Butler v. Jimmy John's Franchise, LLC et al
Filing
233
ORDER DENYING Plaintiff Donald Conrad's 225 Sealed Motion for Reconsideration. [Public Redacted Version]. Signed by Chief Judge Nancy J. Rosenstengel on 4/26/2021. (cab).
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IN THE UNITED STATES DISTRICT COURT
FOR THE SOUTHERN DISTRICT OF ILLINOIS
DONALD CONRAD,
On Behalf of Himself & All Others
Similarly Situated,
Plaintiff,
v.
Case No. 18-CV-00133-NJR
JIMMY JOHN’S FRANCHISE, LLC,
JIMMY JOHN’S ENTERPRISES, LLC,
and
JIMMY JOHN’S LLC,
Defendants.
MEMORANDUM AND ORDER
ROSENSTENGEL, Chief Judge:
Plaintiff Donald Conrad asks the Court to reconsider its February 24
Memorandum and Order for four reasons. Unfortunately for Conrad, however, none of
his reasons is persuasive. So for the reasons explained below, the Court denies his Motion
for Reconsideration.
BACKGROUND
The Court incorporates the Background section of the February 24 Memorandum
and Order (Doc. 223). Conrad’s specific objections are set forth below.
LEGAL STANDARD
“Judges are permitted to reconsider their rulings in the course of a litigation.” In re
Text Messaging Antitrust Litig., 630 F.3d 622, 627 (7th Cir. 2010). But “[t]he district court’s
‘opinions are not intended as mere first drafts, subject to revision and reconsideration at
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a litigant’s pleasure.’” A&C Constr. & Installation, Co. WLL v. Zurich Am. Ins. Co., 963 F.3d
705, 709 (7th Cir. 2020) (quoting Quaker Alloy Casting Co. v. Gulfco Indus., Inc., 123 F.R.D.
282, 288 (N.D. Ill. 1988)). A motion for reconsideration, therefore, “is not a forum to
relitigate losing arguments; it may be granted only if the movant can ‘demonstrate a
manifest error of law or fact or present newly discovered evidence.’” Ohr v. Latino Express,
Inc., 776 F.3d 469, 478 (7th Cir. 2015) (quoting Anderson v. Catholic Bishops of Chi., 759 F.3d
645, 653 (7th Cir. 2014)).
ANALYSIS
I.
Argument 1: “The Court mistakenly thought Dr. Singer’s summaries of
the WSR data were actually the results of his regressions.”
In its February 24 Memorandum and Order, the Court referred to a chart from Dr.
Singer’s report that showed how the average manager was reflected in the WSR data as
earning
about
per-hour, or almost
per year—far below the actual average wage of
. (Mem. & Order at 45 (citing Singer Report at 34, Doc. 115-3)). Conrad
objects to how the Court referred to this as a “finding” of Dr. Singer’s regression. For
example, the Court said that “the regression yields an average of
” (Id.
(emphasis added)). Instead, Conrad notes that the chart reflects “the wage data as it was
produced by Jimmy John’s.” (Pl.’s’ Mot. at 13). He also asserts that the Court contradicted
itself by not passing on the quality of the WSR data while also excluding Dr. Singer’s
testimony because of the switcher problem. (Id. at 17). The Court disagrees.
Simply put, the Court did not misapprehend Dr. Singer’s report. True, the chart
refers to the raw data: it is not the product of Dr. Singer’s regressions. Yet the switcher
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marks a systemic failure of Dr. Singer’s “models fail to adjust for those two percent of
WSRs that do not consistently record employee wages as per-shift or per-hour.” (Mem.
& Order at 40). Small as it seems, that two percent of employees comprise 25 percent of
managers. (Ordover Rebuttal at 11). Dr. Ordover recognized this and aptly demonstrated
how “’separating Dr. Singer’s regression by manager pay type results in a finding that
managers paid on an hourly basis had an average wage suppression of approximately
two percent, while salaried managers suffered no suppression at all.’” (See Mem. & Order
at 13 (quoting Ordover Report at 21, Doc. 133-56)). Conrad wrote off the switcher problem
as “’mathematically irrelevant’” and moved on. (See id. at 44 (quoting Singer Rebuttal
at 28, Doc. 185-2)). But “on issues affecting class certification,” the Court need not “simply
assume the truth of the matters asserted by the plaintiff.” Bell v. PNC Bank, Nat’l Ass’n,
800 F.3d 360, 377 (7th Cir. 2015). Indeed, “[t]he ‘rigorous analysis’ requirement ‘applies
to expert testimony critical to proving class certification requirements.’” Howard v. Cook
Cty. Sherriff’s Office, 989 F.3d 587, 601 (7th Cir. 2021) (quoting In re Blood Reagants Antitrust
Litig., 783 F.3d 183, 187 (3d Cir. 2015)). Conrad’s argument amounts to semantics aimed
to distort the focus of the Court’s opinion. 1
Conrad’s argument that the switcher problem is benign because Dr. Singer’s models reveal impact in
percentage terms—rather than dollars and cents—is similarly unavailing. As Jimmy John’s ably explains
in its brief, “[e]xpressing the relationship in percentage terms (i.e., in log terms) would not eliminate the
measurement errors created by recording [wages] in two different metrics.” (Jimmy John’s Resp. at 6
(describing how if, for example, one were to record snowfall in inches one day and centimeters the next,
then calculating the percentage change in snowfall without adjusting for the different metrics would still
lead to erroneous results)). At any rate, Conrad never raised this argument before, so it is not properly
before the Court now. See Caisse Nationale de Credit Agricole v. CBI Indus., Inc., 90 F.3d 1264, 1270 (7th Cir.
