK. Related Case: 5:12-cv-1262-LHK (lhklc1, COURT STAFF) (Filed on 4/25/2012) Modified on 4/26/2012 (dhm, COURT STAFF). (Entered: 04/25/2012) 04/26/2012 122 NOTICE of Substitution of Counsel by Frank H Busch and Sujal J. Shah (Busch, Frank) (Filed on 4/26/2012) (Entered: 04/26/2012) 05/01/2012 123 STIPULATION Extending Time to Answer Consolidated Amended Complaint filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Busch, Frank) (Filed on 5/1/2012) (Entered: 05/01/2012) 05/16/2012 124 NOTICE of Appearance by Richard Martin Heimann (Heimann, Richard) (Filed on 5/16/2012) (Entered: 05/16/2012) 05/16/2012 125 NOTICE of Appearance by Kelly M. Dermody (Dermody, Kelly) (Filed on 5/16/2012) (Entered: 05/16/2012) 05/21/2012 126 ANSWER to Amended Complaint byIntel Corp.. (Pickett, Donn) (Filed on 5/21/2012) (Entered: 05/21/2012) 05/21/2012 127 Defendant Adobe Systems Inc.'s ANSWER to Amended Complaint byAdobe Systems Inc.. (Attachments: # 1 Certificate/Proof of Service)(Kiernan, David) (Filed on 5/21/2012) (Entered: 05/21/2012) 05/21/2012 128 Defendant Intuit Inc's ANSWER to Amended Complaint (Jury Demand) byIntuit Inc.. (Attachments: # 1 Certificate/Proof of Service)(Stewart, Craig) (Filed on 5/21/2012) (Entered: 05/21/2012) 05/21/2012 129 ANSWER to Amended Complaint byPixar. (Henn, Emily) (Filed on 5/21/2012) (Entered: 05/21/2012) 05/21/2012 130 ANSWER to Amended Complaint byLucasfilm Ltd.. (Purcell, Daniel) (Filed on 5/21/2012) (Entered: 05/21/2012) 05/21/2012 131 ANSWER to Amended Complaint byGoogle Inc.. (Rubin, Lee) (Filed on 5/21/2012) 1156 (Entered: 05/21/2012) 05/21/2012 132 ANSWER to Amended Complaint byApple Inc.. (Tubach, Michael) (Filed on 5/21/2012) (Entered: 05/21/2012) 05/22/2012 133 CERTIFICATE OF SERVICE by Apple Inc. re 132 Answer to Amended Complaint (Tubach, Michael) (Filed on 5/22/2012) (Entered: 05/22/2012) 05/23/2012 134 STIPULATION WITH PROPOSED ORDER [Extending Case Management Conference] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 5/23/2012) (Entered: 05/23/2012) 05/24/2012 135 Order by Hon. Lucy H. Koh denying (134) Stipulation in case 5:11-cv-02509LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on 5/24/2012) (Entered: 05/24/2012) 05/24/2012 Set/Reset Hearing re 135 Order on Stipulation, Further Case Management Conference set for 7/25/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT STAFF) (Filed on 5/24/2012) (Entered: 05/24/2012) 05/25/2012 136 ASSOCIATION of Counsel Joseph R. Saveri, Saveri Law Firm by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 5/25/2012) (Entered: 05/25/2012) 05/25/2012 137 MOTION for Extension of Time to File Plaintiffs' Motion for Class Certification Pursuant to Civil Local Rule 6-3 filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 5/25/2012) (Entered: 05/25/2012) 05/25/2012 138 Declaration of Ann B. Shaver in Support of 137 MOTION for Extension of Time to File Plaintiffs' Motion for Class Certification Pursuant to Civil Local Rule 6-3 filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6 Exhibit F, # 7 Exhibit G, # 8 Exhibit H, # 9 Exhibit I, # 10 Exhibit J, # 11 Exhibit K, # 12 Exhibit L, # 13 Exhibit M, # 14 Exhibit N, # 15 Exhibit O, # 16 Exhibit P, # 17 Exhibit Q, # 18 Exhibit R, # 19 Exhibit S, # 20 Exhibit T, # 21 Exhibit U, # 22 Exhibit 1, # 23 Exhibit 2) (Related document(s) 137 ) (Shaver, Anne) (Filed on 5/25/2012) (Entered: 05/25/2012) 05/25/2012 139 Proposed Order re 137 MOTION for Extension of Time to File Plaintiffs' Motion for Class Certification Pursuant to Civil Local Rule 6-3 by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 5/25/2012) (Entered: 05/25/2012) 05/29/2012 140 Order by Hon. Lucy H. Koh denying (137) Motion for Extension of Time to File in case 5:11-cv-02509-LHK. Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on 5/29/2012) (Entered: 05/29/2012) 05/29/2012 Set/Reset Hearing re 140 Order on Motion for Extension of Time to File, Further Case Management Conference set for 6/4/2012 02:30 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT STAFF) (Filed on 5/29/2012) (Entered: 05/29/2012) 05/29/2012 141 Discovery Dispute Joint Report #2 by Apple Inc., Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A)(Tubach, Michael) (Filed on 5/29/2012) Modified text on 5/30/2012 (dhm, COURT STAFF). (Entered: 05/29/2012) 06/01/2012 142 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 6/1/2012) 1157 (Entered: 06/01/2012) 06/01/2012 143 NOTICE of Appearance by Joseph R. Saveri (Saveri, Joseph) (Filed on 6/1/2012) (Entered: 06/01/2012) 06/03/2012 144 UNOPPOSED ADMINISTRATIVE MOTION to Amend Pretrial Order No. 1 filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Responses due by 6/18/2012. Replies due by 6/25/2012. (Attachments: # 1 Exhibit Exhibit A to Motion - [Proposed Order])(Shaver, Anne) (Filed on 6/3/2012) Modified text on 6/4/2012 (dhm, COURT STAFF). (Entered: 06/03/2012) 06/03/2012 145 Declaration of Anne B. Shaver in Support of 144 MOTION to Amend/Correct Plaintiffs Unopposed Administrative Motion to Amend Pretrial Order No. 1 filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A to Shaver Declaration - Firm Resume)(Related document(s) 144 ) (Shaver, Anne) (Filed on 6/3/2012) (Entered: 06/03/2012) 06/03/2012 146 Declaration of Joseph R. Saveri in Support of 144 MOTION to Amend/Correct Plaintiffs Unopposed Administrative Motion to Amend Pretrial Order No. 1 filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Related document(s) 144 ) (Shaver, Anne) (Filed on 6/3/2012) (Entered: 06/03/2012) 06/04/2012 147 Order by Hon. Lucy H. Koh granting (144) Motion to Amend/Correct. Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on 6/4/2012) (Entered: 06/04/2012) 06/04/2012 149 Minute Entry: Further Case Management Conference held on 6/4/2012 before Judge Lucy H. Koh (Date Filed: 6/4/2012). Further Case Management Conference set for 9/12/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 6/4/2012) (Entered: 06/05/2012) 06/05/2012 148 Case Management Order; Referral of Discovery; Further Case Management Order. *** Counsel is advised that this Order contains new dates in addition to the dates discussed at the June 4, 2012 Case Management Conference.*** . Signed by Judge Lucy H. Koh on 6/5/2012. (lhklc1, COURT STAFF) (Filed on 6/5/2012) (Entered: 06/05/2012) 06/12/2012 Pursuant to Signed Order ( 148 ). Case Reassigned to Magistrate Judge Paul Singh Grewal for all further discovery disputes. Magistrate Judge Howard R. Lloyd no longer assigned to the case. (tsh, COURT STAFF) (Filed on 6/12/2012) (Entered: 06/12/2012) 06/14/2012 150 NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover of withdrawal of Attorney John Radice (Nussbaum, Linda) (Filed on 6/14/2012) (Entered: 06/14/2012) 06/14/2012 151 STIPULATION WITH PROPOSED ORDER Regarding Amending Answers and Affirmative Defenses filed by Pixar. (Henn, Emily) (Filed on 6/14/2012) (Entered: 06/14/2012) 06/15/2012 152 Stipulation and Order Regarding Amending Answers and Affirmative Defenses by Hon. Lucy H. Koh granting (151) Stipulation in case 5:11-cv-02509-LHK. Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11cv-03541-LHK, 5:12-cv-01262-LHK (lhklc1, COURT STAFF) (Filed on 6/15/2012) Modified text on 6/18/2012 (dhm, COURT STAFF). (Entered: 06/15/2012) 06/18/2012 153 NOTICE of Compliance with the Courts June 5, 2012 Case Management Order by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover (Attachments: # 1 Declaration of Dean M. Harvey Regarding Plaintiffs Compliance with the Courts June 5, 2012 Case Management Order, # 2 Declaration of Joseph R. Saveri Regarding Compliance with the Courts June 5, 2012 Case Management Order)(Harvey, Dean) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 1158 06/18/2012 154 Declaration of Eric B. Evans regarding Compliance with 148 June 5, 2012 Case Management Order by Google Inc.. (Evans, Eric) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/18/2012 155 Declaration of Catherine T. Zeng re 148 Order Regarding Defendant Intuit Inc.'s Production of Data and Documents by Intuit Inc.. (Zeng, Catherine) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/18/2012 156 Declaration of David C. Kiernan re 148 Order Regarding Defendant Adobe Systems Incorporateds Production of Data and Documents by Adobe Systems Inc.. (Kiernan, David) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/18/2012 157 Declaration of Jonathan Herczeg re 148 Order Regarding Pixar's Production of Documents and Data by Pixar. (Henn, Emily) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/18/2012 158 Declaration of Frank M. Hinman re 148 Order Regarding Intel's Production of Data and Documents by Intel Corp.. (Hinman, Frank) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/18/2012 159 Declaration of Christina Brown re 148 Order Regarding Apple Inc.'s Document and Data Productions by Apple Inc.. (Brown, Christina) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/18/2012 160 Declaration of Justina K. Sessions re 148 Regarding Lucasfilm's Document and Data Production filed by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 6/18/2012) Modified on 6/19/2012 linking entry to entry #148 (dhm, COURT STAFF). (Entered: 06/18/2012) 06/21/2012 161 MOTION for leave to appear in Pro Hac Vice of Peter A. Barile III ( Filing fee $ 305, receipt number 0971-6911874.) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order)(Barile, Peter) (Filed on 6/21/2012) (Entered: 06/21/2012) 07/02/2012 162 STATUS REPORT REGARDING REVIEW OF DOCUMENTS AND DATA by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A)(Dermody, Kelly) (Filed on 7/2/2012) (Entered: 07/02/2012) 07/02/2012 163 Order by Hon. Lucy H. Koh granting 161 Motion for Pro Hac Vice.(lhklc1, COURT STAFF) (Filed on 7/2/2012) (Entered: 07/02/2012) 07/02/2012 164 ORDER re Discovery. Signed by Judge Lucy H. Koh on 6/28/2012. (lhklc1, COURT STAFF) (Filed on 7/2/2012) (Entered: 07/02/2012) 07/02/2012 165 ORDER re Case Schedule. Signed by Judge Lucy H. Koh on 7/2/2012. (lhklc1, COURT STAFF) (Filed on 7/2/2012) (Entered: 07/02/2012) 07/03/2012 166 NOTICE of Appearance by Kevin Edward Rayhill (Rayhill, Kevin) (Filed on 7/3/2012) (Entered: 07/03/2012) 07/05/2012 167 NOTICE of Appearance by Lisa Jennifer Leebove (Leebove, Lisa) (Filed on 7/5/2012) (Entered: 07/05/2012) 07/05/2012 168 AMENDED ANSWER to 65 Consolidated Amended Complaint byLucasfilm Ltd.. (Purcell, Daniel) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/05/2012 169 Amended ANSWER to 65 Amended Complaint byIntel Corp.. (Pickett, Donn) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/05/2012 170 AMENDED ANSWER to 65 AMENDED COMPLAINT byAdobe Systems Inc.. (Kiernan, 1159 David) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/05/2012 171 AMENDED ANSWER to Plaintiffs' 65 Consolidated Amended Complaint byIntuit Inc.. (Zeng, Catherine) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/05/2012 172 AMENDED ANSWER to 65 Amended Complaint byPixar. (Henn, Emily) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/05/2012 173 AMENDED ANSWER to 65 Amended Complaint byGoogle Inc.. (Rubin, Lee) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/05/2012 174 AMENDED ANSWER to Plaintiffs' 65 Consolidated Amended Complaint byApple Inc.. (Tubach, Michael) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012) 07/09/2012 175 STIPULATION WITH PROPOSED ORDER AMENDING CASE SCHEDULE filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 7/9/2012) (Entered: 07/09/2012) 07/10/2012 176 Order by Hon. Lucy H. Koh granting (175) Stipulation in case 5:11-cv-02509-LHK. Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on 7/10/2012) (Entered: 07/10/2012) 07/10/2012 Set Deadlines/Hearings: Fact Discovery Cutoff 1/29/13; Expert Discovery Cutoff 3/26/2013. Final Pretrial Conference set for 7/31/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection set for 8/27/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury Trial set for 8/27/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 7/10/2012) (Entered: 07/18/2012) 07/10/2012 Set/Reset Hearing re 176 Order on Stipulation, Hearing re Class Certification Motion set for 12/13/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 7/10/2012) (Entered: 08/28/2012) 07/19/2012 177 CLERKS NOTICE AMENDING TRIAL SCHEDULE (CHANGING DATE FOR COMMENCEMENT OF TRIAL) Jury Selection set for 8/26/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury Trial set for 8/26/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 7/19/2012) (Entered: 07/19/2012) 07/23/2012 178 ORDER to Show Cause Why Case No. 5:12-CV-01262-LHK Should Not Be Dismissed for Failure to Prosecute. Signed by Judge Lucy H. Koh on 7/23/2012. (lhklc1S, COURT STAFF) (Filed on 7/23/2012) Modified on 7/23/2012 (lhklc1S, COURT STAFF). (Entered: 07/23/2012) 09/06/2012 179 JOINT CASE MANAGEMENT STATEMENT filed by Michael Devine. (Leebove, Lisa) (Filed on 9/6/2012) (Entered: 09/06/2012) 09/06/2012 180 NOTICE of Appearance by Joseph Peter Forderer (Forderer, Joseph) (Filed on 9/6/2012) (Entered: 09/06/2012) 09/11/2012 181 CASE MANAGEMENT STATEMENT (SUPPLEMENTAL) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Dermody, Kelly) (Filed on 9/11/2012) (Entered: 09/11/2012) 09/12/2012 182 RESPONSE to 181 Plaintiffs' Supplemental Case Management Statement by Google Inc.. (Rubin, Lee) (Filed on 9/12/2012) Modified text on 9/13/2012 (dhmS, COURT STAFF). (Entered: 09/12/2012) 1160 09/12/2012 183 09/12/2012 Minute Entry and Case Management Order: Further Case Management Conference held on 9/12/2012 before Judge Lucy H. Koh (Date Filed: 9/12/2012). Final Pretrial Conference set for 10/31/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection set for 11/12/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury Trial set for 11/12/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Motion Hearing set for 1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 9/12/2012) (Entered: 09/13/2012) Set/Reset Hearing re 183 Case Management Conference - Further, Set Hearings (Inadvertently not calendared when Case Management Order was docketed) Further Case Management Conference set for 12/12/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT STAFF) (Filed on 9/12/2012) (Entered: 10/16/2012) 09/18/2012 184 Transcript of Proceedings held on 09-12-12, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 12/17/2012. (las, ) (Filed on 9/18/2012) (Entered: 09/18/2012) 09/19/2012 185 NOTICE of Appearance by James Gerard Beebe Dallal (Dallal, James) (Filed on 9/19/2012) (Entered: 09/19/2012) 10/01/2012 186 Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Joseph