MERCK & CO., INC. et al v. UNITED STATES DEPARTMENT OF HEALTH AND HUMAN SERVICES et al

Filing 1

COMPLAINT against All Defendants ( Filing fee $ 400 receipt number 0090-6188695) filed by AMGEN INC., ELI LILLY AND COMPANY, ASSOCIATION OF NATIONAL ADVERTISERS, INC., MERCK & CO., INC.. (Attachments: #1 Declaration of C. Garthwaite, #2 Declaration of R. Dhar, #3 Declaration of R. El-Dada for Merck, #4 Declaration of J. Oleksiw for Lilly, #5 Declaration of D. Marek for Amgen, #6 Civil Cover Sheet, #7 Summons to U.S. Department of Health and Human Services, #8 Summons to Alex M. Azar II, #9 Summons to U.S. Centers for Medicare and Medicaid Services, #10 Summons to Seema Verma, #11 Summons to U.S. Attorney General, #12 Summons to U.S. Attorney for DC)(Bress, Richard)

Case 1:19-cv-01738-APM Document 1-2 Filed 06/14/19 Page 1 of 43

UNITED STATES DISTRICT COURT
FOR THE DISTRICT OF COLUMBIA
MERCK & CO., INC., ELI LILLY AND
COMPANY,
AMGEN
INC.,
and
ASSOCIATION
OF
NATIONAL
ADVERTISERS, INC.,
Plaintiffs,
v.
Case No. __________________
UNITED STATES DEPARTMENT OF
HEALTH AND HUMAN SERVICES,
ALEX M. AZAR II, CENTERS FOR
MEDICARE & MEDICAID SERVICES, and
SEEMA VERMA,
Defendants.

EXPERT DECLARATION OF PROFESSOR RAVI DHAR
JUNE 14, 2019

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TABLE OF CONTENTS
I.

QUALIFICATIONS .............................................................................................................3

II.

ASSIGNMENT......................................................................................................................4

III. SUMMARY OF CONCLUSIONS ......................................................................................6
IV. PROVIDING WAC IN DIRECT-TO-CONSUMER PHARMACEUTICAL
TELEVISION ADVERTISING IS LIKELY TO MISLEAD CONSUMERS INTO
OVERESTIMATING THEIR ACTUAL OUT-OF-POCKET COSTS FOR MANY
DRUGS AND IS NOT LIKELY TO LEAD TO MORE INFORMED CHOICES ........7
A. Overview of the Anchoring Process and Consumer Decision Making ..................... 8
B. WAC in DTC Television Advertising Is Likely to Anchor Consumers’ Expectations
about Out-Of-Pocket Costs ......................................................................................... 10
C. As a Result of the Anchoring Bias, the Rule is Likely to Confuse and Mislead
Consumers into Overestimating Their Out-of-Pocket Costs for Many Drugs ...... 12
V.

BY LEADING MANY CONSUMERS TO OVERESTIMATE THEIR ACTUAL OUTOF-POCKET COSTS, THE RULE IS LIKELY TO DETER THEM FROM SEEKING
INFORMATION FROM A DOCTOR OR OBTAINING TREATMENT ...................17
A. DTC Pharmaceutical Advertising Encourages Patients to Seek Treatment .......... 17
B. The Rule Is Likely to Deter Many Consumers from Contacting Their Doctors by
Leading Consumers to Overestimate Their Out-of-Pocket Costs ........................... 19
C. The Disclaimer in the Rule is Unlikely to Correct the Biased Expectations of OutOf-Pocket Costs Caused by the Rule for Many Consumers or the Rule’s Effect of
Diminishing the Likelihood that Consumers Will Initiate a Conversation with Their
Doctors .......................................................................................................................... 20

VI. THE JAMA STUDY DOES NOT SUPPORT THE RULE ............................................23

2

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I.

QUALIFICATIONS
1.

I am the George Rogers Clark Professor of Management and Marketing at the Yale

School of Management. I am also the Director of the Yale Center for Customer Insights at the
School of Management at Yale University, New Haven, Connecticut. I also have an affiliated
appointment as a Professor of Psychology at the Department of Psychology, Yale University. In
addition, I serve on the editorial board of peer-reviewed consumer research journals such as the
Journal of Academy of Marketing Science, Journal of Consumer Psychology, Journal of Consumer
Research, Journal of Marketing, and Marketing Letters. Previously, I was the Associate Editor of
Journal of Marketing Research, the Area Editor of Marketing Science, and the Associate Editor of
Journal of Consumer Research. My academic work focuses on consumer behavior, consumer
psychology, branding, marketing management, marketing strategy, survey methodology, and
evaluation.
2.