1996) (“Reconsideration is not an appropriate forum for rehashing previously rejected arguments or
arguing matters that could have been heard during the pendency of the previous motion.”).
1
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II.
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Argument 2: “Dr. Singer’s regressions do not yield inflates estimates of
antitrust impact.”
Conrad claims that “[t]he Court overlooked thirteen pages of Dr. Singer’s
explanation why there was no econometric or statistical reason to suspect that these 2%
would skew his results.” (Pl.’s’ Mot. at 14). But in those pages, Dr. Singer conceded that
the switcher problem was not accounted for by the “worker fixed effects,” (Singer
Rebuttal at 24, Doc. 185-2); characterized it as a mere “[r]andom measurement error,” (id.
at 25); and used a graph, not specific to this case, purporting to show that the switcher
problem is “effectively washed away when the regression has a large number of data
points,” (id. at 25-28). The Court rejected those arguments, recognizing that the potential
for error caused by the switcher problem was heightened because it affected a significant
subsection of employees (managers). (Mem & Order at 44-45).
Now, on reconsideration, Conrad presents another expert report, this time in the
guise of a “supplemental declaration.” He contends that Dr. Singer excluded the switcher
data, redid his regressions, and confirmed his original finding of antitrust impact. Thus,
Conrad asks the Courts to consider this new report and reverse course.
Consideration of Dr. Singer’s supplemental declaration is inappropriate because it
is not newly discovered evidence. Jimmy John’s first raised the switcher problem in its
July 2020 Motion to Exclude. Dr. Singer then prepared a rebuttal report, where he argued
that it was a random measurement error. Conrad could have shown that then; but
instead, he tried meeting his burden by relying on general principles. At the hearing, the
Court specifically asked Conrad’s counsel about the switcher problem; he summarily
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claimed that the two-percent measurement error was harmless. (Tr. at 31–33). He also
conceded that the “fixed effects” only control for factors fixed over time. (Id.). Yet that
would exclude 25 percent of managers whose wages were not consistently recorded as
per-shift or per-hour. Conrad wants a redo by submitting a supplemental declaration,
but the Court already gave him a fair chance to state his case. He failed to meet his
burden.
Along those lines, the litigants, the public, and the Court all share an interest in
finality. Naturally, Jimmy John’s disputes the assertions in Dr. Singer’s supplemental
declaration. Indeed, Jimmy John’s raises several arguments challenging his “fixes,”
paving the way for a Daubert challenge within a Daubert challenge. Adding to the
confusion, this dispute is linked to a motion for class certification filed in December 2019
that relies heavily on Dr. Singer’s first report—the one that the Court excluded. More
active management is necessary now “to ensure that the certification decision is not
unjustifiably delayed.” Fed. R. Civ. P. 26(a) advisory committee’s note 2003 amendment;
see, e.g., Kempner Mobile Elecs., Inc. v. S.W. Bell Mobile Sys., 428 F.3d 706, 713 (7th Cir. 2005)
(affirming denial of leave to file expert rebuttal report because it “would have a
prolonged delay in the already protracted proceedings requiring additional discovery
and increased costs”). The Court will not consider this not-so-new evidence.
III.
Argument 3: “In the alternative, the appropriate answer to the Court’s
concerns is to exclude the 2% of switchers, not the entire opinion.”
Conrad argues that the Court should not exclude Dr. Singer’s report in whole
cloth. Rather, he hopes to salvage “Dr. Singer’s separate, stand-alone regressions for in-
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shoppers and drivers that did not use manager data, or the damages methodology.”