P. Forderer, # 2 Proposed Order, # 3 Exhibit Class Certification Brief (Redacted), # 4 Exhibit Colligan Declaration (Redacted), # 5 Exhibit Expert Report (Redacted), # 6 Exhibit Exhibits to Shaver Declaration (Redacted), # 7 Exhibit Exhibits to Colligan Declaration (Redacted)) (Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012) 10/01/2012 187 MOTION to Certify Class and Memorandum of Points and Authorities filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion Hearing set for 1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 11/12/2012. Replies due by 12/10/2012. (Attachments: # 1 Proposed Order)(Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012) 10/01/2012 188 Declaration of Ann B. Shaver in Support of 187 MOTION to Certify Class and Memorandum of Points and Authorities filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 6, # 2 Exhibit 7, # 3 Exhibit 8, # 4 Exhibit 9, # 5 Exhibit 10, # 6 Exhibit 1-5, 11-55, 58-68, and 70, # 7 Exhibit 56, # 8 Exhibit 57, # 9 Exhibit 69, # 10 Exhibit 71)(Related document(s) 187 ) (Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012) 10/01/2012 189 Declaration of Edward Colligan in Support of 187 MOTION to Certify Class and Memorandum of Points and Authorities filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A & B)(Related document(s) 187 ) (Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012) 10/01/2012 190 Declaration of Edward E. Leamer, Ph.D. in Support of 187 MOTION to Certify Class and Memorandum of Points and Authorities filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3)(Related document(s) 187 ) (Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012) 10/01/2012 191 CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 188 Declaration in Support,, 189 Declaration in Support, 1161 186 Administrative Motion to File Under Seal , 190 Declaration in Support, 187 MOTION to Certify Class and Memorandum of Points and Authorities (Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012) 10/08/2012 192 Declaration of Robert Booth In Support of Plaintiffs' Administrative Motion to File Under Seal filed byPalm Inc.. (Smith, Benjamin) (Filed on 10/8/2012) (Entered: 10/08/2012) 10/08/2012 193 Proposed Order re 192 Declaration in Support of Granting Plaintiffs' Administrative Motion to File Under Seal by Palm Inc.. (Smith, Benjamin) (Filed on 10/8/2012) (Entered: 10/08/2012) 10/08/2012 194 MOTION to Withdraw as Attorney Jonathan Herczeg filed by Pixar. Responses due by 10/22/2012. Replies due by 10/29/2012. (Attachments: # 1 Proposed Order)(Henn, Emily) (Filed on 10/8/2012) (Entered: 10/08/2012) 10/09/2012 195 Defendants' Joint Response to 186 Plaintiffs' Administrative Motion to Seal filed by Adobe Systems Inc., Apple Inc., Lucasfilm Ltd., Intuit Inc., Google Inc., Intel Corp., Pixar. (Attachments: # 1 Exhibit A)(Kiernan, David) (Filed on 10/9/2012) Modified on 10/10/2012 counsel posted document incorrectly as a motion and failed to link entry to document #186 (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 196 Declaration of Donna Morris in Support of 195 Joint Response to Plaintiffs' Administrative Motion to Seal filed byAdobe Systems Inc.. (Related document(s) 195 ) (Kiernan, David) (Filed on 10/9/2012) Modified text on 10/10/2012 (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 197 Declaration of Lisa Borgeson in Support of 186 Plaintiffs' Administrative Motion to File Under Seal filed byIntuit Inc.. (Related document(s) 195 ) (Kiernan, David) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 198 Proposed Order Granting 186 Plaintiffs' Administrative Motion to File Under Seal by Adobe Systems Inc.. (Attachments: # 1 Exhibit A (Plaintiffs Notice of Motion and Motion for Class Cert_Proposed Redactions), # 2 Exhibit B (Expert Report of Edward E. Leamer, Ph.D. With Proposed Redactions), # 3 Exhibit C (Exhibits With Proposed Redactions))(Kiernan, David) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 199 Declaration of DAVID J. ANDERMAN in Support of 195 Joint Response to Plaintiffs' Administrative Motion to Seal filed by Lucasfilm Ltd.. (Related document(s) 195 ) (Purcell, Daniel) (Filed on 10/9/2012) Modified text on 10/10/2012 (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 200 Declaration of Alan Eustace in Support of 195 Administrative Motion to File Under Seal filed by Google Inc.. (Related document(s) 195 ) (Evans, Eric) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 201 Declaration of Frank Wagner in Support of 195 Administrative Motion to File Under Seal filed by Google Inc.. (Related document(s) 195 ) (Evans, Eric) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 202 Declaration of James M. Kennedy Pursuant to Civil Local Rule 79-5(d) Submitted in Support of 195 Plaintiffs' Administrative Motion to File Under Seal filed by Pixar. (Related document (s) 195 ) (Henn, Emily) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 203 Declaration of Tina M. Evangelista in Support of 195 Plaintiffs' Administrative Motion to File Under Seal Plaintiffs' Notice of Motion and Motion for Class Certification and Memorandum of Law in Support filed by Intel Corp.. (Related document(s) 195 ) (Busch, 1162 Frank) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/09/2012 204 Declaration of Mark Bentley Pursuant to Civil Local Rule 79-5(d) in Support of 195 Administrative Motion to File Under Seal filed by Apple Inc.. (Related document(s) 195 ) (Brown, Christina) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012) 10/10/2012 205 MOTION for leave to appear in Pro Hac Vice Chinue T. Richardson ( Filing fee $ 305, receipt number 0971-7189136.) filed by Pixar. (Attachments: # 1 Certificate/Proof of Service Certificate of Good Standing)(Richardson, Chinue) (Filed on 10/10/2012) (Entered: 10/10/2012) 10/11/2012 206 Order by Hon. Lucy H. Koh granting 205 Motion for Pro Hac Vice.(lhklc1, COURT STAFF) (Filed on 10/11/2012) (Entered: 10/11/2012) 10/16/2012 207 MOTION for leave to appear in Pro Hac Vice Thomas A. Isaacson ( Filing fee $ 305, receipt number 0971-7203150.) filed by Pixar. (Attachments: # 1 Certificate/Proof of Service Certificate of Good Standing)(Isaacson, Thomas) (Filed on 10/16/2012) (Entered: 10/16/2012) 10/17/2012 208 Order by Hon. Lucy H. Koh granting (207) Motion for Pro Hac Vice in case 5:11-cv-02509LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK(lhklc3, COURT STAFF) (Filed on 10/17/2012) (Entered: 10/17/2012) 11/12/2012 209 OPPOSITION to ( 187 MOTION for Class Certification ) filed by Apple Inc.. (Tubach, Michael) (Filed on 11/12/2012) Modified text on 11/13/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012) 11/12/2012 210 MOTION to Strike the Report of Dr. Edward E. Leamer filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. Motion Hearing set for 1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 11/26/2012. Replies due by 12/3/2012. (Attachments: # 1 Declaration of Susan J. Welch, # 2 Exhibit)(Hinman, Frank) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 211 Administrative Motion to File Under Seal filed by Adobe Systems Inc.. (Kiernan, David) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 212 *** FILED IN ERROR. DOCUMENT LOCKED. PLEASE SEE DOCKET # 230 . *** Expert Report of Prefessor Kevin M. Murphy in Support of 209 Opposition/Response to Motion for Class Certification filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Related document(s) 209 ) (Hinman, Frank) (Filed on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). Modified on 11/14/2012 (wv, COURT STAFF). (Entered: 11/12/2012) 11/12/2012 213 MOTION for an Evidentiary Hearing on Class Certification Issues filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Purcell, Daniel) (Filed on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012) 11/12/2012 214 Declaration of Catherine T. Zeng in Support of 211 joint Administrative Motion to File Under Seal filed by Intuit Inc.. (Related document(s) 211 ) (Zeng, Catherine) (Filed on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012) 11/12/2012 215 Declaration of Christina J. Brown in Support of 209 Opposition to Motion for Class Certification filed by Apple Inc. PUBLIC REDACTED VERSION. (Attachments: # 1 Ex. 16, # 2 Ex. 7, # 3 Ex. 8-15, # 4 Ex. 16, # 5 Ex. 17, # 6 Ex. 18, # 7 Ex. 19-22, # 8 Ex. 23, # 9 Ex. 24, # 10 Ex. 25-27)(Related document(s) 209 ) (Brown, Christina) (Filed on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012) 1163 11/12/2012 216 Proposed Order re 213 ADMINISTRATIVE MOTION for an Evidentiary Hearing on Class Certification Issues by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Purcell, Daniel) (Filed on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012) 11/12/2012 217 Declaration of Lin W. Kahn in Support of 211 Administrative Motion to File Under Seal filed byAdobe Systems Inc.. (Related document(s) 211 ) (Mittelstaedt, Robert) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 218 Declaration of James M. Kennedy in Support of 211 Administrative Motion to File Under Seal filed byPixar. (Related document(s) 211 ) (Henn, Emily) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 219 Declaration of Justina K. Sessions in Support of 211 Administrative Motion to File Under Seal filed byLucasfilm Ltd.. (Related document(s) 211 ) (Sessions, Justina) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 220 Declaration of Frank Busch in Support of 211 Administrative Motion to File Under Seal filed byIntel Corp.. (Related document(s) 211 ) (Busch, Frank) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 221 Declaration of Frank Wagner in Support of 211 Administrative Motion to File Under Seal filed byGoogle Inc.. (Related document(s) 211 ) (Evans, Eric) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 222 Declaration of Christina J. Brown in Support of 211 Administrative Motion to File Under Seal filed byApple Inc.. (Related document(s) 211 ) (Brown, Christina) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/12/2012 223 EXHIBITS re 211 Administrative Motion to File Under Seal filed byAdobe Systems Inc.. (Attachments: # 1 Exhibit A (Opp), # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E)(Related document(s) 211 ) (Kiernan, David) (Filed on 11/12/2012) (Entered: 11/12/2012) 11/13/2012 224 Proposed Order re 211 Administrative Motion to File Under Seal by Adobe Systems Inc.. (Kiernan, David) (Filed on 11/13/2012) (Entered: 11/13/2012) 11/13/2012 225 Proposed Order re 210 MOTION to Strike the Report of Dr. Edward E. Leamer by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Busch, Frank) (Filed on 11/13/2012) (Entered: 11/13/2012) 11/13/2012 226 Transcript of Proceedings held on 06-04-12, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 2/11/2013. (las, ) (Filed on 11/13/2012) (Entered: 11/13/2012) 11/13/2012 227 CERTIFICATE OF SERVICE by Intel Corp. re 212 Declaration in Support, 210 MOTION to Strike the Report of Dr. Edward E. Leamer, 215 Declaration in Support, (Busch, Frank) (Filed on 11/13/2012) (Entered: 11/13/2012) 11/13/2012 228 CERTIFICATE OF SERVICE by Apple Inc. re 209 Opposition/Response to Motion, 215 Declaration in Support, (Brown, Christina) (Filed on 11/13/2012) (Entered: 11/13/2012) 11/14/2012 229 Proposed Order re 224 Proposed Order Revised Proposed Order re 211 Administrative Motion to File Under Seal by Adobe Systems Inc.. (Kiernan, David) (Filed on 11/14/2012) (Entered: 11/14/2012) 11/14/2012 230 Expert Report of Professor Kevin M. Murphy in Support of 209 Opposition/Response to 1164 Motion CORRECTION OF DOCKET # 212 , filed byAdobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Related document(s) 209 ) (Hinman, Frank) (Filed on 11/14/2012) Modified text on 11/19/2012 (dhmS, COURT STAFF). (Entered: 11/14/2012) 11/15/2012 231 NOTICE of Appearance Google Inc. (Rubin, Lee) (Filed on 11/15/2012) (Entered: 11/15/2012) 11/15/2012 232 MOTION Administrative Motion for Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Responses due by 11/29/2012. Replies due by 12/6/2012. (Shaver, Anne) (Filed on 11/15/2012) (Entered: 11/15/2012) 11/15/2012 233 Declaration of Brendan P. Glackin in Support of 232 MOTION Administrative Motion for Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A , # 2 Exhibit B)(Related document(s) 232 ) (Shaver, Anne) (Filed on 11/15/2012) Modified on 11/16/2012 (ewn, COURT STAFF). Modified on 11/16/2012 (ewn, COURT STAFF). Modified on 11/28/2012 PURSUANT TO ORDER (DOC. #242) THE GLACKIN DECLARATION IS PERMANENTLY LOCKED (dhmS, COURT STAFF). (Entered: 11/15/2012) 11/15/2012 234 Proposed Order re 232 MOTION Administrative Motion for Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 11/15/2012) (Entered: 11/15/2012) 11/16/2012 235 MOTION to Remove Incorrectly Filed Document filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order) (Glackin, Brendan) (Filed on 11/16/2012) (Entered: 11/16/2012) 11/16/2012 236 Amended Declaration of Brendan P. Glackin in Support of 232 MOTION Administrative Motion for Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4 (c)(2) CORRECTION OF DOCKET # 233 . filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B)(Related document(s) 232 ) (Glackin, Brendan) (Filed on 11/16/2012) Modified text on 11/19/2012 (dhmS, COURT STAFF). (Entered: 11/16/2012) 11/16/2012 237 OPPOSITION to ( 213 MOTION for an Evidentiary Hearing on Class Certification Issues ) filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order Denying Defendants' Administrative Motion) (Glackin, Brendan) (Filed on 11/16/2012) Modified text on 11/19/2012 (dhmS, COURT STAFF). (Entered: 11/16/2012) 11/19/2012 238 OPPOSITION to ( 232 MOTION Administrative Motion for Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) ) filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Proposed Order)(Hinman, Frank) (Filed on 11/19/2012) Modified text on 11/20/2012 (dhmS, COURT STAFF). (Entered: 11/19/2012) 11/19/2012 239 Declaration of Frank M. Hinman in Support of 238 Opposition to Motion, filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit A-E)(Related document(s) 238 ) (Hinman, Frank) (Filed on 11/19/2012) Modified text on 11/20/2012 (dhmS, COURT STAFF). (Entered: 11/19/2012) 11/19/2012 240 Declaration of JOSEPH P. FORDERER in Support of 211 Administrative Motion to File Under Seal AS TO INFORMATION DESIGNATED CONFIDENTIAL BY PLAINTIFFS filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Related document(s) 211 ) (Forderer, Joseph) (Filed on 11/19/2012) (Entered: 11/19/2012) 1165 11/19/2012 241 Proposed Order re 240 Declaration in Support, 211 Administrative Motion to File Under Seal AS TO INFORMATION DESIGNATED CONFIDENTIAL BY PLAINTIFFS by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A (Opposition to Plaintiffs Motion for Class Certification: Plaintiffs Proposed Redactions), # 2 Exhibit B (Exhibits to the Declaration of Christina Brown: Plaintiffs Proposed Redactions), # 3 Exhibit C (Exhibits to the Declaration of Susan J. Welch: Plaintiffs Proposed Redactions))(Forderer, Joseph) (Filed on 11/19/2012) (Entered: 11/19/2012) 11/21/2012 242 ORDER by Judge Lucy H. Koh denying (213) Motion for Hearing; granting in part and denying in part (232) Motion ; granting (235) Motion to Remove Incorrectly Filed Document in case 5:11-cv-02509-LHK (lhklc1, COURT STAFF) (Filed on 11/21/2012) (Entered: 11/21/2012) 11/21/2012 243 Order by Hon. Lucy H. Koh granting 194 Motion to Withdraw as Attorney. Attorney Jonathan A D Herczeg terminated.