My teaching responsibilities at Yale University’s School of Management include

two doctoral courses that examine advanced research topics in the area of consumer behavior,
judgment, and decision-making. I also teach or have taught several different courses for graduate
students who are enrolled in the MBA program or the Executive MBA program at Yale: Consumer
Behavior, E-Business and Marketing, Marketing Strategy, Marketing Management, Marketing of
Financial Services, and Strategic Marketing Leadership. I have taught and given seminars to midlevel and senior-level executives in more than a dozen countries in North and South America, Asia,
and Europe. Additionally, I have worked as a consultant or adviser to companies on marketingrelated issues in different types of industries (e.g., health, consumer products, high technology,
and financial services). I have served as an expert witness on issues related to marketing and
marketing research on more than 50 cases, including cases involving health-related products.
3.

I hold a Ph.D. and Master of Science in Business Administration from the

University of California at Berkeley. My doctoral dissertation (“Consumer Preference for a NoChoice Option”) was in the area of consumer decision-making. I have published more than seventy
papers in journals, proceedings, and as book chapters, including leading marketing, psychology,
and management journals, such as the Harvard Business Review, Journal of Behavioral Decision
Making, Journal of Business, Journal of Consumer Psychology, Journal of Consumer Research,
Journal of Marketing Research, Journal of Personality and Social Psychology, Management
Science, Marketing Science, Organizational Behavior and Human Decision Processes, Sloan
3

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Management Review, and other peer-reviewed and industry journals.
4.

Several of my publications received research awards such as the William O’Dell

Award (“Consumer Choice between Hedonic and Utilitarian Goods,” 2005). The William O’Dell
Award is presented to the Journal of Marketing Research article that has made the most significant,
long-term contribution to marketing theory, methodology, and/or practice. I was also awarded the
2012 Distinguished Scientific Contribution Award from the Society of Consumer Psychology,
which is given annually to honor a scholar who has made significant and lasting contributions in
the field of consumer psychology. A study of 475 marketing faculty at top 30 schools (as of spring
2017), ranked me as one of four most productive marketing faculty (among those with at least one
publication per year in one of the four top marketing journals over the 10-year period between
2007 and 2016), tying for rank 2 through 4 with two other faculty.1
5.

Prior to earning my Ph.D., I earned an undergraduate degree in engineering from

the Indian Institute of Technology and a master’s degree in business administration from the Indian
Institute of Management. A detailed listing of my educational background and publications is set
forth in the curriculum vitae, which is attached to the end of this declaration as Appendix A.
6.

In my work as a marketing professor and as a consultant, I have conducted,

supervised, and/or evaluated more than 500 surveys and experiments relating to different aspects
of consumer behavior. My current research focuses on consumers’ decision making, the manner
in which consumers acquire and process information when forming product perception and
preferences, the effect of product attributes and information presentation on consumer purchase
and consumption decisions, and the effect of different “marketing mix” activities (such as
promotions and advertising) on consumer purchase decisions.
II.

ASSIGNMENT
7.

I understand that Plaintiffs Merck & Co.. Inc., Eli Lilly and Company, Amgen Inc.,

and the Association of National Advertisers, Inc., intend to bring a lawsuit against Defendants,
Department of Health and Human Services (“HHS”) and Centers for Medicare and Medicaid
Services (“CMS”), among others, and to request a stay of implementation of its “Regulation to
1

van Osselaer, Stijn M. J., and Sarah Lim, “Research Productivity of Faculty at 30 Leading Marketing
Departments,” Marketing Letters, (2019): 1-17, at pp. 1-3, 8 (Table 3).

4

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Require Drug Pricing Transparency” (hereafter “the Rule” or “42 C.F.R. § 403”).2
8.

CMS, which falls under HHS, issued the Rule.3 The Rule requires that television

advertisements for prescription drugs and biological products contain the following statement:
“The list price for a [30-day supply of] [typical course of treatment with] [name of prescription
drug or biological product] is [insert list price]. If you have health insurance that covers drugs,
your cost may be different.”4 In particular, “this requirement applies to any advertisement for a
prescription drugs or biological product distributed in the United States, for which payment is
available, directly or indirectly, under titles XVIII or XIX of the Social Security Act, except for a
prescription drugs or biological product that has a list price, as defined herein, of less than $35 per
month for a 30-day supply or typical course of treatment.”5 The Rule was published on May 10,
2019 and is effective starting on July 9, 2019.6
9.

I have been asked by counsel for Plaintiffs in the above-captioned matter to provide

an expert opinion on what the Rule’s required statement is likely to convey to consumers and what
impact, if any, the required statement is likely to have on a consumer’s behavior. In addition, I
have been asked to opine on whether the required statement is likely to enable consumers to
estimate more precisely their actual out-of-pocket costs and lead to more informed choices. I have
also been asked to evaluate the Journal of American Medical Association article cited extensively
in the Federal Register publication of the Rule (hereafter “the JAMA article” or “the JAMA
study”).7
10.