(Pl.’s’ Mot. at 6). But those regressions alone cannot establish that common issues
predominate over all Jimmy John’s employees, including managers, as presented in
Conrad’s Motion for Class Certification. And when confronted with expert testimony,
“the trial judge must determine at the outset” whether the “methodology can be applied
to the facts in issue.” Daubert v. Merrell Dow Pharms., Inc., 509 579, 923–93 (1993). Yet
because Conrad himself would be excluded from the results, a piecemeal report cannot
establish that antitrust impact is capable of proof through evidence that is common to the
class. 2
IV.
Argument 4: “The Court applied contradictory legal standards to Dr.
Ordover and Dr. Singer.”
Conrad previously argued that Dr. Ordover erred by not controlling for countylevel economic conditions. The Court rejected that argument because “ ’the exclusion of
major variables or the inclusion of improper variables may diminish the probative value
of a regression model’” but “’do not generally preclude admissibility.’” (Mem. & Order
at 50 n.7 (quoting In re Urethane Antitrust Litig., 768 F.3d 1245, 1260-61 (10th Cir. 2014))).
Now, Conrad points to a variable that Jimmy John’s expert, Dr. Ordover, added to his
regression to control for the switcher problem. He says that the Court contradicted itself
by citing the same case when it chose not to exclude Dr. Ordover’s over Conrad’s
objection about Dr. Ordover’s dummy variable. Relatedly, Conrad says that it was
2In
a footnote, Conrad suggests redefining the class. (Pl.’s’ Reply at 5 n.7). He may very well choose to do
so, but not through a motion for reconsideration in a Daubert challenge.
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contradictory for the Court to exclude Dr. Singer’s report because he “omit[ed] from his
own regression the new endogenous variable that Dr. Ordover created.” (Pl.’s Mot. at 17).
To that end, Conrad rehashes the “endogeneity bias” argument. He again says that
Dr. Ordover’s models are unreliable because he “created a new right-hand side variable
attempting to guess the unit of measurement.” (Pl.’s’ Mot. at 19). The Court rejected that
argument, noting that Conrad provided “scant proof that the variable Dr. Ordover
created by unpooling the wage data is merely a function of the dependent variable.”
(Mem. & Order at 47). Again, Conrad says Dr. Ordover’s “fix” for the switcher problem
was flawed because his “additional ‘control’ variables . . . are mechanically determined
by the value of the left-hand-side variable, injecting circularity or endogeneity.” (Pl.’s’
Reply at 2). Again, the Court disagrees.
As alluded to in the Memorandum and Order, endogeneity bias “occurs when the
dependent and independent variables affect each other.” See John E. Lopatka, Economic
Authority and the Limits of Expertise in Antitrust Cases, 90 Cornell L.R. 617, 698 n.498 (2005).
It underscores the adage “Correlation does not equal causation.” When a model suffers
from endogeneity bias, it shrugs the possibility that an unobserved factor may be driving
any correlation between the independent and dependent variables. To account for
endogeneity bias, statisticians neutralize those unobserved factors to avoid conflating
correlation with causation. Here, Dr. Ordover adjusted for the switcher problem by
adding a dummy variable to the right-hand-side of the equation. Because the WSR data
does not specify whether a given wage was per-shift or per-hour, Dr. Ordover inferred
that wages below
were per-shift, and that wages above
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were per hour (the few
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other words, knowing that Mr. Acosta was paid on a shift
basis when his wage was recorded as
does not tell us his
hourly rate.
(Ordover Rebuttal at 14). The Court still agrees with this assessment: Dr. Ordover’s
models do not suffer from endogeneity bias because there is not a lockstep relationship
between an employee’s wages and whether that employee was paid per-hour or per-shift.
To illustrate, consider the distinguishable case that Conrad cites for support, In re
Polypropylene Carpet Antitrust Litigation, which involved a supposed price-fixing scheme
orchestrated by several carpet manufacturers. 93 F. Supp. 2d 1348, 1351 (N.D. Ga. 2000).
At class certification, an expert for the putative class used “multiple regression analysis”
to “identify any difference between the actual prices of polypropylene carpet and the
forecasted competitive prices during that period.” Id. Rather than using total
manufacturing cost as an independent variable, however, the expert instead used the
ratio of the price of carpet to fiber costs as the dependent variable. Id. As a result, the
defendants claimed that the expert’s analysis suffered from endogeneity bias because it
assumed that increases in fiber costs corresponded with the overall price of
polypropylene carpet. See id. at 1360. That correlation, they argued, had “nothing to do
with collusive activity” and undermined the significance of other factors like variables
for demand, changes in income, and the entry of competition. Id. But the district judge
sided with the putative class, noting that “changes in fiber costs reflect changes in the
variable costs of producing polypropylene carpet.” Id. at 1362. Indeed, the parties agreed
that fiber costs made up “seventy percent of total costs depending on the style,” so
changes in the “remaining variable costs . . . did not significantly affect the high
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