(lhklc1, COURT STAFF) (Filed on 11/21/2012) (Entered: 11/21/2012) 11/26/2012 244 Order by Hon. Lucy H. Koh granting 113 Motion to Withdraw as Attorney Katerine M Lehe. (lhklc1, COURT STAFF) (Filed on 11/26/2012) (Entered: 11/26/2012) 12/05/2012 245 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Palm Inc., Pixar, Daniel Stover. (Shaver, Anne) (Filed on 12/5/2012) (Entered: 12/05/2012) 12/10/2012 246 Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Anne Shaver, # 2 Proposed Order, # 3 Exhibit Redacted Reply Class Certification, # 4 Exhibit Redacted Reply Report Edward Leamer, # 5 Exhibit Exhibits Under Seal)(Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012) 12/10/2012 247 REPLY (re 187 MOTION to Certify Class and Memorandum of Points and Authorities, 210 MOTION to Strike the Report of Dr. Edward E. Leamer ) filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012) 12/10/2012 248 Declaration of Dean M. Harvey in Support of 247 Reply to Opposition/Response, filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit Exhibits Filed Under Seal, # 2 Exhibit 7, # 3 Exhibit 8, # 4 Exhibit 9, # 5 Exhibit 10, # 6 Exhibit 11, # 7 Exhibit 31, # 8 Exhibit 32, # 9 Exhibit 33, # 10 Exhibit 34)(Related document(s) 247 ) (Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012) 12/10/2012 249 Declaration of Edward E. Leamer in Support of 247 Reply to Opposition/Response, filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Related document(s) 247 ) (Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012) 12/10/2012 250 CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 247 Reply to Opposition/Response, (Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012) 12/11/2012 251 CLERKS NOTICE CONTINUING FURTHER CASE MANAGEMENT CONFERENCE TO DATE OF MOTION HEARING Further Case Management Conference set for 1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose. ****THIS IS A TEXT-ONLY ENTRY. THERE IS NO DOCUMENT ASSOCIATED WITH THIS DOCKET ENTRY**** (mpb, COURT STAFF) (Filed on 12/11/2012) (Entered: 12/11/2012) 12/12/2012 252 Administrative Motion to File Under Seal LETTER RE CORRECTION TO CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND IN OPPOSITION TO DEFENDANTS MOTION TO STRIKE THE REPORT OF DR. 1166 EDWARD E. LEAMER, AND REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D. filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order, # 2 Exhibit Redacted Letter)(Harvey, Dean) (Filed on 12/12/2012) (Entered: 12/12/2012) 12/12/2012 253 Letter from Brendan P. Glackin RE CORRECTION TO CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND IN OPPOSITION TO DEFENDANTS MOTION TO STRIKE THE REPORT OF DR. EDWARD E. LEAMER, AND REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D.. (Harvey, Dean) (Filed on 12/12/2012) (Entered: 12/12/2012) 12/17/2012 254 Joint Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Appendix Appendix A, # 2 Exhibit Exhibits A-C, # 3 Proposed Order)(Evans, Eric) (Filed on 12/17/2012) (Entered: 12/17/2012) 12/17/2012 255 Declaration of Susan J. Welch in Support of 254 Joint Administrative Motion to File Under Seal filed byIntel Corp.. (Related document(s) 254 ) (Welch, Susan) (Filed on 12/17/2012) (Entered: 12/17/2012) 12/17/2012 256 Declaration of Catherine T. Zeng in Support of 254 Joint Administrative Motion to File Under Seal filed byIntuit Inc.. (Related document(s) 254 ) (Zeng, Catherine) (Filed on 12/17/2012) (Entered: 12/17/2012) 12/17/2012 257 Declaration of Lin W. Kahn in Support of 254 Joint Administrative Motion to File Under Seal filed byAdobe Systems Inc.. (Related document(s) 254 ) (Wang, Lin) (Filed on 12/17/2012) (Entered: 12/17/2012) 12/17/2012 258 Declaration of Christina Brown in Support of 254 Joint Administrative Motion to File Under Seal filed byApple Inc.. (Related document(s) 254 ) (Brown, Christina) (Filed on 12/17/2012) (Entered: 12/17/2012) 12/17/2012 259 Declaration of James M. Kennedy in Support of 254 Joint Administrative Motion to File Under Seal filed byPixar. (Related document(s) 254 ) (Richardson, Chinue) (Filed on 12/17/2012) (Entered: 12/17/2012) 12/18/2012 260 Declaration of Justina K. Sessions in Support of 254 Joint Administrative Motion to File Under Seal filed byLucasfilm Ltd.. (Related document(s) 254 ) (Sessions, Justina) (Filed on 12/18/2012) (Entered: 12/18/2012) 12/18/2012 261 Declaration of Frank Wagner in Support of 254 Joint Administrative Motion to File Under Seal filed byGoogle Inc.. (Related document(s) 254 ) (Selin, Anne) (Filed on 12/18/2012) (Entered: 12/18/2012) 01/09/2013 262 NOTICE of Change of Address by James Gerard Beebe Dallal for Joseph Saveri Law Firm (Dallal, James) (Filed on 1/9/2013) (Entered: 01/09/2013) 01/09/2013 263 JOINT ADMINISTRATIVE MOTION for Leave to Supplement the Record in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification; Declaration of Eric B. Evans; Supplemental Declaration of Kevin Murphy; Proposed Order filed by Google Inc.. (Attachments: # 1 Declaration of Eric B. Evans, # 2 Exhibit A to Evans Decl., # 3 Declaration of Kevin Murphy, # 4 Proposed Order)(Evans, Eric) (Filed on 1/9/2013) Modified text on 1/10/2013 (dhmS, COURT STAFF). (Entered: 01/09/2013) 01/09/2013 264 Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Exhibit A to Administrative Motion to Seal, # 2 Exhibit B to Administrative Motion to Seal, # 3 Exhibit C to Administrative Motion to Seal, # 4 Declaration of Anne Selin, # 5 Proposed Order) (Evans, Eric) (Filed on 1/9/2013) (Entered: 01/09/2013) 01/09/2013 265 Declaration of Frank Busch in Support of 264 Administrative Motion to File Under Seal filed byIntel Corp.. (Related document(s) 264 ) (Busch, Frank) (Filed on 1/9/2013) (Entered: 1167 01/09/2013) 01/09/2013 266 Declaration of Christina Brown in Support of 264 Administrative Motion to File Under Seal filed byApple Inc.. (Related document(s) 264 ) (Brown, Christina) (Filed on 1/9/2013) (Entered: 01/09/2013) 01/10/2013 267 NOTICE of Appearance by Lisa Janine Cisneros (Cisneros, Lisa) (Filed on 1/10/2013) (Entered: 01/10/2013) 01/10/2013 268 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 1/10/2013) (Entered: 01/10/2013) 01/11/2013 269 ORDER Re: Motions to Seal. Signed by Judge Lucy H. Koh on 1/11/2013. (lhklc3, COURT STAFF) (Filed on 1/11/2013) (Entered: 01/11/2013) 01/14/2013 270 OPPOSITION to ( 263 JOINT ADMINISTRATIVE MOTION for Leave to Supplement the Record in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification ) and ( 210 MOTION to Strike the Report of Dr. Edward E. Leamer ) [REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Dr. Edward E. Leamer in Opposition to Defendants' Administrative Motion)(Harvey, Dean) (Filed on 1/14/2013) Modified text on 1/16/2013 (dhmS, COURT STAFF). (Entered: 01/14/2013) 01/14/2013 271 Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A [Plaintiffs' Opposition to Defendants' Administrative Motion - Redacted], # 2 Exhibit B [Declaration of Dr. Edward E. Leamer in Opposition to Defendants' Administrative Motion - Redacted], # 3 Exhibit C [Plaintiffs' Opposition to Defendants' Administrative Motion - Redactions Highlighted], # 4 Exhibit D [Declaration of Dr. Edward E. Leamer in Opposition to Defendants' Administrative Motion - Redactions Highlighted])(Harvey, Dean) (Filed on 1/14/2013) (Entered: 01/14/2013) 01/15/2013 272 NOTICE by Intuit Inc. of Request to Bring Electronic Equipment into the Courtroom (Attachments: # 1 Proposed Order)(Zeng, Catherine) (Filed on 1/15/2013) Modified on 1/16/2013 COUNSEL POSTED DOCUMENT INCORRECTLY AS A NOTICE (dhmS, COURT STAFF). (Entered: 01/15/2013) 01/15/2013 273 ORDER by Judge Lucy H. Koh granting in part and denying in part (186) Administrative Motion to File Under Seal Documents Related to Plaintiffs' Motion for Class Certification; granting in part and denying in part (211) Administrative Motion to File Under Seal Documents Related to Defendants' Opposition to Class Certification; granting in part and denying in part (246) Administrative Motion to File Under Seal Documents Related to Plaintiffs' Consolidated Reply in Support of its Motion for Class Certification and Opposition to Defendants' Motion to Strike; granting (252) Administrative Motion to File Under Seal Portion of Glackin Letter; granting in part and denying in part (254) Defendants' Joint Administrative Motion to File Under Seal in case 5:11-cv-02509-LHK (lhklc3, COURT STAFF) (Filed on 1/15/2013) (Entered: 01/15/2013) 01/16/2013 274 ERRATA re 215 Declaration in Support, by Apple Inc.. (Brown, Christina) (Filed on 1/16/2013) (Entered: 01/16/2013) 01/16/2013 275 CLERKS NOTICE re Deficiency (dhmS, COURT STAFF) (Filed on 1/16/2013) (Entered: 01/16/2013) 01/16/2013 276 ERRATA re 222 Declaration in Support, 221 Declaration in Support of Joint Administrative Motion to Seal dated Nov. 12, 2012 by Google Inc.. (Selin, Anne) (Filed on 1/16/2013) (Entered: 01/16/2013) 01/16/2013 277 ORDER TO BRING EQUIPMENT INTO COURTROOM re 272 Notice (Other), filed by Intuit Inc.. Signed by Judge Lucy H. Koh on 1/16/13. (mpb, COURT STAFF) (Filed on 1168 1/16/2013) (Entered: 01/16/2013) 01/16/2013 278 MOTION to Compel Google Documents [REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion Hearing set for 2/26/2013 10:00 AM in Courtroom 5, 4th Floor, San Jose before Magistrate Judge Paul Singh Grewal. Responses due by 1/30/2013. Replies due by 2/6/2013. (Attachments: # 1 Declaration of Dean M. Harvey in Support of Plaintiffs Motion to Compel and Plaintiffs Motion to Shorten Time, Exhibits A-O [REDACTED], # 2 Proposed Order Granting Plaintiffs' Motion to Compel Google Documents)(Harvey, Dean) (Filed on 1/16/2013) (Entered: 01/16/2013) 01/16/2013 279 Administrative Motion to File Under Seal , Pursuant to Civil Local Rule 79-5(d), Portions of Plaintiffs' Motion to Compel Google Documents and the Declaration of Dean M. Harvey in Support Thereof filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A: Plaintiffs' Motion to Compel Google Documents [Redacted], # 2 Exhibit B: Declaration of Dean M. Harvey in Support Thereof with Exhibits A-O [Redacted], # 3 Exhibit C: Highlighted Version of Plaintiffs' Motion To Compel Google Documents, # 4 Exhibit D: Declaration of Dean M. Harvey in Support Thereof)(Harvey, Dean) (Filed on 1/16/2013) (Entered: 01/16/2013) 01/16/2013 280 MOTION to Shorten Time on Plaintiffs' Motion to Compel filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order Granting Plaintiffs' Motion to Shorten Time on Plaintiffs' Motion to Compel)(Harvey, Dean) (Filed on 1/16/2013) (Entered: 01/16/2013) 01/17/2013 281 Minute Entry: Motion Hearing held on 1/17/2013 before Judge Lucy H. Koh (Date Filed: 1/17/2013) re 187 MOTION to Certify Class and Memorandum of Points and Authorities filed by Michael Devine, Siddharth Hariharan, Mark Fichtner, Daniel Stover, Brandon Marshall. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/17/2013) (Entered: 01/22/2013) 01/17/2013 282 Minute Entry and Case Management Order: Further Case Management Conference held on 1/17/2013 before Judge Lucy H. Koh (Date Filed: 1/17/2013). Further Case Management Conference set for 3/13/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/17/2013) (Entered: 01/22/2013) 01/22/2013 283 Administrative Motion to File Under Seal filed by Adobe Systems Inc.. (Attachments: # 1 Exhibit, # 2 Exhibit A, # 3 Exhibit B, # 4 Exhibit C, # 5 Exhibit D, # 6 Exhibit E, # 7 Exhibit F, # 8 Exhibit G, # 9 Proposed Order Granting Renewed Administrative Motion to File Under Seal)(Kiernan, David) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 284 Declaration of Donna Morris in Support of 283 Administrative Motion to File Under Seal filed byAdobe Systems Inc.. (Related document(s) 283 ) (Kiernan, David) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 285 Declaration of Lisa K. Borgeson in Support of 283 Administrative Motion to File Under Seal filed byIntuit Inc.. (Related document(s) 283 ) (Kiernan, David) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 286 Letter from Eric Evans to Honorable Paul S. Grewal. (Evans, Eric) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 287 Declaration of Tina M. Evangelista in Support of 283 Administrative Motion to File Under Seal filed byIntel Corp.. (Related document(s) 283 ) (Busch, Frank) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 288 Declaration of Frank Wagner in Support of 283 Administrative Motion to File Under Seal filed byGoogle Inc.. (Related document(s) 283 ) (Selin, Anne) (Filed on 1/22/2013) (Entered: 01/22/2013) 1169 01/22/2013 289 NOTICE of Compliance with 273 Court's January 15, 2013 Order re Motions to Seal by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover (Harvey, Dean) (Filed on 1/22/2013) Modified text on 1/23/2013 (dhmS, COURT STAFF). (Entered: 01/22/2013) 01/22/2013 290 REDACTION to PLAINTIFFS' NOTICE OF MOTION AND MOTION FOR CLASS CERTIFICATION, AND MEMORANDUM OF LAW IN SUPPORT in compliance with the Court's January 15, 2013 Order 273 by Daniel Stover, Siddharth Hariharan, Michael Devine, Mark Fichtner, Brandon Marshall. (Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 291 REDACTION to DECLARATION OF ANNE B. SHAVER IN SUPPORT OF PLAINTIFFS' MOTION FOR CLASS CERTIFICATION in compliance with the Court's January 15, 2013 Order 273 by Daniel Stover, Siddharth Hariharan, Michael Devine, Mark Fichtner, Brandon Marshall. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4 (redacted), # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10 Exhibit 10, # 11 Exhibit 11, # 12 Exhibit 12, # 13 Exhibit 13, # 14 Exhibit 14 (redacted), # 15 Exhibit 16, # 16 Exhibit 17, # 17 Exhibit 18, # 18 Exhibit 19, # 19 Exhibit 20, # 20 Exhibit 21 (redacted), # 21 Exhibit 22, # 22 Exhibit 23, # 23 Exhibit 24 (redacted), # 24 Exhibit 25 (redacted), # 25 Exhibit 26, # 26 Exhibit 27, # 27 Exhibit 28, # 28 Exhibit 29 (redacted), # 29 Exhibit 30, # 30 Exhibit 31, # 31 Exhibit 32 (redacted), # 32 Exhibit 33, # 33 Exhibit 34 (redacted), # 34 Exhibit 35, # 35 Exhibit 36, # 36 Exhibit 37 (redacted), # 37 Exhibit 38, # 38 Exhibit 39 (redacted), # 39 Exhibit 40 (redacted), # 40 Exhibit 41, # 41 Exhibit 42 (redacted), # 42 Exhibit 50, # 43 Exhibit 51, # 44 Exhibit 52, # 45 Exhibit 53, # 46 Exhibit 55, # 47 Exhibit 56, # 48 Exhibit 57, # 49 Exhibit 58, # 50 Exhibit 60, # 51 Exhibit 61, # 52 Exhibit 62 (redacted), # 53 Exhibit 63 (redacted), # 54 Exhibit 64, # 55 Exhibit 65, # 56 Exhibit 66, # 57 Exhibit 67 (redacted), # 58 Exhibit 68 (redacted), # 59 Exhibit 69, # 60 Exhibit 70, # 61 Exhibit 71)(Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 292 Joint Administrative Motion to File Under Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Proposed Order, # 2 Exhibit Opposition [REDACTED], # 3 Exhibit Declaration [REDACTED], # 4 Opposition [highlighted], # 5 Declaration [highlighted])(Busch, Frank) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 293 AFFIDAVIT OF EDWARD T. COLLIGAN AND EXHIBITS A AND B in compliance with the Court's January 15, 2013 Order 273 by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 294 Declaration of Frank Busch in Support of 292 Joint Administrative Motion to File Under Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal filed byIntel Corp.. (Related document(s) 292 ) (Busch, Frank) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 295 Declaration of Catherine T. Zeng in Support of 292 Joint Administrative Motion to File Under Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal filed byIntuit Inc.. (Related document(s) 292 ) (Zeng, Catherine) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 296 DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,,,, PLAINTIFFS' NOTICE OF MOTION AND MOTION FOR CLASS CERTIFICATION, AND MEMORANDUM OF LAW IN SUPPORT by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Anne B. Shaver in Support of Plaintiffs' Motion for Class Certification, # 2 Exhibit 4, # 3 Exhibit 14, # 4 Exhibit 15, # 5 Exhibit 21, # 6 Exhibit 24, # 7 Exhibit 25, # 8 Exhibit 29, # 9 Exhibit 32, # 10 Exhibit 34, # 11 Exhibit 37, # 12 Exhibit 39, # 13 Exhibit 40, # 14 Exhibit 42, # 15 Exhibit 43, # 16 Exhibit 44, # 17 Exhibit 45, # 18 Exhibit 46, # 19 1170 Exhibit 47, # 20 Exhibit 48, # 21 Exhibit 49, # 22 Exhibit 54, # 23 Exhibit 59, # 24 Exhibit 62, # 25 Exhibit 63, # 26 Exhibit 67, # 27 Exhibit 68)(Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 297 REDACTION to PLAINTIFFS' CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND IN OPPOSITION TO MOTION TO STRIKE in compliance with the Court's January 15, 2013 Order 273 by Daniel Stover, Siddharth Hariharan, Michael Devine, Mark Fichtner, Brandon Marshall. (Attachments: # 1 Declaration of Dean M. Harvey, # 2 Exhibit 1 (redacted), # 3 Exhibit 2 (redacted), # 4 Exhibit 3, # 5 Exhibit 4 (redacted), # 6 Exhibit 5, # 7 Exhibit 6, # 8 Exhibit 7, # 9 Exhibit 8, # 10 Exhibit 9, # 11 Exhibit 10 (redacted), # 12 Exhibit 11, # 13 Exhibit 12, # 14 Exhibit 13 (redacted), # 15 Exhibit 14, # 16 Exhibit 21, # 17 Exhibit 26 (redacted), # 18 Exhibit 27 (redacted), # 19 Exhibit 28, # 20 Exhibit 29 (redacted), # 21 Exhibit 31, # 22 Exhibit 32, # 23 Exhibit 33, # 24 Exhibit 34)(Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 298 DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,,,, PLAINTIFFS' CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND IN OPPOSITION TO MOTION TO STRIKE in compliance with the Court's January 15, 2013 Order by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Dean M. Harvey, # 2 Exhibit 1, # 3 Exhibit 2, # 4 Exhibit 4, # 5 Exhibit 10, # 6 Exhibit 13, # 7 Exhibit 15, # 8 Exhibit 16, # 9 Exhibit 17, # 10 Exhibit 18, # 11 Exhibit 19, # 12 Exhibit 20, # 13 Exhibit 22, # 14 Exhibit 23, # 15 Exhibit 24, # 16 Exhibit 25, # 17 Exhibit 26, # 18 Exhibit 27, # 19 Exhibit 29, # 20 Exhibit 30)(Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 299 DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,,,, Letter from Brendan P. Glackin RE CORRECTION TO CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND IN OPPOSITION TO MOTION TO STRIKE, AND REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D. by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 300 Declaration of Christina Brown in Support of 292 Joint Administrative Motion to File Under Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal filed byApple Inc.. (Related document(s) 292 ) (Brown, Christina) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 301 REDACTION to 210 MOTION to Strike the Report of Dr. Edward E. Leamer in compliance with the Court's January 15, 2013 Order 273 by Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Exhibit to Welch Declaration in Support)(Busch, Frank) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 302 DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,,,, Motion to Strike the Report of Dr. Edward E. Leamer 210 by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Declaration of Susan J. Welch, # 2 Exhibit to Welch Declaration)(Busch, Frank) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 303 Declaration of Justina K. Sessions in Support of Defendants' Renewed Administrative Motion to Seal filed byLucasfilm Ltd.. (Sessions, Justina) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 304 REDACTION OPPOSITION TO PLAINTIFFS MOTION FOR CLASS CERTIFICATION by Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Brown, Christina) (Filed on 1/22/2013) (Entered: 01/22/2013) 01/22/2013 305 Declaration of Anne M. Selin in Support of Defendants' Renewed Motion to Seal filed byGoogle Inc.. (Selin, Anne) (Filed on 1/22/2013) (Entered: 01/22/2013) 1171 01/23/2013 306 Declaration of Christina J. Brown in Support of 307 Renewed Administrative Motion to Seal filed by Apple Inc.. (Brown, Christina) (Filed on 1/23/2013) Modified on 1/28/2013 linking entry to document #307 (dhmS, COURT STAFF). (Entered: 01/23/2013) 01/23/2013 307 Renewed Administrative Motion to File Under Seal filed by Apple Inc.. (Attachments: # 1 Proposed Order)(Brown, Christina) (Filed on 1/23/2013) Modified text on 1/28/2013 (dhmS, COURT STAFF). (Entered: 01/23/2013) 01/23/2013 308 REDACTION to 304 Redacted Document by Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10 Exhibit 10, # 11 Exhibit 11, # 12 Exhibit 12, # 13 Exhibit 13, # 14 Exhibit 14a, # 15 Exhibit 14b, # 16 Exhibit 14c, # 17 Exhibit 14d, # 18 Exhibit 14e, # 19 Exhibit 14f, # 20 Proposed Order 15, # 21 Exhibit 16, # 22 Exhibit 17, # 23 Exhibit 18, # 24 Exhibit 19, # 25 Exhibit 20, # 26 Exhibit 21, # 27 Exhibit 22a,*** PURSUANT TO ORDER 317 , DOCUMENT REMOVED. DOCUMENT TO BE REFILED LATER. *** # 28 Exhibit 22b, # 29 Exhibit 22c, # 30 Exhibit 23, # 31 Exhibit 24, # 32 Exhibit 25, # 33 Exhibit 26, # 34 Exhibit 27)(Brown, Christina) (Filed on 1/23/2013) Modified on 1/23/2013 (fff, COURT STAFF). (Attachment 27 replaced on 1/31/2013) (sp, COURT STAFF). Modified on 1/31/2013 (sp, COURT STAFF). (Entered: 01/23/2013) 01/23/2013 309 EXHIBITS re 307 Administrative Motion to File Under Seal filed byAdobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit A-1b, # 2 Exhibit A-1c, # 3 Exhibit A-1d, # 4 Exhibit A-1e, # 5 Exhibit A-1f, # 6 Exhibit B-1, # 7 Exhibit C-1, # 8 Exhibit D-1, # 9 Exhibit E-1, # 10 Exhibit F-1, # 11 Exhibit G-1a,*** PURSUANT TO ORDER 317 , DOCUMENT REMOVED. DOCUMENT TO BE REFILED LATER. *** # 12 Exhibit G-1b, # 13 Exhibit G-1c, # 14 Exhibit H-1, # 15 Exhibit I-1, # 16 Exhibit J-1, # 17 Exhibit K-1)(Related document(s) 307 ) (Brown, Christina) (Filed on 1/23/2013) Modified on 1/23/2013 (fff, COURT STAFF). (Attachment 11 replaced on 1/31/2013) (sp, COURT STAFF). Modified on 1/31/2013 (sp, COURT STAFF). (Entered: 01/23/2013) 01/23/2013 310 MOTION to Remove Incorrectly Filed Document filed by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 1/23/2013) (Entered: 01/23/2013) 01/23/2013 311 Proposed Order re 310 MOTION to Remove Incorrectly Filed Document by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 1/23/2013) (Entered: 01/23/2013) 01/23/2013 312 EXHIBITS re 308 Redacted Document,,,, Exhibit 22a to Declaration of Christina Brown filed byLucasfilm Ltd.. (Related document(s) 308 ) (Sessions, Justina) (Filed on 1/23/2013) (Entered: 01/23/2013) 01/23/2013 313 Administrative Motion to File Under Seal Google's Response In Support of Plaintiffs' Administrative Motion to Seal Portions of Plaintiffs' Motion to Compel Google Documents and the Declaration of Dean M. Harvey In Support Thereof filed by Google Inc.. (Attachments: # 1 Exhibit Exhibit 1, # 2 Exhibit Exhibit 2, # 3 Exhibit Exhibit 3, # 4 Proposed Order, # 5 Declaration Declaration of Anne M. Selin, # 6 Exhibit, # 7 Exhibit, # 8 Exhibit)(Selin, Anne) (Filed on 1/23/2013) (Entered: 01/23/2013) 01/23/2013 314 EXHIBITS G1-a to 307 Defendant's Renewed Administrative Motion filed by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 1/23/2013) Modified on 1/28/2013 linking entry to document #307 (dhmS, COURT STAFF). (Entered: 01/23/2013) 01/23/2013 315 ORDER DENYING MOTION TO SHORTEN TIME by Judge Paul S. Grewal, denying 280 Motion to Shorten Time. (ofr, COURT STAFF) (Filed on 1/23/2013) (Entered: 01/24/2013) 01/24/2013 316 STATUS REPORT by Apple Inc., Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Tubach, Michael) (Filed on 1/24/2013) (Entered: 01/24/2013) 1172 01/25/2013 317 Order by Hon. Lucy H. Koh granting (310) Motion to Remove Incorrectly Filed Document in case 5:11-cv-02509-LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK (lhklc1, COURT STAFF) (Filed on 1/25/2013) (Entered: 01/25/2013) 01/25/2013 318 OPPOSITION to ( 278 MOTION to Compel Google Documents [REDACTED] ) filed byGoogle Inc.. (Attachments: # 1 Declaration of Lee H. Rubin, # 2 Declaration of Alan Eustace)(Evans, Eric) (Filed on 1/25/2013) Modified text on 1/28/2013 (dhmS, COURT STAFF). (Entered: 01/25/2013) 01/25/2013 319 Administrative Motion to File Under Seal re Google's Opposition to Plaintiffs' Motion to Compel and Supporting Documents filed by Google Inc.. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Declaration of Laszlo Bock, # 4 Declaration of Eric B. Evans, # 5 Proposed Order)(Evans, Eric) (Filed on 1/25/2013) (Entered: 01/25/2013) 02/01/2013 320 Statement JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dermody, Kelly) (Filed on 2/1/2013) (Entered: 02/01/2013) 02/05/2013 321 Transcript of Proceedings held on 01-17-13, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 5/6/2013. (las, ) (Filed on 2/5/2013) (Entered: 02/05/2013) 02/05/2013 322 ORDER REGARDING JOINT DISCOVERY STATUS REPORT TO THE COURT. Signed by Judge Lucy H. Koh on 2/05/2013. (lhklc3, COURT STAFF) (Filed on 2/5/2013) (Entered: 02/05/2013) 02/08/2013 323 STIPULATION WITH PROPOSED ORDER Permiting Supplemental Briefing Regarding Plaintiffs Motion to Compel Google Documents filed by Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 2/8/2013) (Entered: 02/08/2013) 02/11/2013 324 STIPULATION AND ORDER PERMITTING SUPPLEMENTAL BRIEFING REGARDING PLAINTIFFS' MOTION TO COMPEL GOOGLE DOCUMENTS by Judge Paul S. Grewal, granting 323 . (ofr, COURT STAFF) (Filed on 2/11/2013) (Entered: 02/12/2013) 02/13/2013 325 Supplemental Brief re 278 MOTION to Compel Google Documents [REDACTED] filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration (Supplemental) of Dean M. Harvey in Support of Plaintiffs' Motion to Compel [Redacted])(Related document(s) 278 ) (Harvey, Dean) (Filed on 2/13/2013) (Entered: 02/13/2013) 02/13/2013 326 Administrative Motion to File Under Seal Portions of Plaintiffs' Supplement Regarding Motion to Compel Google Documents filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D)(Harvey, Dean) (Filed on 2/13/2013) (Entered: 02/13/2013) 02/15/2013 327 STATUS REPORT Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Shaver, Anne) (Filed on 2/15/2013) (Entered: 02/15/2013) 02/18/2013 328 RESPONSE (re 278 MOTION to Compel Google Documents [REDACTED] 1173 ) Supplement regarding Plaintiffs' Motion to Compel filed byGoogle Inc.. (Attachments: # 1 Declaration of Eric B. Evans)(Evans, Eric) (Filed on 2/18/2013) (Entered: 02/18/2013) 02/18/2013 329 Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Declaration of Eric B. Evans, # 4 Proposed Order)(Evans, Eric) (Filed on 2/18/2013) (Entered: 02/18/2013) 02/20/2013 330 ORDER RE Privilege Logs. Signed by Judge Lucy H. Koh on 2/20/2013. (lhklc3, COURT STAFF) (Filed on 2/20/2013) (Entered: 02/20/2013) 02/20/2013 331 Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Declaration of Eric B. Evans, # 6 Proposed Order)(Evans, Eric) (Filed on 2/20/2013) (Entered: 02/20/2013) 02/26/2013 332 Minute Entry: Motion Hearing held on 2/26/2013 before Magistrate Judge Paul S. Grewal re 278 MOTION to Compel: The court takes matter under submission; written order after hearing to be issued. (Court Reporter: Summer Fisher.) (ofr, COURT STAFF) (Date Filed: 2/26/2013) (Entered: 02/26/2013) 02/28/2013 333 ORDER GRANTING-IN-PART SEALING MOTIONS by Judge Paul S. Grewal granting 313 Administrative Motion to File Under Seal; granting in part and denying in part 319 Administrative Motion to File Under Seal; granting in part and denying in part 326 Administrative Motion to File Under Seal; granting in part and denying in part 329 Administrative Motion to File Under Seal; granting in part and denying in part 331 Administrative Motion to File Under Seal; granting 279 Administrative Motion to File Under Seal (psglc2, COURT STAFF) (Filed on 2/28/2013) (Entered: 02/28/2013) 02/28/2013 334 ORDER RE PLAINTIFFS' MOTION TO COMPEL PRODUCTION by Judge Paul S. Grewal denying 278 Motion to Compel (psglc2, COURT STAFF) (Filed on 2/28/2013) (Entered: 02/28/2013) 03/02/2013 335 Administrative Motion to File Under Seal Exhibits 1 and 2 to the March 1, 2013 Joint Discovery Status Report filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit Exhibits 1 and 2)(Cisneros, Lisa) (Filed on 3/2/2013) (Entered: 03/02/2013) 03/02/2013 336 JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Attachments: # 1 Exhibit A to Joint Discovery Status Report, # 2 Slip Sheet)(Cisneros, Lisa) (Filed on 3/2/2013) Modified text on 3/4/2013 (dhmS, COURT STAFF). (Entered: 03/02/2013) 03/02/2013 337 Declaration of Lisa J. Cisneros Regarding Late Filing on 3/2/2013 Statement re 335 