In forming my opinion, I drew on my knowledge, education, and experience in

marketing and consumer behavior developed over the past several decades. The materials that I

2

3

4
5
6
7

Department of Health and Human Services, Centers for Medicare & Medicaid Services, 42 C.F.R. § 403,
“Medicare and Medicaid Programs; Regulation To Require Drug Pricing Transparency,” Federal Register, Vol.
84, No. 91, Friday, May 10, 2019, Rules and Regulations (hereafter “the Rule” or “42 C.F.R. § 403”), at pp.
20732-20758.
42 C.F.R. § 403, at p. 20732; “About CMS,” CMS.gov, https://www.cms.gov/about-cms/about-cms.html (viewed
May 31, 2019).
42 C.F.R. § 403, at p. 20732 (sic, brackets in the original).
42 C.F.R. § 403, at p. 20732 (sic).
42 C.F.R. § 403, at p. 20732.
Garrett, Jace B., William B. Tayler, Ge Bai, Mariana P. Socal, Antonio J. Trujillo, and Gerard F. Anderson,
“Consumer Responses to Price Disclosure in Direct-to-Consumer Pharmaceutical Advertising,” JAMA Internal
Medicine, Vol. 179, No. 3 (2019): 435-437 (“the JAMA article” or “the JAMA study”), cited e.g., in 42 C.F.R. §
403, at p. 20734.

5

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relied upon in developing my opinions are disclosed in Appendix B. In addition, I relied on general
principles of marketing research and survey and experiment research as well as consumer
information processing and decision-making.
11.

I have been assisted in this matter by employees of Analysis Group, Inc. I am being

compensated at the rate of $850 per hour. In addition, I receive compensation for work Analysis
Group performs in support of my work. My compensation is not contingent on the nature of my
findings or on the outcome of this litigation.
12.

My analyses and opinions in this declaration are based on information available to

me as of the date of this declaration. I reserve the right to supplement my testimony and this
declaration in response to any further information provided by the parties, and/or in light of
additional documents or testimony brought to my attention after the date of my signature below,
prior to the resolution of this matter.
III.

SUMMARY OF CONCLUSIONS
13.

Based on my review of relevant materials in this case, as well as my education,

background, and professional experience, it is my opinion that:
a. Providing WAC in direct-to-consumer (“DTC”) pharmaceutical television
advertising is likely to mislead consumers into overestimating their actual out-ofpocket costs for many drugs and is not likely to lead to more informed choices.
b. By leading many consumers to overestimate their actual out-of-pocket costs, the Rule
is likely to deter them from seeking information from a doctor or obtaining treatment.
c. The disclaimer in the Rule is unlikely to correct the biased expectations of out-ofpocket costs caused by the Rule for many consumers or the Rule’s effect of
diminishing the likelihood that consumers will initiate a conversation with their
doctors.
d. The JAMA study does not support the Rule; HHS overstates and misinterprets the
JAMA study findings, ignores the study’s implication that the Rule (even with the
disclaimer) will likely cause many consumers to vastly overestimate their out-ofpocket costs and reduce their likelihood of asking their doctors about the drug, and
ignores the study’s shortcomings that limit its generalizability.
6

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IV.

PROVIDING WAC IN DIRECT-TO-CONSUMER PHARMACEUTICAL
TELEVISION ADVERTISING IS LIKELY TO MISLEAD CONSUMERS INTO
OVERESTIMATING THEIR ACTUAL OUT-OF-POCKET COSTS FOR MANY
DRUGS AND IS NOT LIKELY TO LEAD TO MORE INFORMED CHOICES
14.

The Rule requires the disclosure of a drug’s “list price.”8 HHS explains that “list

price” means the “Wholesale Acquisition Cost” or “WAC” for a prescription drug.9 WAC is not
the price at which prescription drugs are sold to consumers. 10 Rather, HHS defines it as “the
manufacturer’s list price for the prescription drug or biological product to wholesalers or direct
purchasers in the United States, not including prompt pay or other discounts, rebates or reductions
in price, for the most recent month for which the information is available, as reported in wholesale
price guides or other publications of drug or biological product pricing data.”11
15.

HHS contends that disclosing WAC is likely to provide consumers important

information to permit them to make informed decisions about their prescription drugs.12 But in
actuality, the Rule is likely to mislead consumers by biasing their expectation of their out-of-pocket
costs for many prescription drugs.
16.

Based on my review of Dr. Craig Garthwaite’s declaration, I understand that the

actual out-of-pocket costs paid by most consumers for prescription drugs are significantly lower
than a prescription drug’s WAC.13
17.

As I will demonstrate below, the Rule is likely to mislead consumers into believing

that their out-of-pocket costs for many drugs are larger than they actually are through the
psychological mechanism known as “anchoring.” Far from promoting informed choice, using
WAC as an anchor is likely to have the opposite effect—it is likely to cause consumers to place
undue importance on WAC in their assessment of their out-of-pocket costs. Further, the salience
of WAC in relation to other inputs that consumers need to consider in order to make an informed
decision about whether to pursue a course of treatment— for example, information about their outof-pocket costs, side effects, and alternative therapies—is likely to result in less informed
8
9
10
11
12
13

42 C.F.R. § 403, at p. 20732.
42 C.F.R. § 403, at p. 20732.
42 C.F.R. § 403, at p. 20758.
42 C.F.R. § 403, at p. 20758.
E.g., 42 C.F.R. § 403, at pp. 20732-20735, 20738.
Expert Declaration of Professor Craig Garthwaite, June 14, 2019 (“Garthwaite Declaration”), at ¶ 10.