Administrative Motion to File Under Seal Exhibits 1 and 2 to the March 1, 2013 Joint Discovery Status Report, 336 Status Report, by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 3/2/2013) Modified text on 3/4/2013 (dhmS, COURT STAFF). (Entered: 03/02/2013) 03/04/2013 338 NOTICE OF REQUEST for In Camera Review by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover (Attachments: # 1 Exhibit A)(Shaver, Anne) (Filed on 3/4/2013) Modified text on 3/5/2013 (dhmS, COURT STAFF). (Entered: 03/04/2013) 03/04/2013 339 MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Supplement, # 2 Declaration, # 3 Proposed Order)(Dallal, James) (Filed on 3/4/2013) (Entered: 03/04/2013) 03/06/2013 340 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., 1174 Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Brown, Christina) (Filed on 3/6/2013) Modified text on 3/8/2013 (dhmS, COURT STAFF). (Entered: 03/07/2013) 03/08/2013 341 NOTICE by Google Inc. re 334 Order on Motion to Compel Notice of Compliance with February 27, 2013 Order (Evans, Eric) (Filed on 3/8/2013) (Entered: 03/08/2013) 03/08/2013 342 ORDER RE: DEPOSITION OBJECTIONS. Signed by Judge Lucy H. Koh on March 8, 2013. (lhklc1, COURT STAFF) (Filed on 3/8/2013) (Entered: 03/08/2013) 03/08/2013 343 MOTION for Leave to File Statement of Recent Decision filed by Lucasfilm Ltd.. (Attachments: # 1 *** EXHIBIT 1 FILED IN ERROR, REFER TO DOCUMENT 345 . *** Exhibit 1, # 2 Proposed Order)(Sessions, Justina) (Filed on 3/8/2013) Modified on 3/11/2013 (fff, COURT STAFF). (Entered: 03/08/2013) 03/08/2013 344 CORRECTIONS to 340 Joint Case Management Statement, by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 3/8/2013) Modified text on 3/11/2013 (dhmS, COURT STAFF). (Entered: 03/08/2013) 03/08/2013 345 ERRATA re 343 MOTION for Leave to File Statement of Recent Decision CORRECTION OF DOCKET #, 343 [343-1] by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 3/8/2013) (Entered: 03/08/2013) 03/08/2013 346 Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Declaration of Eric B. Evans, # 2 Signature Page (Declarations/Stipulations))(Evans, Eric) (Filed on 3/8/2013) (Entered: 03/09/2013) 03/12/2013 347 Administrative Motion to File Under Seal Pursuant to February 28, 2013 Sealing Order filed by Google Inc.. (Attachments: # 1 Declaration, # 2 Proposed Order, # 3 Exhibit, # 4 Exhibit, # 5 Exhibit, # 6 Exhibit, # 7 Exhibit, # 8 Exhibit, # 9 Exhibit, # 10 Exhibit)(Selin, Anne) (Filed on 3/12/2013) (Entered: 03/12/2013) 03/13/2013 348 MOTION for leave to appear in Pro Hac Vice ( Filing fee $ 305, receipt number 09717545843.) filed by Pixar. (Nields, John) (Filed on 3/13/2013) (Entered: 03/13/2013) 03/13/2013 349 Order by Hon. Lucy H. Koh granting (348) Motion for Pro Hac Vice in case 5:11-cv-02509LHK for Nields.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc3, COURT STAFF) (Filed on 3/13/2013) (Entered: 03/13/2013) 03/13/2013 350 CASE MANAGEMENT ORDER. Signed by Judge Lucy H. Koh on March 13, 2013. (lhklc1, COURT STAFF) (Filed on 3/13/2013) (Entered: 03/13/2013) 03/13/2013 357 Minute Entry: Further Case Management Conference held on 3/13/2013 before Judge Lucy H. Koh (Date Filed: 3/13/2013). Further Case Management Conference set for 4/2/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 3/13/2013) (Entered: 03/15/2013) 03/14/2013 351 Statement Regarding Document Redactions by Pixar. (Henn, Emily) (Filed on 3/14/2013) (Entered: 03/14/2013) 03/14/2013 352 Statement re 350 Order Statement regarding Redactions by Google Inc.. (Evans, Eric) (Filed on 3/14/2013) (Entered: 03/14/2013) 03/14/2013 353 Statement re 350 Order Defendants Adobe Systems Inc. and Intuit Inc.'s Statements Regarding Redactions by Adobe Systems Inc., Intuit Inc.. (Mittelstaedt, Robert) (Filed on 3/14/2013) (Entered: 03/14/2013) 03/14/2013 354 Statement re 350 Order Regarding Redactions by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 3/14/2013) (Entered: 03/14/2013) 03/14/2013 355 1175 Statement Regarding Document Redactions by Apple Inc.. (Tubach, Michael) (Filed on 3/14/2013) (Entered: 03/14/2013) 03/14/2013 356 Statement Regarding Document Redactions by Intel Corp.. (Shah, Sujal) (Filed on 3/14/2013) (Entered: 03/14/2013) 03/15/2013 358 NOTICE of Change In Counsel by Cody Shawn Harris NOTICE OF WITHDRAWAL OF COUNSEL (Harris, Cody) (Filed on 3/15/2013) (Entered: 03/15/2013) 03/15/2013 359 ORDER RE: REDACTIONS FOR LACK OF RELEVANCE AND/OR RESPONSIVENESS. Signed by Judge Lucy H. Koh on March 15, 2013. (lhklc1, COURT STAFF) (Filed on 3/15/2013) (Entered: 03/15/2013) 03/15/2013 360 STATUS REPORT Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 3/15/2013) (Entered: 03/15/2013) 03/18/2013 361 ORDER GRANTING DEFENDANT GOOGLE INC.'S RENEWED ADMINISTRATIVE MOTION TO FILE UNDER SEAL PURSUANT TO FEBRUARY 28, 2013 SEALING ORDER by Judge Paul S. Grewal, granting 347 . (ofr, COURT STAFF) (Filed on 3/18/2013) (Entered: 03/18/2013) 03/18/2013 362 ORDER RE: MARCH 15, 2013 STATUS REPORT. Signed by Judge Lucy H. Koh on March 18, 2013. (lhklc1, COURT STAFF) (Filed on 3/18/2013) (Entered: 03/18/2013) 03/19/2013 363 TRANSCRIPT ORDER by Apple Inc. from Court Reporter Lee-Anne Shortridge. (Brown, Christina) (Filed on 3/19/2013) (Entered: 03/19/2013) 03/21/2013 364 NOTICE of Appearance by Amanda R. Conley (Conley, Amanda) (Filed on 3/21/2013) (Entered: 03/21/2013) 03/22/2013 365 Joint Discovery Status Report by Google Inc.. (Selin, Anne) (Filed on 3/22/2013) Modified text on 3/25/2013 (dhmS, COURT STAFF). (Entered: 03/22/2013) 03/26/2013 366 Transcript of Proceedings held on 3-13-13, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: leeanne_shortridge@cand.uscourts.gov. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 6/24/2013. (Related documents(s) 363 ) (las, ) (Filed on 3/26/2013) (Entered: 03/26/2013) 03/26/2013 367 TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on 3/26/2013) (Entered: 03/26/2013) 03/27/2013 368 MOTION for Leave to File Statement of Recent Decision filed by Intuit Inc.. (Attachments: # 1 Exhibit 1, # 2 Exhibit A, # 3 Proposed Order)(Zeng, Catherine) (Filed on 3/27/2013) (Entered: 03/27/2013) 03/28/2013 369 TRANSCRIPT ORDER by Intel Corp. for Court Reporter Lee-Anne Shortridge. (Busch, Frank) (Filed on 3/28/2013) (Entered: 03/28/2013) 03/28/2013 370 MOTION to Withdraw as Attorney filed by Pixar. Responses due by 4/11/2013. Replies due by 4/18/2013. (Attachments: # 1 Proposed Order)(Haslam, Robert) (Filed on 3/28/2013) (Entered: 03/28/2013) 03/28/2013 371 STIPULATION WITH PROPOSED ORDER Regarding Document Admissibility and Authentication filed by Adobe Systems Inc.. (Mittelstaedt, Robert) (Filed on 3/28/2013) 1176 (Entered: 03/28/2013) 03/29/2013 372 Order by Hon. Lucy H. Koh granting 368 Motion for Leave to File.(lhklc3, COURT STAFF) (Filed on 3/29/2013) (Entered: 03/29/2013) 03/29/2013 373 Order by Hon. Lucy H. Koh granting 343 Motion for Leave to File Recent Decision.(lhklc3, COURT STAFF) (Filed on 3/29/2013) (Entered: 03/29/2013) 03/29/2013 374 Order by Hon. Lucy H. Koh granting 339 Motion for Leave to File Recent Decision.(lhklc3, COURT STAFF) (Filed on 3/29/2013) (Entered: 03/29/2013) 03/29/2013 375 Supplemental Brief re 361 Order on Administrative Motion to File Under Seal filed pursuant to Order dkt. no. 361 filed byGoogle Inc.. (Related document(s) 361 ) (Evans, Eric) (Filed on 3/29/2013) (Entered: 03/29/2013) 03/29/2013 376 Declaration of D. Harvey in Support of 361 Order on Administrative Motion to File Under Seal pursuant to Order dkt. no. 361 filed byGoogle Inc.. (Related document(s) 361 ) (Evans, Eric) (Filed on 3/29/2013) (Entered: 03/29/2013) 03/29/2013 377 OPPOSITION to 361 Order on Administrative Motion to File Under Seal pursuant to Order dkt. no. 361 by Google Inc.. (Evans, Eric) (Filed on 3/29/2013) Modified text on 4/1/2013 (dhmS, COURT STAFF). (Entered: 03/29/2013) 03/29/2013 378 DECLARATION of Eric B. Evans in Opposition to 361 Order on Administrative Motion to File Under Seal pursuant to Order dkt. no. 361 filed byGoogle Inc.. (Related document(s) 361 ) (Evans, Eric) (Filed on 3/29/2013) (Entered: 03/29/2013) 03/29/2013 379 Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 3/29/2013) Modified text on 4/1/2013 (dhmS, COURT STAFF). (Entered: 03/29/2013) 04/01/2013 380 ORDER REGARDING DISCOVERY. Signed by Judge Lucy H. Koh on 4/01/2013. (lhklc3, COURT STAFF) (Filed on 4/1/2013) (Entered: 04/01/2013) 04/02/2013 381 CLERKS NOTICE CONTINUING FURTHER CASE MANAGEMENT CONFERENCE Further Case Management Conference set for 4/8/2013 10:00 AM in Courtroom 8, 4th Floor, San Jose. *****THIS IS A TEXT ONLY NOTICE. THERE IS NO DOCUMENT ASSOCIATED WITH THIS DOCKET ENTRY***** (mpb, COURT STAFF) (Filed on 4/2/2013) (Entered: 04/02/2013) 04/05/2013 382 ORDER by Judge Lucy H. Koh granting in part and denying in part (187) Motion to Certify Class; denying (210) Motion to Strike ; denying (263) Motion for Leave to File in case 5:11cv-02509-LHK (lhklc3, COURT STAFF) (Filed on 4/5/2013) (Entered: 04/05/2013) 04/05/2013 383 DOCUMENT E-FILED UNDER SEAL by Court Staff. (lhklc3, COURT STAFF) (Filed on 4/5/2013) (Additional attachment(s) added on 4/5/2013: # 1 Certificate/Proof of Service) (mpbS, COURT STAFF). (Entered: 04/05/2013) 04/05/2013 384 ORDER RE: JOINT CASE MANAGEMENT STATEMENT. Signed by Judge Lucy H. Koh on April 5, 2013. (lhklc1, COURT STAFF) (Filed on 4/5/2013) (Entered: 04/05/2013) 04/05/2013 385 STATUS REPORT Joint Discovery Status Report by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 4/5/2013) (Entered: 04/05/2013) 04/08/2013 386 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc.. (Kiernan, David) (Filed on 4/8/2013) Modified text on 4/9/2013 (dhmS, COURT STAFF). (Entered: 04/08/2013) 04/08/2013 387 TRANSCRIPT ORDER by Lucasfilm Ltd. for Court Reporter Lee-Anne Shortridge. (Paige, 1177 Eugene) (Filed on 4/8/2013) (Entered: 04/08/2013) 04/08/2013 388 04/08/2013 Minute Entry and Case Management Order: Further Case Management Conference held on 4/8/2013 before Judge Lucy H. Koh (Date Filed: 4/8/2013). Further Case Management Conference set for 5/15/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. Final Pretrial Conference set for 5/8/2014 01:30 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection set for 5/27/2014 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury Trial set for 5/27/2014 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 4/8/2013) (Entered: 04/08/2013) Set/Reset Hearing re 388 Case Management Conference - Further, Set Hearings Final Pretrial Conference set for 5/8/2014 01:30 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT STAFF) (Filed on 4/8/2013) (Entered: 04/08/2013) 04/08/2013 389 TRANSCRIPT ORDER by Apple Inc. for Court Reporter Lee-Anne Shortridge. (Brown, Christina) (Filed on 4/8/2013) (Entered: 04/08/2013) 04/09/2013 390 NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover OF WITHDRAWAL REGARDING DKT. NOS. 186 AND 246 (Harvey, Dean) (Filed on 4/9/2013) (Entered: 04/09/2013) 04/09/2013 391 Notice of Withdrawal of Motion Regarding Dkt. Nos. 195 , 211 , 254 , 264 , and 292 (Hinman, Frank) (Filed on 4/9/2013) (Entered: 04/09/2013) 04/12/2013 392 Transcript of Proceedings held on 4-8-13, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: leeanne_shortridge@cand.uscourts.gov. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 7/11/2013. (Related documents(s) 387 ) (las, ) (Filed on 4/12/2013) (Entered: 04/12/2013) 04/12/2013 393 Joint Discovery Status Report by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 4/12/2013) Modified text on 4/15/2013 (dhmS, COURT STAFF). (Entered: 04/12/2013) 04/12/2013 394 Joint Renewed Administrative Motion to File Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit A-1, # 2 Exhibit B-1 (part 1), # 3 Exhibit B-1 (part 2), # 4 Exhibit B-1 (part 3), # 5 Exhibit C-1, # 6 Exhibit D-1, # 7 Exhibit E-1, # 8 Exhibit F-1, # 9 Exhibit G-1, # 10 Exhibit A-2 (highlighted), # 11 Exhibit B2 (highlighted), # 12 Exhibit C-2 (highlighted), # 13 Exhibit D-2 (highlighted), # 14 Exhibit E-2 (highlighted), # 15 Exhibit F-2 (highlighted), # 16 Exhibit G-2 (highlighted), # 17 Proposed Order)(Brown, Christina) (Filed on 4/12/2013) Modified text on 4/15/2013 (dhmS, COURT STAFF). (Entered: 04/12/2013) 04/12/2013 395 Declaration of Frank Busch in Support of 394 Joint Administrative Motion to File Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byIntel Corp.. (Related document(s) 394 ) (Busch, Frank) (Filed on 4/12/2013) (Entered: 04/12/2013) 04/12/2013 396 Declaration of Anne M. Selin in Support of 394 Joint Administrative Motion to File Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byGoogle Inc.. (Related document(s) 394 ) (Selin, Anne) (Filed on 4/12/2013) (Entered: 04/12/2013) 04/12/2013 397 Declaration of Catherine T. Zeng in Support of 394 Joint Administrative Motion to File Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byIntuit Inc.. (Related document(s) 394 ) (Zeng, Catherine) (Filed on 4/12/2013) (Entered: 04/12/2013) 04/12/2013 398 Declaration of Christina Brown in Support of 394 Joint Administrative Motion to File Under 1178 Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byApple Inc.. (Related document(s) 394 ) (Brown, Christina) (Filed on 4/12/2013) (Entered: 04/12/2013) 04/12/2013 399 Declaration of Lin Kahn in Support of 394 Joint Administrative Motion to File Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byAdobe Systems Inc.. (Related document(s) 394 ) (Kahn, Lin) (Filed on 4/12/2013) (Entered: 04/12/2013) 04/12/2013 400 Declaration of James M. Kennedy in Support of 394 Defendants' Renewed Motion to Seal filed by Pixar. (Richardson, Chinue) (Filed on 4/12/2013) Modified on 4/15/2013 linking entry to document #394 (dhmS, COURT STAFF). (Entered: 04/13/2013) 04/13/2013 401 Declaration of Justina K. Sessions in Support of 394 Joint Administrative Motion to File Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byLucasfilm Ltd.. (Related document(s) 394 ) (Sessions, Justina) (Filed on 4/13/2013) (Entered: 04/13/2013) 04/15/2013 402 ORDER Regarding April 12, 2013 Joint Discovery Status Report. Signed by Judge Lucy H. Koh on 4/15/2013. (lhklc3, COURT STAFF) (Filed on 4/15/2013) (Entered: 04/15/2013) 04/15/2013 403 TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on 4/15/2013) (Entered: 04/15/2013) 04/19/2013 404 Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 4/19/2013) Modified text on 4/22/2013 (dhmS, COURT STAFF). (Entered: 04/19/2013) 04/25/2013 405 Declaration of Thomas Henry Intuit's In-House counsel filed byIntuit Inc.. (Kiernan, David) (Filed