7

Case 1:19-cv-01738-APM Document 1-2 Filed 06/14/19 Page 8 of 43

decisions.14
18.

In what follows, section IV.A discusses academic research on the anchoring

process to explain the role of price information provided to consumers in making judgments
involving consumers’ out-of-pocket costs. Section IV.B discusses why WAC would serve as such
an anchor for consumers’ expectations about out-of-pocket costs. Section IV.C discusses why
WAC anchor is likely to mislead consumers by biasing their expectations that their out-of-pocket
costs are larger than they actually are in the marketplace for most consumers.
A. Overview of the Anchoring Process and Consumer Decision Making
19.

Consumers often make judgments and decisions with incomplete and/or imperfect

information.15 As a result, “people rely on a limited number of heuristic principles” that lead to
systematic biases in decisions.16 One of the most established heuristic principles leading to such
biases is the “anchoring” effect.17
20.

Anchoring manifests in the following way. Studies show that when a person makes

a numerical judgement, she is biased by initial numerical information she received even when the
anchoring information is arbitrary and irrelevant. 18 For example, a study found that when
participants were asked to estimate the percentage of members of the United Nations that are
14

15

16

17

18

Zhang, Shi, and Arthur B. Markman, “Processing Product Unique Features: Alignability and Involvement in
Preference Construction,” Journal of Consumer Psychology, Vol. 11, No. 9 (2001): 13-27, at p. 13; Kivetz, Ran,
and Itamar Simonson, “The Effects of Incomplete Information on Consumer Choice,” Journal of Marketing
Research, Vol. 37, No. 4 (2000): 427-448, at p. 427.
“Many decisions are based on beliefs concerning the likelihood of uncertain events such as the outcome of an
election, the guilt of a defendant, or the future value of the dollar.” Tversky, Amos, and Daniel Kahneman,
“Judgment under Uncertainty: Heuristics and Biases,” Science, Vol. 185, No. 4157 (1974): 1124-1131, at p. 1124.
“Some of the most important decisions consumers make involve ambiguity and uncertainty.” Kahn, Barbara E.,
and Rakesh K. Sarin, “Modeling Ambiguity in Decisions under Uncertainty,” Journal of Consumer
Research, Vol. 15, No. 2 (1988): 265-272, at p. 265.
Tversky, Amos, and Daniel Kahneman, “Judgment under Uncertainty: Heuristics and Biases,” Science, Vol. 185,
No. 4157 (1974): 1124-1131, at p. 1124. See also, Kahneman, Daniel, “New Challenges to the Rationality
Assumption,” Journal of Institutional and Theoretical Economics, Vol. 150, No. 1 (1994): 18-36, at p. 18.
Mullainathan, Sendhil, and Richard H. Thaler, “Behavioral Economics,” NBER Working Paper Series, No. 7948,
(2000): 1-13, at p. 2, https://www.nber.org/papers/w7948.pdf.
“Three heuristics of judgment, labeled representativeness, availability and anchoring, were described in the 1974
review, along with a dozen systematic biases, including non-regressive prediction, neglect of base-rate
information, overconfidence and overestimates of the frequency of events that are easy to recall.” Kahneman,
Daniel, “Maps of Bounded Rationality: A Perspective on Intuitive Judgment and Choice,” Nobel Prize Lecture
(2002): 449-489, at p. 465.
Tversky, Amos, and Daniel Kahneman, “Judgment under Uncertainty: Heuristics and Biases,” Science, Vol. 185,
No. 4157 (1974): 1124-1131, at p. 1128.

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African countries, their estimates were influenced by first observing the results of the researcher
spinning a wheel containing numbers 0 to 100. 19 Although individuals usually make some
adjustments from the anchor before arriving at a numerical judgment, their judgements tend to end
up around the starting anchors.20 The anchoring bias is robust, evidenced by considerable research
in a variety of contexts. 21 And it prevails in payment scenarios, both hypothetical and real.22
21.