on 4/25/2013) (Entered: 04/25/2013) 04/25/2013 406 Declaration of Adobe's In-House Counsel Karen Robinson filed byAdobe Systems Inc.. (Kiernan, David) (Filed on 4/25/2013) (Entered: 04/25/2013) 04/25/2013 407 Declaration of William G. Berry Re 402 April 15, 2013 Order filed by Google Inc.. (Selin, Anne) (Filed on 4/25/2013) Modified on 4/26/2013 linking entry to document #402 (dhmS, COURT STAFF). (Entered: 04/25/2013) 04/25/2013 408 Declaration of James M. Kennedy on behalf of Pixar pursuant tp 402 Court's April 15, 2013 Order filed by Pixar. (Richardson, Chinue) (Filed on 4/25/2013) Modified on 4/26/2013 linking entry to document #402 (dhmS, COURT STAFF). (Entered: 04/25/2013) 04/25/2013 409 Declaration of Joy C. Sherrod Regarding Intel's Production Of Compensation Related Discovery Materials filed byIntel Corp.. (Shah, Sujal) (Filed on 4/25/2013) (Entered: 04/25/2013) 04/25/2013 410 Declaration of Thomas M. Jeon in Support of 402 Order dated April 15, 2013 filed byLucasfilm Ltd.. (Attachments: # 1 Signature Attestation)(Related document(s) 402 ) (Purcell, Daniel) (Filed on 4/25/2013) (Entered: 04/25/2013) 04/25/2013 411 Declaration of Heather Moser Grenier filed byApple Inc.. (Attachments: # 1 Exhibit A) (Tubach, Michael) (Filed on 4/25/2013) (Entered: 04/25/2013) 04/26/2013 412 TRANSCRIPT ORDER by UNITED STATES OF AMERICA for Court Reporter Lee-Anne Shortridge. (Pletcher, Anna) (Filed on 4/26/2013) (Entered: 04/26/2013) 04/26/2013 413 JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 4/26/2013) Modified text on 4/29/2013 (dhmS, COURT STAFF). (Entered: 04/26/2013) 1179 05/03/2013 414 Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 5/3/2013) Modified text on 5/6/2013 (dhmS, COURT STAFF). (Entered: 05/03/2013) 05/08/2013 415 JOINT CASE MANAGEMENT CONFERENCE STATEMENT filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 5/8/2013) Modified text on 5/9/2013 (dhmS, COURT STAFF). (Entered: 05/08/2013) 05/10/2013 416 JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 5/10/2013) Modified text on 5/13/2013 (dhmS, COURT STAFF). (Entered: 05/10/2013) 05/10/2013 417 Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1:Redacted Supplemental Class Certification Motion, # 2 Exhibit 2:Redacted Expert Report of Kevin Hallock, # 3 Exhibit 3: Redacted Report of Edward Leamer, # 4 Proposed Order)(Harvey, Dean) (Filed on 5/10/2013) (Entered: 05/10/2013) 05/10/2013 418 SUPPLEMENTAL MOTION to Certify Class and Brief in Support of Class Certification filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion Hearing set for 8/8/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 6/21/2013. Replies due by 7/12/2013. (Attachments: # 1 Declaration Dean Harvey, # 2 Declaration Lisa Cisneros, # 3 Exhibit Redacted Expert Report of Kevin Hallock, # 4 Exhibit Redacted Expert Report of Edward Leamer, # 5 Proposed Order)(Harvey, Dean) (Filed on 5/10/2013) Modified text on 5/13/2013 (dhmS, COURT STAFF). (Entered: 05/10/2013) 05/14/2013 419 Order by Hon. Lucy H. Koh granting 370 Motion to Withdraw as Attorney. Attorney Robert T. Haslam, III terminated.(lhklc3, COURT STAFF) (Filed on 5/14/2013) (Entered: 05/14/2013) 05/14/2013 420 Order by Hon. Lucy H. Koh granting 371 Stipulation Regarding Document Admissibility and Authentication.(lhklc3, COURT STAFF) (Filed on 5/14/2013) (Entered: 05/14/2013) 05/15/2013 421 CASE MANAGEMENT ORDER. Signed by Judge Lucy H. Koh on 5/15/2013. (lhklc3, COURT STAFF) (Filed on 5/15/2013) (Entered: 05/15/2013) 05/15/2013 422 Minute Entry: Further Case Management Conference held on 5/15/2013 before Judge Lucy H. Koh (Date Filed: 5/15/2013). Further Case Management Conference set for 8/8/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Raynee Mercado.) (mpb, COURT STAFF) (Date Filed: 5/15/2013) (Entered: 05/16/2013) 05/17/2013 423 JOINT DISCOVERY STATUS REPORT by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 424 Joint Response to Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Adobe Systems Inc.. (Attachments: # 1 Exhibit Expert Witness Report of Kevin Hallock - REDACTED, # 2 Exhibit Supplemental Expert Report of Edward E. Leamer, Ph.D. - REDACTED, # 3 Exhibit Plaintiffs' Supplemental Motion and Brief in Support of Class Certification - REDACTED, # 4 Proposed Order, # 5 Certificate/Proof of Service POS of Documents Lodged Under Seal) (Kiernan, David) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 425 Declaration of Catherine T. Zeng in Support of 424 Response to Administrative Motion to 1180 File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Intuit Inc.. (Attachments: # 1 Exhibit EE, # 2 Exhibit FF, # 3 Exhibit GG, # 4 Exhibit HH, # 5 Exhibit II, # 6 Exhibit JJ, # 7 Exhibit 912, # 8 Exhibit 914, # 9 Exhibit 1107, # 10 Exhibit 1760, # 11 Exhibit 1761, # 12 Exhibit 2135, # 13 Exhibit 2140, # 14 Exhibit 2142, # 15 Exhibit 2738, # 16 Exhibit 2739 Part 1, # 17 Exhibit 2739 Part 2, # 18 Exhibit 2739 Part 3, # 19 Exhibit 2740 Part 1, # 20 Exhibit 2740 Part 2, # 21 Exhibit 2743, # 22 Exhibit 2744, # 23 Certificate/Proof of Service)(Related document(s) 424 ) (Zeng, Catherine) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 426 Declaration of Justina K. Sessions in Support of 424 Joint Response to Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Lucasfilm Ltd.. (Attachments: # 1 Exhibit 17, # 2 Exhibit 8, # 3 Exhibit 112, # 4 Envelope 359, # 5 Exhibit 360, # 6 Exhibit 690, # 7 Exhibit 710, # 8 Exhibit 711, # 9 Exhibit 715, # 10 Exhibit 716, # 11 Exhibit 727, # 12 Exhibit 728, # 13 Exhibit 729, # 14 Exhibit 730, # 15 Exhibit 944, # 16 Exhibit 945, # 17 Exhibit 959, # 18 Exhibit 2002, # 19 Exhibit 2084, # 20 Exhibit 2088, # 21 Exhibit 2094, # 22 Exhibit 2096, # 23 Exhibit 2100, # 24 Exhibit KK, # 25 Exhibit LL, # 26 Exhibit MM, # 27 Exhibit NN, # 28 Exhibit OO, # 29 Exhibit PP)(Related document(s) 424 ) (Sessions, Justina) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 427 Declaration of Eric B. Evans in Support of 424 Joint Response to Administrative Motion to File Under Seal Plaintiffs' Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Google Inc.. (Attachments: # 1 Exhibit Q, # 2 Exhibit R, # 3 Exhibit S, # 4 Exhibit T, # 5 Exhibit V, # 6 Exhibit W, # 7 Exhibit X, # 8 Exhibit EE)(Related document(s) 424 ) (Evans, Eric) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 428 EXHIBITS re 418 SUPPLEMENTAL MOTION to Certify Class Public Exhibits to Cisneros Declaration, Exhibit U filed byGoogle Inc.. (Attachments: # 1 Exhibit 175, # 2 Exhibit 186, # 3 Exhibit 192, # 4 Exhibit 557, # 5 Exhibit 597, # 6 Exhibit 648, # 7 Exhibit 650, # 8 Exhibit 651, # 9 Exhibit 653, # 10 Exhibit 661, # 11 Exhibit 872, # 12 Exhibit 1868, # 13 Exhibit 1869, # 14 Exhibit 1870, # 15 Exhibit 1871, # 16 Exhibit 1872, # 17 Exhibit 2735) (Related document(s) 418 ) (Evans, Eric) (Filed on 5/17/2013) (Entered: 05/17/2013) 05/17/2013 429 Declaration of Lin W. Kahn in Support of 424 Joint Response to Administrative Motion to File Under Seal Plaintiffs' Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Adobe Systems Inc.. (Attachments: # 1 Exhibit A-D, F, # 2 Exhibit 11, # 3 Exhibit 12, # 4 Exhibit 210, # 5 Exhibit 216, # 6 Exhibit 300, # 7 Exhibit 416, # 8 Errata 1158, # 9 Exhibit 1159, # 10 Exhibit 1160, # 11 Exhibit 1250, # 12 Exhibit 2486-1, # 13 Exhibit 2486-2, # 14 Exhibit 2486-3, # 15 Exhibit 2487, # 16 Exhibit 2501, # 17 Exhibit 2800, # 18 Certificate/Proof of Service) (Related document(s) 424 ) (Kahn, Lin) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 430 REDACTION Declaration of Krystal N. Bowen in Support of 424 Joint Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents by Intel Corp.. (Attachments: # 1 Exhibit 9, # 2 Exhibit 10, # 3 Exhibit Y, # 4 Exhibit Z, # 5 Exhibit AA, # 6 Exhibit BB, # 7 Exhibit CC, # 8 Exhibit DD, # 9 Exhibit 391, # 10 Exhibit 392, # 11 Exhibit 393, # 12 Exhibit 397, # 13 Exhibit 398, # 14 Exhibit 399, # 15 Exhibit 400, # 16 Exhibit 478, # 17 Exhibit 781, # 18 Exhibit 2030, # 19 Exhibit 2033, # 20 Exhibit 2035)(Bowen, Krystal) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 431 Declaration of James M. Kennedy in Support of 424 Joint Response to Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Pixar. (Attachments: # 1 Cisneros Ex. 129, # 2 Cisneros Ex. 137, # 3 Cisneros Ex. 420, # 4 Cisneros Ex. 424, # 5 Cisneros Ex. 1306, # 6 Cisneros Ex. 1308, # 7 Cisneros Ex. 1309, # 8 Cisneros Ex. QQ, # 9 Cisneros Ex. RR, # 101181 Cisneros Ex. SS, # 11 Cisneros Ex. TT, # 12 Cisneros Ex. UU, # 13 Cisneros Ex. VV)(Related document (s) 424 ) (Richardson, Chinue) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 432 Declaration of Christina Brown in Support of 424 Joint Response to Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Apple Inc.. (Related document(s) 424 ) (Brown, Christina) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013) 05/17/2013 433 EXHIBITS re 432 Declaration in Support, Declaration of Christina Brown in Support of Defendants' Joint Response to Plaintiffs' Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents, Exhibits 1-8 filed byApple Inc.. (Attachments: # 1 Exhibit H, # 2 Exhibit I, # 3 Exhibit J, # 4 Exhibit K, # 5 Exhibit L, # 6 Exhibit M, # 7 Exhibit N, # 8 Exhibit O, # 9 Exhibit P, # 10 Exhibit 268, # 11 Exhibit 278, # 12 Exhibit 279, # 13 Exhibit 1130, # 14 Exhibit 1376, # 15 Exhibit 1854, # 16 Exhibit 1855 (part 1), # 17 Exhibit 1855 (part 2), # 18 Exhibit 1855 (part 3), # 19 Exhibit 1856, # 20 Exhibit 1858, # 21 Exhibit 1859)(Related document(s) 432 ) (Brown, Christina) (Filed on 5/17/2013) (Entered: 05/18/2013) 05/20/2013 434 TRANSCRIPT ORDER by Apple Inc. for Court Reporter Raynee Mercado. (Brown, Christina) (Filed on 5/20/2013) (Entered: 05/20/2013) 05/22/2013 435 MEDIATION STATUS REPORT by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 5/22/2013) Modified text on 5/23/2013 (dhmS, COURT STAFF). (Entered: 05/22/2013) 05/28/2013 436 STATUS REPORT Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Attachments: # 1 Declaration of James G. Dallal re: Extension of Time to File Due to Technical Failure Pursuant to Civil Local Rule 5-1(e)(5))(Dallal, James) (Filed on 5/28/2013) (Entered: 05/28/2013) 05/30/2013 437 ORDER RE: DISCOVERY STATUS REPORTS. Signed by Judge Lucy H. Koh on May 30, 2013. (lhklc1, COURT STAFF) (Filed on 5/30/2013) (Entered: 05/30/2013) 05/31/2013 438 Transcript of Proceedings held on May 15, 2013, before Judge Lucy H. Koh. Court Reporter Raynee H. Mercado, CSR, Telephone number 510-451-7530, rayneeh@hotmail.com, raynee_mercado@cand.uscourts.gov. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 8/29/2013. (Related documents(s) 434 ) (rhm) (Filed on 5/31/2013) (Entered: 05/31/2013) 06/21/2013 439 OPPOSITION to ( 418 SUPPLEMENTAL MOTION to Certify Class ) filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Brown, Christina) (Filed on 6/21/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/21/2013) 06/21/2013 440 Supplemental Expert Report of Professor Kevin M. Murphy in Support of 439 Opposition to Motion filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit, # 2 Appendix)(Related document(s) 439 ) (Busch, Frank) (Filed on 6/21/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/21/2013) 06/21/2013 441 Declaration of Christina Brown in Support of 450 Defendants' Joint Adminstrative Motion to File Under Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Apple Inc.. (Brown, Christina) (Filed on 1182 6/21/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/21/2013 443 Declaration of Anne M. Selin In Support of 450 Defendants' Joint Administrative Motion to Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class Certification and Related Document filed by Google Inc.. (Selin, Anne) (Filed on 6/21/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/21/2013 444 Declaration of James M. Kennedy in Support of 450 Defendants' Joint Administrative Motion to Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class Certification and Related Document filed by Pixar. (Richardson, Chinue) (Filed on 6/21/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 442 EXHIBIT Expert Report of Kathryn Shaw, Ph.D re 439 Opposition to Motion filed by Adobe Systems Inc.. (Related document(s) 439 ) (Kahn, Lin) (Filed on 6/22/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 445 Declaration of Christina Brown in Support of 439 Opposition to Supplemental Class Certification Motion filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10 Exhibit 10)(Related document(s) 439 ) (Brown, Christina) (Filed on 6/22/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 446 DECLARATION of Lin W. Kahn in Support of 439 Opposition to Supplemental to Motion for Class Certification filed by Adobe Systems Inc.. (Attachments: # 1 Exhibit 1-10, part 1, # 2 Exhibit 1-10, part 2, # 3 Errata 11-20, # 4 Exhibit 21-27, # 5 Errata 28-30, part 1, # 6 Exhibit 28-30, part 2)(Related document(s) 439 ) (Kahn, Lin) (Filed on 6/22/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 447 Declaration of Lin W. Kahn in Support of 450 Joint Administrative Motion to File Under Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Adobe Systems Inc.. (Related document(s) 450 ) (Kahn, Lin) (Filed on 6/22/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 448 Declaration of Catherine T. Zeng in Support of 450 Administrative Motion to File Under Seal filed by Intuit Inc.. (Related document(s) 450 ) (Zeng, Catherine) (Filed on 6/22/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 449 Declaration of Frank Busch in Support of 450 Defendants Joint Administrative Motion to File Under Seal filed by Intel Corp.. (Busch, Frank) (Filed on 6/22/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 450 Joint Administrative Motion to File Under Seal Defendants' Opposition to Plaiintiffs' Supplemental Moiton in Support of Class Certification and Related Documents filed by Lucasfilm Ltd.. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4) (Sessions, Justina) (Filed on 6/22/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/22/2013 451 Declaration of JUSTINA K. SESSIONS in Support of 450 Joint Administrative Motion to File Under Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class Certification and Related Documents filed by Lucasfilm Ltd.. (Related document(s) 450 ) (Sessions, Justina) (Filed on 6/22/2013) Modified on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013) 06/27/2013 452 NOTICE OF ERRATA to 439 Opposition to Supplemental Class Certification Motion and 1183 440 Supplemental Expert Report of Professor Kevin M. Murphy by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Corrected Exhibit 7)(Brown, Christina) (Filed on 6/27/2013) Modified text on 6/28/2013 (dhmS, COURT STAFF). (Entered: 06/27/2013) 07/12/2013 453 Letter from Co-Lead Class Counsel re Notice of Settlement. (Harvey, Dean) (Filed on 7/12/2013) (Entered: 07/12/2013) 07/12/2013 454 Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Anne B. Shaver, # 2 Proposed Order, # 3 Exhibit, # 4 Exhibit, # 5 Exhibit, # 6 Exhibit)(Shaver, Anne) (Filed on 7/12/2013) (Entered: 07/12/2013) 07/12/2013 455 REPLY in Support of ( 418 SUPPLEMENTAL MOTION to Certify Class ) [REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 7/12/2013) Modified text on 7/15/2013 (dhmS, COURT STAFF). (Entered: 07/12/2013) 07/12/2013 456 Declaration of Anne B. Shaver in Support of 455 Plaintiffs' Reply in Support of Supplemental Class Certification Motion filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit, # 2 Exhibit, # 3 Exhibit)(Related document(s) 455 ) (Shaver, Anne) (Filed on 7/12/2013) Modified text on 7/15/2013 (dhmS, COURT STAFF). (Entered: 07/12/2013) 07/12/2013 457 Declaration of Edward E. Leamer in Support of 455 Reply to Opposition/Response [REDACTED] filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Related document(s) 455 ) (Shaver, Anne) (Filed on 7/12/2013) (Entered: 07/12/2013) 07/12/2013 458 Declaration of Non-Party Sheryl Sandberg in Support of 455 Reply to Opposition/Response [REDACTED] filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Related document(s) 455 ) (Shaver, Anne) (Filed on 7/12/2013) (Entered: 07/12/2013) 07/12/2013 459 CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 457 Declaration in Support, 456 Declaration in Support, 455 Reply to Opposition/Response, 458 Declaration in Support, (Shaver, Anne) (Filed on 7/12/2013) (Entered: 07/12/2013) 07/14/2013 460 ORDER REGARDING JULY 12, 2013 NOTICE OF SETTLEMENT LETTER. Signed by Judge Lucy H. Koh on 7/14/2013. (lhklc3, COURT STAFF) (Filed on 7/14/2013) (Entered: 07/14/2013) 07/19/2013 461 RESPONSE to ( 454 PLAINTIFFS ADMINISTRATIVE MOTION TO FILE UNDER SEAL PLAINTIFFS REPLY IN SUPPORT OF SUPPLEMENTAL MOTION FOR CLASS CERTIFICATION filed by Lucasfilm Ltd.. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E)(Sessions, Justina) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 462 JOINT RESPONSE to 454 Plaintiffs Administrative Motion To File Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Busch, Frank) (Filed on 7/19/2013) Modified on 7/23/2013 counsel posted document incorrectly as a motion and failed to link entry to related document (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 463 Declaration of Lin W. Kahn in Support of 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Adobe Systems Inc.. (Related document (s) 462 ) (Kahn, Lin) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 464 Declaration of Rowan T. Mason in Support of 462 Defendants Joint Response To Plaintiffs 1184 Administrative Motion To File Under Seal filed by Intuit Inc.. (Related document(s) 462 ) (Mason, Rowan) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 465 Declaration of Anne M. Selin in Support of 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Google Inc.. (Related document(s) 462 ) (Selin, Anne) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 466 Declaration of Frank Busch in Support of 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Intel Corp.. (Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 467 Proposed Order re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 468 STATUS REPORT re Mediation by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Brown, Christina) (Filed on 7/19/2013) (Entered: 07/19/2013) 07/19/2013 469 OBJECTIONS to Evidence in Plaintiffs' Reply in Support of Supplemental Class Certification Motion and Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D. re 457 Declaration of Edward E. Leamer , 455 Reply to Opposition/Response, by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Brown, Christina) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 470 REPLY in Support of 418 Supplemental Class Certification MOTION filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Exhibit Leamer)(Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013) Modified on 7/23/2013 incorrect event type selected when posting document. Entry linked to document #418 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 471 Declaration of Christina Brown in Support of 469 Objection to Reply Evidence filed byAdobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B)(Related document(s) 469 ) (Brown, Christina) (Filed on 7/19/2013) (Entered: 07/19/2013) 07/19/2013 472 EXHIBITS re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Exhibit B, # 2 Exhibit C, # 3 Exhibit D)(Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 473 EXHIBITS re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Exhibit F, # 2 Exhibit G, # 3 Exhibit H, # 4 Exhibit J, # 5 Exhibit K, # 6 Exhibit L, # 7 Exhibit M, # 8 Exhibit N, # 9 Exhibit O)(Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/19/2013 474 EXHIBITS re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Exhibit 2738, # 2 Exhibit 2739 (Part 1), # 3 Exhibit 2739 (Part 2), # 4 Exhibit 2739 (Part 3))(Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 1185 07/19/2013 475 Declaration of Christina Brown in Support of 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal filed by Apple Inc.. (Related document(s) 462 ) (Brown, Christina) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013) 07/20/2013 476 Proposed Order re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File Under Seal CORRECTION OF DOCKET # 467 . by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Busch, Frank) (Filed on 7/20/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/20/2013) 07/22/2013 477 STIPULATION WITH PROPOSED ORDER Substituting Counsel by Lucasfilm and Pixar filed by Pixar. (Henn, Emily) (Filed on 7/22/2013) (Entered: 07/22/2013) 07/22/2013 478 TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover for Court Reporter Raynee Mercado. (Harvey, Dean) (Filed on 7/22/2013) (Entered: 07/22/2013) 07/23/2013 479 MOTION TO ENFORCE LOCAL RULE 7-3(d)(1) AND STRIKE DEFENDANTS' IMPROPER SUR REPLY filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Responses due by 7/29/2013. (Attachments: # 1 Proposed Order)(Harvey, Dean) (Filed on 7/23/2013) (Entered: 07/23/2013) 07/23/2013 480 Declaration of DEAN M. HARVEY in Support of 479 MOTION TO ENFORCE LOCAL RULE 7-3(d)(1) AND STRIKE DEFENDANTS' IMPROPER SUR REPLY filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E) (Related document(s) 479 ) (Harvey, Dean) (Filed on 7/23/2013) (Entered: 07/23/2013) 07/24/2013 481 Order by Hon. Lucy H. Koh granting 477 Stipulation to Permit Keker & Van Nest LLP to Withdraw as Counsel for Lucasfilm.(lhklc3, COURT STAFF) (Filed on 7/24/2013) (Entered: 07/24/2013) 07/25/2013 482 NOTICE of Appearance by Robert Addy Van Nest Daniel Purcell, Eugene M. Paige, Justina K. Sessions (Van Nest, Robert) (Filed on 7/25/2013) (Entered: 07/25/2013) 07/26/2013 483 BRIEF Regarding the Impact of the Proposed Settlement on Plaintiffs' Supplemental Motion for Class Certification re 460 Order by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 7/26/2013) Modified text on 7/29/2013 (dhmS, COURT STAFF). (Entered: 07/26/2013) 07/26/2013 484 JOINT BRIEF Regarding the Impact of the Proposed Pixar and Lucasfilm Settlements on the Supplemental Class Certification Motion re 460 Order by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Brown, Christina) (Filed on 7/26/2013) Modified text on 7/29/2013 (dhmS, COURT STAFF). (Entered: 07/26/2013) 07/28/2013 485 OPPOSITION to ( 479 MOTION TO ENFORCE LOCAL RULE 7-3(d)(1) AND STRIKE DEFENDANTS' IMPROPER SUR REPLY )filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Proposed Order)(Brown, Christina) (Filed on 7/28/2013) Modified text on 7/29/2013 (dhmS, COURT STAFF). (Entered: 07/28/2013) 07/29/2013 486 NOTICE of Appearance by Daniel Edward Purcell (Purcell, Daniel) (Filed on 7/29/2013) (Entered: 07/29/2013) 07/29/2013 487 NOTICE of Appearance by Eugene Morris Paige (Paige, Eugene) (Filed on 7/29/2013) (Entered: 07/29/2013) 07/29/2013 488 NOTICE of Appearance by Justina Kahn Sessions (Sessions, Justina) (Filed on 7/29/2013) (Entered: 07/29/2013) 07/30/2013 489 Letter from Co-Lead Class Counsel re Notice of Settlement. (Harvey, Dean) (Filed on 1186 7/30/2013) (Entered: 07/30/2013) 08/01/2013 490 CASE MANAGEMENT STATEMENT filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 8/1/2013) (Entered: 08/01/2013) 08/08/2013 495 Minute Entry: Motion Hearing held on 8/8/2013 before Judge Lucy H. Koh (Date Filed: 8/8/2013) re 418 SUPPLEMENTAL MOTION to Certify Class filed by Michael Devine, Siddharth Hariharan, Mark Fichtner, Daniel Stover, Brandon Marshall, Further Case Management Conference held on 8/8/2013 before Judge Lucy H. Koh (Date Filed: 8/8/2013), Case referred to Private ADR.. Further Case Management Conference set for 10/3/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 8/8/2013) (Entered: 08/19/2013) 08/09/2013 491 MOTION for Leave to File Statement of Recent Decision filed by Apple Inc.. (Attachments: # 1 Exhibit 1 - Statement of Recent Decision, # 2 Proposed Order and Stipulation)(Riley, George) (Filed on 8/9/2013) (Entered: 08/09/2013) 08/12/2013 492 TRANSCRIPT ORDER by Apple Inc. for Court Reporter Lee-Anne Shortridge. (Brown, Christina) (Filed on 8/12/2013) (Entered: 08/12/2013) 08/12/2013 493 TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on 8/12/2013) (Entered: 08/12/2013) 08/19/2013 494 Transcript of Proceedings held on 8-8-13, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: leeanne_shortridge@cand.uscourts.gov. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this filing. Release of Transcript Restriction set for 11/18/2013. (Related documents(s) 492 ) (las, ) (Filed on 8/19/2013) (Entered: 08/19/2013) 08/23/2013 496 MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1 - Statement of Recent Decision, # 2 Proposed Order and Stipulation)(Harvey, Dean) (Filed on 8/23/2013) (Entered: 08/23/2013) 08/27/2013 497 CHART Related to 424 Defendants' Joint Response to Plaintiffs' Administrative Motion to File Under Seal and Suporting Declarations Filed on May 17, 2013 filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Related document(s) 424 ) (Selin, Anne) (Filed on 8/27/2013) Modified text on 8/28/2013 (dhmS, COURT STAFF). (Entered: 08/27/2013) 08/30/2013 498 MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Proposed Order)(Harvey, Dean) (Filed on 8/30/2013) (Entered: 08/30/2013) 09/19/2013 499 MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit, # 2 Proposed Order)(Dallal, James) (Filed on 9/19/2013) (Entered: 09/19/2013) 09/19/2013 500 Letter from Co-Lead Class Counsel and Counsel for Settling Defendants re Motion for Preliminary Approval of Class Action Settlements. (Harvey, Dean) (Filed on 9/19/2013) (Entered: 09/19/2013) 09/21/2013 501 MOTION for Preliminary Approval of Class Action Settlements; Memorandum of Points and Authorities in Support Thereof [REDACTED] filed by Michael Devine, Mark Fichtner, 1187 Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion Hearing set for 10/3/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 10/7/2013. Replies due by 10/15/2013. (Attachments: # 1 Proposed Order Granting Plaintiffs Motion for Conditional Class Certification and Preliminary Approval of Class Action Settlements with Defendants Intuit Inc., Lucasfilm, Ltd., and Pixar)(Cisneros, Lisa) (Filed on 9/21/2013) Modified text on 9/23/2013 (dhmS, COURT STAFF). (Entered: 09/21/2013) 09/21/2013 502 Declaration of Kelly M. Dermody in Support of 501 MOTION for Preliminary Approval [REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6)(Related document(s) 501 ) (Cisneros, Lisa) (Filed on 9/21/2013) Modified text on 9/23/2013 (dhmS, COURT STAFF). (Entered: 09/21/2013) 09/21/2013 503 Declaration of Joseph R. Saveri in Support of 501 MOTION for Preminary Approval of Class Action Settlement [REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1)(Related document (s) 501 ) (Cisneros, Lisa) (Filed on 9/21/2013) Modified text on 9/23/2013 (dhmS, COURT STAFF). (Entered: 09/21/2013) 09/21/2013 504 Administrative Motion to File Under Seal Portions of Plaintiffs' Motion for Preliminary Approval of Class Settlements filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Declaration Dean M. Harvey, # 8 Proposed Order)(Cisneros, Lisa) (Filed on 9/21/2013) (Entered: 09/21/2013) 09/25/2013 505 MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Proposed Order and Stipulation)(Cisneros, Lisa) (Filed on 9/25/2013) (Entered: 09/25/2013) 09/25/2013 506 NOTICE by Lucasfilm Ltd., Pixar of Letter to Attorneys General (Attachments: # 1 Letter) (Henn, Emily) (Filed on 9/25/2013) (Entered: 09/25/2013) 09/25/2013 507 NOTICE by Intuit Inc. of Mailing of Letter to Attorneys General Pursuant to 28 U.S.C. Section 1715 (Attachments: # 1 Exhibit)(Kiernan, David) (Filed on 9/25/2013) (Entered: 09/25/2013) 09/26/2013 508 JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Brandon Marshall, Daniel Stover. (Sessions, Justina) (Filed on 9/26/2013) Modified text on 9/30/2013 (dhmS, COURT STAFF). (Entered: 09/26/2013) 09/30/2013 509 ORDER by Judge Lucy H. Koh granting in part and denying in part (307) Administrative Motion to File Under Seal; granting in part and denying in part (335) Administrative Motion to File Under Seal; granting in part and denying in part (346) Administrative Motion to File Under Seal; granting in part and denying in part (394) Administrative Motion to File Under Seal; granting in part and denying in part (271) Administrative Motion to File Under Seal; granting in part and denying in part (283) Administrative Motion to File Under Seal in case 5:11-cv-02509-LHK (lhklc4, COURT STAFF) (Filed on 9/30/2013) (Entered: 09/30/2013) 09/30/2013 510 ORDER by Judge Lucy H. Koh granting 491 Motion for Leave to File; granting 496 Motion for Leave to File; granting 498 Motion for Leave to File; granting 499 Motion for Leave to File; granting 505 Motion for Leave to File. ****THIS IS A TEXT-ONLY ENTRY. THERE IS NO DOCUMENT ASSOCIATED WITH THIS DOCKET ENTRY**** (lhklc1, COURT STAFF) (Filed on 9/30/2013) (Entered: 09/30/2013) 10/01/2013 511 CLERKS NOTICE CONTINUING FURTHER CASE MANAGEMENT CONFERENCE AND MOTION FOR PRELIMINARY APPROVAL Further Case Management Conference set for 10/21/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. Motion Hearing set for 1188 10/21/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. *****THIS IS A TEXT-ONLY NOTICE. THERE IS NO DOCUMENT ASSOCIATED WITH THIS DOCKET ENTRY***** (mpb, COURT STAFF) (Filed on 10/1/2013) (Entered: 10/01/2013) 10/01/2013 Set/Reset Hearing re 511 Clerks Notice, Clerks Notice Continuing Motion Hearing, Set Motion and Deadlines/Hearings,,, (mpb, COURT STAFF) (Filed on 10/1/2013) (Entered: 10/01/2013) 10/07/2013 512 DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, Expert Report of Professor Kevin M. Murphy by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Brown, Christina) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 513 DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, Defendants' Joint Administrative Motion for Leave to Supplement the Record by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Supplemental Declaration of Professor Kevin M. Murphy) (Brown, Christina) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 514 REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by Adobe Systems Inc.. (Attachments: # 1 Plaintiffs Motion for Class Certification, # 2 Exhibit 14 to Declaration of Ann B. Shaver in Support of Plaintiffs Motion for Class Certification, # 3 Exhibit 4 to Declaration of Dean Harvey in Support of Plaintiffs Reply, # 4 Exhibit 26 to Harvey Decl., # 5 Exhibit 29 to Harvey Decl.)