As I will discuss below, the proposed disclosure of WAC in direct-to-consumer

television advertisements is likely to bias consumers’ expectations about their out-of-pocket costs
for many drugs in the direction of WAC, the anchor. Such expectations would be biased and result
in consumers overestimating the out-of-pocket costs for many drug purchases because, as I will
discuss in Section IV.C, WAC for a prescription drug is generally substantially higher than—and

19

20

21

22

Tversky, Amos, and Daniel Kahneman, “Judgment under Uncertainty: Heuristics and Biases,” Science, Vol. 185,
No. 4157 (1974): 1124-1131, at p. 1128.
“In many situations, people make estimates by starting from an initial value that is adjusted to yield the final
answer. The initial value, or starting point, may be suggested by the formulation of the problem, or it may be the
result of a partial computation. In either case, adjustments are typically insufficient.” Tversky, Amos, and Daniel
Kahneman, “Judgment under Uncertainty: Heuristics and Biases,” Science, Vol. 185, No. 4157 (1974): 11241131, at p. 1128. See also, Epley, Nicholas, and Thomas Gilovich, “Are Adjustments Insufficient?,” Personality
and Social Psychology Bulletin, Vol. 30, No. 4 (2004): 447-460, at p. 447; Strack, Fritz, and Thomas Mussweiler,
“Explaining the Enigmatic Anchoring Effect: Mechanisms of Selective Accessibility,” Journal of Personality
and Social Psychology, Vol. 73, No. 3 (1997): 437-446, at pp. 437-438.
“Anchoring effects are elicited easily in the laboratory, the field, and the classroom—a robustness that helps
explain why anchoring has been used to explain such diverse phenomena as preference reversals, the hindsight
bias, subadditivity in likelihood judgment, social comparison, and egocentric biases, among others.” Epley,
Nicholas, and Thomas Gilovich, “The Anchoring-and-Adjustment Heuristic: Why the Adjustments Are
Insufficient,” Psychological Science, Vol. 17, No. 4 (2006): 311-318, at p. 311 (references omitted).
“Given how often consumers are called upon to make numeric judgments, anchoring could be important across
many payment contexts. In hypothetical scenarios, anchoring effects have been shown with credit card payments,
negotiation outcomes, and buying and selling prices. … A smaller body of work has considered anchoring effects
with incentive-compatible designs. Work by Ariely, Loewenstein, and Prelec (2003), as well as Maniadis, Tufano,
and List (2014) employs designs with real money and goods at stake. Both of these articles show data consistent
with classic anchoring effects.” Jung, Minah H., Hannah Perfecto, and Leif D. Nelson, “Anchoring in Payment:
Evaluating a Judgmental Heuristic in Field Experimental Settings,” Journal of Marketing Research, Vol. 53, No.
3 (2016): 354-368, at p. 355 (references partially omitted). “[T]he combined uncertainty of personal valuation
and socially appropriate payment should make customers especially susceptible to anchors.” Jung, Minah H.,
Hannah Perfecto, and Leif D. Nelson, “Anchoring in Payment: Evaluating a Judgmental Heuristic in Field
Experimental Settings,” Journal of Marketing Research, Vol. 53, No. 3 (2016): 354-368, at p. 355 (references
omitted). See also, Chandrashekaran, Rajesh, and Dhruv Grewal, “Anchoring Effects of Advertised Reference
Price and Sale Price: The Moderating Role of Saving Presentation Format,” Journal of Business Research, Vol.
59, No. 10-11 (2006): 1063-1071, at p. 1064. Ariely, Dan, George Loewenstein, and Drazen Prelec, “‘Coherent
Arbitrariness’: Stable Demand Curves without Stable Preferences,” The Quarterly Journal of Economics, Vol.
118, No. 1 (2003): 73-105, at pp. 73, 76, 78; Frederick, Shane W., and Daniel Mochon, “A Scale Distortion
Theory of Anchoring,” Journal of Experimental Psychology: General, Vol. 141, No. 1 (2012): 124-133, at pp.
124, 132.

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often not directly related to—a consumer’s out-of-pocket cost.23 And, as I will discuss in Section
V, this overestimation will likely impact how consumers compare the costs and benefits of talking
to a doctor about a particular treatment or getting treated.
B. WAC in DTC Television Advertising Is Likely to Anchor Consumers’
Expectations about Out-Of-Pocket Costs
22.

Rather than WAC providing meaningful information to assist consumers in making

informed judgments, WAC is likely to serve as an anchor that biases consumers’ estimates of their
out-of-pocket costs.
23.

Research on the Affordable Care Act has shown that the manner in which

consumers make health-related decisions is influenced by the context in which the information is
provided. 24 For several reasons, the context here (a brief disclosure of WAC in a television
advertisement) will likely enhance the anchoring effect of that disclosure.
24.

First, WAC is the only price-related information required by the Rule to be

disclosed to consumers in the advertisement and, as such, is likely to become a salient point
entering into their assessment. Research finds that a “consumer’s attention is drawn to salient
attributes of goods” and that “[c]onsumers attach disproportionately high weight to salient
attributes.” 25 , 26 As a result, information that is not explicitly provided (e.g., insurance plan
specifics27) is likely to be underweighted in arriving at the out-of-pocket costs estimate, while the

23
24

25

26

27

Garthwaite Declaration, at ¶¶ 22, 67.
Taylor, Erin Audrey, Katherine Grace Carman, Andrea Lopez, Ashley Muchow, Parisa Roshan, and Christine
Eibner,
Consumer
Decisionmaking
in
the
Health
Care
Marketplace,
RAND,
2016,
https://www.rand.org/pubs/research_reports/RR1567.html. See also, Dhar, Ravi, and Margarita Gorlin, “A Dual‐
System Framework to Understand Preference Construction Processes in Choice,” Journal of Consumer
Psychology, Vol. 23, No. 4 (2013): 528-542, at p. 529.
Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer, “Salience and Consumer Choice,” Journal of Political
Economy, Vol. 121, No. 5 (2013): 803-843, at pp. 803, 805. See also, “Highly accessible values are generally
overweighted, and when considered as possible answers to a question, they become potent anchors. … These
effects of salience and anchoring play a central role in treatments of judgment and choice.” Kahneman, Daniel,
“A Perspective on Judgment and Choice: Mapping Bounded Rationality,” American Psychologist, Vol. 58, No.
9 (2003): 697-720, at p. 716. See also, Frederick, Shane, Nathan Novemsky, Jing Wang, Ravi Dhar, and Stephen
Nowlis, “Opportunity Cost Neglect,” Journal of Consumer Research, Vol. 36, No. 4 (2009): 553-561.
WAC in an advertisement may be particularly salient for the 34% of Americans who find it “difficult” (24%) or
“very difficult” (10%) to afford their drugs (a statistic reported by HHS, 42 C.F.R. § 403, at p. 20735).
Out-of-pocket costs vary significantly by, among other things, cost-sharing elements such as copayments,
coinsurance, and deductibles. Garthwaite Declaration, at ¶¶ 18-19.

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salient information, the so-called “list price,” is likely to be overweighted.28 Further, it is easy for
a consumer to assign value to WAC (a numerical dollar amount) whereas assigning value to more
abstract concepts, like the benefits of a drug, is more challenging.29 As a result, the Rule is likely
to cause consumers to place undue importance on WAC, rather than balance it with other
considerations consumers need to make an informed decision.
25.

Additionally, unique aspects of television advertising are likely to enhance the

anchoring effect of a WAC disclosure. Television advertisements are characterized by “fleeting
messages that have a very short life span” with little “opportunity to examine [them] in
considerable detail.” 30 WAC will be displayed for a few fleeting moments in the television
advertisement, which are not likely to provide the consumer the opportunity to process the
information at her own pace, much less the opportunity to process the complex detail needed to
accurately understand what WAC represents. Thus, consumers may not process much more than
the dollar value itself, rather than what that dollar value likely means vis-à-vis the consumer’s
actual out-of-pocket costs. Likewise, WAC is to be presented to consumers while they are likely
to be in a “low-involvement” state—watching television and not motivated to make much effort
with respect to that information.31 That is, the disclosure of WAC is unlikely to trigger immediate

28

29

30

31

E.g., Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer, “Salience and Consumer Choice,” Journal of
Political Economy, Vol. 121, No. 5 (2013): 803-843, at pp. 803, 805.
“[P]eople focus primarily on alignable differences of options rather than on nonalignable differences,” and the
degree of involvement in a decision is likely to affect participants’ attention to nonalignable differences, i.e., a
higher degree of task involvement would increase the processing of nonalignable information. Zhang, Shi and
Arthur B. Markman, “Processing Product Unique Features: Alignability and Involvement in Preference
Construction,” Journal of Consumer Psychology, Vol. 11, No. 1 (2001): 13-27, at pp. 19, 25. See also, Kivetz,
Ran, and Itamar Simonson, “The Effects of Incomplete Information on Consumer Choice,” Journal of Marketing
Research, Vol. 37, No. 4 (2000): 427-448, at p. 427.
“TV and radio are characterized by fleeting messages that have a very short life span; newspapers are generally
discarded soon after being read. Magazines, however, are generally read over several days and are often kept for
reference […] One benefit of the longer life of magazines is that reading occurs at a less hurried pace and there
is more opportunity to examine ads in considerable detail.” Belch, George E., and Michael A. Belch, Advertising
and Promotion: An Integrated Marketing Communications Perspective, Sixth Edition, New York, NY: McGrawHill, 2003, at p. 400.
“[T]he special quality of television advertising impact is low involvement, as compared with higher involvement
for magazine advertising.” Krugman, Herbert E., “The Measurement of Advertising Involvement,” Public
Opinion Quarterly, Vol. 30, No. 4 (1966): 583-596, at p. 584. “Magazine ads generate more brainwave activity
in the beta-range than the television ads. Relative to TV, magazine ads generate more left-brain activity.”
Zaichkowsky, Judith L., “Conceptualizing Involvement,” Journal of Advertising, Vol. 15, No. 2 (1986): 4-34, at
p. 11; see also, Park, C. Whan, and S. Mark Young, “Consumer Response to Television Commercials: The Impact
of Involvement and Background Music on Brand Attitude Formation,” Journal of Marketing Research, Vol. 23,
No. 1 (1986): 11-24.

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further research or inquiry beyond the passive absorption of the information when a consumer is
in a low-involvement state and not motivated to fully process the information.32
26.