(Kahn, Lin) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 515 REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by Google Inc.. (Attachments: # 1 Exhibit Exhibit A to March 1, 2013 Joint Discovery Status Report)(Selin, Anne) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 516 REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by Google Inc.. (Attachments: # 1 Exhibit 14 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification (Part 1), # 2 Exhibit 14 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification (Part 2), # 3 Exhibit 14 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification (Part 3), # 4 Exhibit 14 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification (Part 4), # 5 Exhibit 19 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 6 Exhibit 21 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 7 Exhibit 25 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 8 Exhibit 26 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 9 Exhibit 27 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 10 Motion to Strike Leamer Report)(Selin, Anne) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 517 DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, 273 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,,,, Defendants' Opposition to Plaintiffs' Motion for Class Certification by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Declaration of Christina Brown in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 2 Exhibit 1, # 3 Exhibit 2, # 4 Exhibit 3, # 5 Exhibit 4, # 6 Exhibit 5, # 7 Exhibit 6, # 8 Exhibit 9, # 9 Exhibit 10, # 10 Exhibit 11, # 11 Exhibit 12, # 12 Exhibit 13, # 13 Exhibit 14 (part 1), # 14 Exhibit 14 (part 2), # 15 Exhibit 15, # 16 Exhibit 16, # 17 Exhibit 17 (part 1), # 18 Exhibit 17 (part 2), # 19 Exhibit 17 (part 3), # 20 Exhibit 18 (part 1), # 21 Exhibit 18 (part 2), # 22 Exhibit 19, # 23 Exhibit 20, # 24 Exhibit 21, # 25 Exhibit 22, # 26 Exhibit 23, # 27 Exhibit 25, # 28 Exhibit 26, # 29 Exhibit 27)(Brown, Christina) (Filed on 10/7/2013) (Entered: 10/07/2013) 1189 10/07/2013 518 REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Expert Report of Edward E. Leamer, Ph.D., # 2 Expert Report of Professor Kevin M. Murphy (part 1), # 3 Expert Report of Professor Kevin M. Murphy (part 2), # 4 Expert Report of Professor Kevin M. Murphy (part 3), # 5 Reply Expert Report of Edward E. Leamer, Ph.D.)(Brown, Christina) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 519 DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, EXPERT REPORT OF EDWARD E. LEAMER, PH.D ISO October 1, 2012 Motion to Certify Class (redacted version at Docket No. 190) by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 520 DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D ISO December 10, 2012 Reply Brief (redacted version at Docket No. 249) by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/07/2013 521 DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, PLAINTIFFS' OPPOSITION TO DEFENDANTS' JOINT ADMIN. MOT. FOR LEAVE TO SUPPLEMENT THE RECORD ISO THEIR OPPOSITION TO THE MOT. FOR CLASS CERT. AND MOT. TO STRIKE DR. LEAMER'S EXPERT REPORT, Docket No. (redacted version at Docket No. 270) by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration DECLARATION OF EDWARD E. LEAMER IN OPPOSITION TO DEFENDANTS ADMINISTRATIVE MOTION, Docket No. (redacted version at Docket No. 270-1)) (Cisneros, Lisa) (Filed on 10/7/2013) (Entered: 10/07/2013) 10/17/2013 522 NOTICE of Substitution of Counsel by Gregory P. Stone AND CONSENT ORDER (Stone, Gregory) (Filed on 10/17/2013) (Entered: 10/17/2013) 10/17/2013 523 CASE MANAGEMENT STATEMENT [UPDATED] filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp.. (Van Nest, Robert) (Filed on 10/17/2013) (Entered: 10/17/2013) 10/18/2013 524 STIPULATION WITH PROPOSED ORDER Regarding Substitution of Counsel for Intel Corporation filed by Intel Corp.. (Stone, Gregory) (Filed on 10/18/2013) (Entered: 10/18/2013) 10/20/2013 525 RESPONSE to 523 the Non-Settling Defendants' Unauthorized Supplemental Filing of Updated Case Management Statement by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D)(Dermody, Kelly) (Filed on 10/20/2013) Modified text on 10/21/2013 (dhmS, COURT STAFF). (Entered: 10/20/2013) 10/20/2013 526 Order by Hon. Lucy H. Koh granting (524) Stipulation in case 5:11-cv-02509LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on 10/20/2013) (Entered: 10/20/2013) 10/21/2013 527 Case Management Order by Hon. Lucy H. Koh; Order granting in part and denying in part (504) Administrative Motion to File Under Seal in case 5:11-cv-02509-LHK. Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK (lhklc1, COURT STAFF) (Filed on 10/21/2013) (Entered: 10/21/2013) 10/21/2013 534 Minute Entry: Motion Hearing held on 10/21/2013 before Judge Lucy H. Koh (Date Filed: 10/21/2013) re 501 MOTION for Preliminary Approval of Class Action Settlements [REDACTED] filed by Michael Devine, Siddharth Hariharan, Mark Fichtner,1190 Stover, Daniel Brandon Marshall, Further Case Management Conference held on 10/21/2013 before Judge Lucy H. Koh (Date Filed: 10/21/2013). Further Case Management Conference set for 12/18/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 10/21/2013) (Entered: 10/28/2013) 10/22/2013 528 TRANSCRIPT ORDER by Apple Inc. for Court Reporter Lee-Anne Shortridge. (Brown, Christina) (Filed on 10/22/2013) (Entered: 10/22/2013) 10/22/2013 529 TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on 10/22/2013) (Entered: 10/22/2013) 10/22/2013 530 TRANSCRIPT ORDER by Intel Corp. for Court Reporter Lee-Anne Shortridge. (Stone, Gregory) (Filed on 10/22/2013) (Entered: 10/22/2013) 10/24/2013 531 ORDER by Judge Lucy H. Koh granting 418 Motion to Certify Class (lhklc1, COURT STAFF) (Filed on 10/24/2013) (Entered: 10/24/2013) 10/25/2013 532 DOCUMENT E-FILED UNDER SEAL by Court Staff. (Attachments: # 1 Certificate/Proof of Service)(lhklc1, COURT STAFF) (Filed on 10/25/2013) (Entered: 10/25/2013) 10/25/2013 533 NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 501 MOTION for Preliminary Approval of Class Action Settlements [REDACTED] Notice Of Filing Revised And Supplemental Settlement Documents (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6 Exhibit F, # 7 Exhibit G)(Dermody, Kelly) (Filed on 10/25/2013) (Entered: 10/25/2013) 10/28/2013 535 NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 501 MOTION for Preliminary Approval of Class Action Settlements [REDACTED] Notice of Filing Pursuant to October 21, 2013 Case Management Order (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3)(Cisneros, Lisa) (Filed on 10/28/2013) (Entered: 10/28/2013) 10/28/2013 536 DOCUMENT E-FILED UNDER SEAL re 527 Order on Administrative Motion to File Under Seal, Attachment D to Plaintiffs' Settlement Agreement with Intuit by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 10/28/2013) (Entered: 10/28/2013) 10/28/2013 537 NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover re 527 Order on Administrative Motion to File Under Seal, Second Notice of Filing Pursuant to the Court's October 21, 2013 Case Management Order (Attachments: # 1 Exhibit 1)(Cisneros, Lisa) (Filed on 10/28/2013) (Entered: 10/29/2013) 10/30/2013 538 NOTICE by Intel Corp. re 430 Redacted Document,, OF FILING REVISED REDACTED INTEL CORP. DOCUMENTS FILED IN RESPONSE TO PLAINTIFFS' ADMINISTRATIVE MOTION TO FILE UNDER SEAL PLAINTIFFS' MOTION IN SUPPORT OF CLASS CERTIFICATION AND RELATED DOCUMENTS (Attachments: # 1 Declaration OF BRADLEY S. PHILLIPS IN SUPPORT, # 2 Exhibit A, # 3 Exhibit B (Part 1 of 10), # 4 Exhibit B (Part 2 of 10), # 5 Exhibit B (Part 3 of 10), # 6 Exhibit B (Part 4 of 10), # 7 Exhibit B (Part 5 of 10), # 8 Exhibit B (Part 6 of 10), # 9 Exhibit B (Part 7 of 10), # 10 Exhibit B (Part 8 of 10), # 11 Exhibit B (Part 9 of 10), # 12 Exhibit B (Part 10 of 10))(Phillips, Bradley) (Filed on 10/30/2013) (Entered: 10/30/2013) 10/30/2013 539 Transcript of Proceedings held on 10-21-13, before Judge Lucy H. Koh. Court Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: leeanne_shortridge@cand.uscourts.gov. Per General Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber until the deadline for the Release of Transcript Restriction.After that date it may be obtained through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than 5 business days from date of this 1191 filing. Release of Transcript Restriction set for 1/28/2014. (Related documents(s) 528 ) (las, ) (Filed on 10/30/2013) (Entered: 10/30/2013) 10/30/2013 10/31/2013 540 Order by Hon. Lucy H. Koh granting 501 Motion for Settlement. (Attachments: # 1 Claim Form, # 2 Notice)(lhklc1, COURT STAFF) (Filed on 10/30/2013) (Entered: 10/30/2013) Set/Reset Hearing re 540 Order on Motion for Settlement Final Approval Hearing re Pixar, Lucasfilms & Intuit set for 5/1/2014 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 10/31/2013) (Entered: 11/01/2013) PACER Service Center Transaction Receipt 11/17/2013 20:28:22 PACER Login: lc0019 Description: Client Code: 3462 Docket Report Search Criteria: 5:11-cv-02509-LHK Billable Pages: 30 Cost: 3.00 1192 No. 13-80223 In the United States Court Of Appeals For the Ninth Circuit __________________________ IN RE HIGH-TECH EMPLOYEE ANTITRUST LITIGATION _________________________ Petition for permission to appeal from the United States District Court Northern District of California The Honorable Lucy H. Koh, Presiding Case No. 5:11-2509-LHK PLAINTIFFS-RESPONDENTS’ CERTIFICATE OF SERVICE LIEFF CABRASER HEIMANN & BERNSTEIN, LLP Kelly M. Dermody Brendan P. Glackin Dean M. Harvey 275 Battery Street, 29th Floor San Francisco, CA 94111-3339 Telephone: (415) 956-1000 Facsimile: (415) 956-1008 JOSEPH SAVERI LAW FIRM Joseph R. Saveri Joshua P. Davis Lisa J. Leebove James G. Dallal 505 Montgomery Street, Suite 625 San Francisco, CA 94111 Telephone: (415) 500-6800 Facsimile: (415) 500-6803 Co-Lead Class Counsel 1141607.1 CERTIFICATE OF SERVICE I hereby certify that on November 18, 2013, I electronically filed the documents noted below with the Clerk of the Court for the United States Court of Appeals for the Ninth Circuit by using the appellate CM/ECF system. I certify that all particpants in the case are registered CM/ECF users and that service will be acomplished by the appellate CM/ECF system. The documents served via the Ninth Circuit’s CM/ECF system include: 1. PLAINTIFFS’ RESPONSE TO PETITION FOR LEAVE TO APPEAL A CLASS CERTIFICATION ORDER PURSUANT TO FEDERAL RULE OF CIVIL PROCEDURE 23(f); 2. SUPPLEMENTAL EXCERPTS OF RECORD, VOLS. I-IV (Public Portions); and 3. PLAINTIFFS-RESPONDENTS’ MOTION TO SEAL PORTIONS OF THEIR SUPPLEMENTAL EXCERPTS OF RECORD In addition, I hereby certify that on November 18, 2013, I served via electronic mail and overnight delivery through a third party commercial carrier the following documents to counsel noted in the accompanying service list: 1. SUPPLEMENTAL EXCERPTS OF RECORD, VOLS. I-VI (Public and Provisionally Sealed Portions); 1141607.1 -1- Dated: November 18, 2013 LIEFF CABRASER HEIMANN & BERNSTEIN, LLP By: /s/ Brendan P. Glackin LIEFF CABRASER HEIMANN & BERNSTEIN, LLP Kelly M. Dermody Brendan P. Glackin Dean M. Harvey 275 Battery Street, 29th Floor San Francisco, CA 94111-3339 Telephone: 415.956.1000 Facsimile: 415.956.1008 1141607.1 -2- SERVICE LIST Robert A. Mittelstaedt George Riley Craig A. Waldman Michael F. Tubach David Kiernan Lisa Chen JONES DAY Christina J. Brown 555 California Street, 26th Floor O'MELVENY & MYERS LLP San Francisco, CA 94104 Two Embarcadero Center, 28th Floor ramittelstaedt@jonesday.com San Francisco, CA 94111 cwaldman@jonesday.com griley@omm.com dkiernan@jonesday.com mtubach@omm.com Tel.: (415) 626-3939 lisachen@omm.com Fax: (415) 875-5700 cjbrown@omm.com Tel.: (415) 984-8700 Counsel for Defendant Adobe Systems Inc. Fax: (415) 984-8701 Counsel for Defendant Apple Inc. Robert Addy Van Nest Eugene M. Paige Daniel Purcell Justina Sessions KEKER & VAN NEST 633 Battery Street San Francisco, CA 94111-1809 rvannest@kvn.com epaige@kvn.com dpurcell@kvn.com jsessions@kvn.com Tel.: (415) 391-5400 Fax: (415) 397-7188 Gregory P. Stone Bradley S. Phillips Gregory M. Sergi John P. Mittelbach MUNGER, TOLLES & OLSON LLP 355 South Grand Avenue, 35th Floor gregory.stone@mto.com brad.phillips@mto.com gregory.sergi@mto.com john.mittelbach@mto.com Los Angeles, California 90071-1560 Telephone: (213) 683-9100 Facsimile: (213) 687-3702 Lee H. Rubin Edward D. Johnson MAYER BROWN LLP Two Palo Alto Square 3000 El Camino Real, Suite 300 Palo Alto, CA 94306-2112 lrubin@mayerbrown.com wjohnson@mayerbrown.com Tel.: (650) 331-2000 Fax: (650) 331-2060 Counsel for Defendant Intel Corp. Kristen A. Rowse MAYER BROWN LLP 350 South Grand Avenue, 25th Floor Los Angeles, CA 90071-2112 krowse@mayerbrown.com Tel.: (213) 229 5137 Fax: (213) 576 8139 Counsel for Defendant Google Inc. 1141607.1 -3-

Disclaimer: Justia Dockets & Filings provides public litigation records from the federal appellate and district courts. These filings and docket sheets should not be considered findings of fact or liability, nor do they necessarily reflect the view of Justia.


Why Is My Information Online?