For these reasons, many consumers exposed to WAC are likely to use it as an

anchor or a starting value when estimating their out-of-pocket costs for a prescription drug and
making decisions about whether to discuss that treatment with their doctor. Indeed, HHS’s
understanding and objective is for WAC to anchor consumers’ perceptions: “Arming a beneficiary
with basic price information will provide him or her with an anchor price or a reference comparison
to be used when making decisions about therapeutic options.”33 HHS even states that Medicare
and Medicaid beneficiaries can use the “anchor price … to make informed decisions about their
care, including whether the difference between the list price and what they actually pay out of
pocket is reasonable.”34
27.

Thus, although HHS repeatedly suggests that the Rule is likely to allow consumers,

especially Medicare and Medicaid beneficiaries, to “make informed decisions about their care,
including whether the difference between the list price and what they actually pay out of pocket is
reasonable,” 35 it would actually do no such thing. Instead, because WAC is the only price
information required by the Rule, salient, easy to evaluate (as a numeric dollar value), and provided
briefly on TV when consumers are more likely to be in a low-involvement state, the WAC value
is likely to bias consumers’ expectations about out-of-pocket costs—consumers are likely to base
those expectations on WAC anchor.
C. As a Result of the Anchoring Bias, the Rule is Likely to Confuse and Mislead
Consumers into Overestimating Their Out-of-Pocket Costs for Many Drugs
28.

Because WAC is likely to be the salient input into consumers’ perceptions of their

out-of-pocket costs for prescription drugs—either through anchoring and/or the reference to “list
price” as discussed below—such consumers are likely to be misled into assuming those out-of32

33
34
35

“Health care information can be complex.… We tend to assume that simply providing information will result in
a level playing field for all. However, many consumers lack the skills, knowledge, and motivation to access
credible sources, process information, and make informed choices.” Peters, Ellen, Judith Hibbard, Paul Slovic,
and Nathan Dieckmann, “Numeracy Skill and the Communication, Comprehension, and Use of Risk-Benefit
Information,” Health Affairs, Vol. 26, No. 3 (2007): 741-748, at p. 742.
42 C.F.R. § 403, at p. 20735.
42 C.F.R. § 403, at p. 20737.
42 C.F.R. § 403, at p. 20737; see also, pp. 20732-20734, 20736, 20738.

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pocket costs are much higher than they actually would be.
29.

I understand from Dr. Garthwaite that WAC for a prescription drug is the price that

is charged by manufacturers to wholesalers and is generally substantially higher than—and often
not related to—a consumer’s out-of-pocket cost.36 Thus, because the disclosure of WAC in DTC
television advertising will function as an anchor, as explained above, it is likely to lead consumers
to overestimate their out-of-pocket costs for many drugs.
30.

Even aside from bias due to anchoring, the Rule is likely to mislead consumers due

to HHS’s decision to refer to WAC in advertisements as “list price.” 37 For most consumer
products, a consumer expects a product’s advertised “list price” to be closely related to the amount
at which the consumer ordinarily purchases a product. In fact, the government compares the
disclosed WAC to the MSRP (a type of “list price”) for automobile purchases, noting that the
Rule’s objective is to provide consumers an “anchor price, such as an MSRP for automobiles, to
gauge the reasonableness of the various price quotes.”38 Thus, HHS’s objective is for consumers
to draw on their experience with MSRP and “list price” disclosures. However, while a consumer
may negotiate additional discounts from the MSRP, she usually pays a sum that is close to—and
directly related to—the MSRP. As discussed above, for most consumers, a prescription drug’s outof-pocket costs is nothing like an MSRP, with which a consumer is likely to be familiar. WAC is
the price at which prescription drugs are sold to wholesalers (net of rebates and discounts), but it
is not charged directly to consumers and is not representative of the price that most consumers
pay.39
31.

In addition to the misleading effect on consumers of the term “list price” in

television advertisements, the bias due to anchoring on WAC is likely to further mislead consumers
into overestimating their out-of-pocket costs for many drugs. “[W]hen an uncertain numeric entity
is evaluated [i.e., the out-of-pocket cost of the advertised drug], higher anchors [i.e., WAC] should

36
37
38

39

Garthwaite Declaration, at ¶¶ 14, 22, 67.
42 C.F.R. § 403, p. 20732.
“Medicare and Medicaid Programs; Regulation to Require Drug Pricing Transparency,” Centers for Medicare &
Medicaid Services, October 18, 2018, https://www.federalregister.gov/documents/2018/10/18/201822698/medicare-and-medicaid-programs-regulation-to-require-drug-pricing-transparency (viewed May 31,
2019).
Garthwaite Declaration, at ¶¶ 14, 22, 67; footnote 5.

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produce higher estimates.”40 This is true for several reasons. First, as discussed above, consumers
are susceptible to numerical anchors even when they know that they are arbitrary. For example, in
assessing how much participants in a study were willing to pay for a given item, in arriving at a
dollar value, they were influenced by the last two digits of their social security number (also
presented as a dollar value).41 Second, people tend to overweight nominal values relative to real
values.42 In particular, economic transactions can be represented in either nominal terms (e.g.,
salary) or real terms (e.g., salary adjusted for inflation). Even when consumers are aware of this
distinction, judgments are often biased towards nominal values, which are relatively simpler to
process and are more salient.43 In the current context, where the so-called “list price” is analogous
to the nominal value and the out-of-pocket cost is the real value, these findings suggest that even
if consumers know that they will pay only a percentage of the “list price,” and even if they know
the exact conversion between the “list price” and their out-of-pocket costs, they are still likely to
overweight the nominal WAC value in their decision. Third, because of the complex and varying
structure of individual insurance plans discussed above, it is extremely challenging even for
motivated and knowledgeable consumers to approximate their out-of-pocket costs from the
advertised “list price.”
32.

Indeed, this anchoring effect manifests in the JAMA study on which HHS relies. In

that study, participants who saw an advertisement for a fictitious drug with a “price” of $15,500
per month, assumed their out-of-pocket costs would be on average $2,787/month.44 While we do
40

41

42

43

44

Jung, Minah H., Hannah Perfecto, and Leif D. Nelson, “Anchoring in Payment: Evaluating a Judgmental Heuristic
in Field Experimental Settings,” Journal of Marketing Research, Vol. 53, No. 3 (2016): 354-368, at p. 355.
Ariely, Dan, George Loewenstein, and Drazen Prelec, “‘Coherent Arbitrariness’: Stable Demand Curves without
Stable Preferences,” The Quarterly Journal of Economics, Vol. 118, No. 1 (2003): 73-105, at pp. 73, 76, 78. See
also, Frederick, Shane W., and Daniel Mochon, “A Scale Distortion Theory of Anchoring,” Journal of
Experimental Psychology: General, Vol. 141, No. 1 (2012): 124-133.
“[R]esponses of the participants in [] surveys departed systematically from standard economic prescription in a
manner suggestive of money illusion. … [W]e interpret money illusion as a bias in the assessment of the real
value of transactions, induced by their nominal representation. … Money illusion… arises in large part because
it is considerably easier and more natural to think in nominal rather than in real terms.” Shafir, Eldar, Peter
Diamond, and Amos Tversky, “Money Illusion,” The Quarterly Journal of Economics, Vol. 112, No. 2 (1997):
341-374, at pp. 366-367.
Raghubir, Priya, and Joydeep Srivastava, “Effect of Face Value on Product Valuation in Foreign
Currencies,” Journal of Consumer Research, Vol. 29, No. 3 (2002): 335-347, at p. 335. See also, Wertenbroch,
Klaus, Dilip Soman, and Amitava Chattopadhyay, “On the Perceived Value of Money: The Reference
Dependence of Currency Numerosity Effects,” Journal of Consumer Research, Vol. 34, No. 1 (2007): 1-10, at p.
1.
JAMA article, at p. 437.

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not know the “actual” out-of-pocket cost of this drug because it is fictitious and we do not know
the particulars of each participant’s insurance plan, if any (out-of-pocket costs differ greatly from
consumer to consumer and even for the same consumer over the course of the year), 45 per
Dr. Garthwaite’s analysis, the out-of-pocket costs for large portions of the population are much
lower for any drug. For example, according to Dr. Garthwaite, for nearly all of Medicaid recipients
(almost 65 million Americans or 21% of the population), the out-of-pocket cost is a flat copayment
of $8 or less, regardless of WAC.46 Thus, for about 21% of US consumers in the high-price nodisclaimer group, the actual out-of-pocket costs are $8 or less (assuming the sample is
representative of the US population). That contrasts with the implied range for 95% of respondents
in the high-price no-disclaimer group from $1,839 to $3,735.47 As a result, a substantial number
of participants overestimated their out-of-pocket costs by over 20,000%.48
33.

A similar overestimation is true for participants covered by commercial insurance.

Specifically, 156 million Americans (49% of the population) are enrolled in employer-sponsored
insurance, of which 99% have a yearly cap on their out-of-pocket spending (i.e., once the consumer
reaches his or her annual limit, he or she will pay nothing out of pocket).49 For those on employersponsored plans with three or more tiers of cost-sharing for prescription drugs (82% of all covered
workers), copays average “$11 for first-tier drugs, $33 for second-tier drugs, $59 for third-tier
drugs, and $105 for fourth-tier drugs.”50 While the tier of the drug cannot be known for certain

45

46
47

48
49
50

Garthwaite Declaration, at ¶ 53. It appears that the JAMA study collected only high-level data on the type of
participants’ insurance coverage: whether or not they had insurance, and if they did, if they had a high deductible
or prescription drug coverage. (JAMA article, at p. 436, Table 1.) It is not clear whether the JAMA study collected
information on whether participants were Medicaid beneficiaries, Medicare beneficiaries (beyond reporting that
68 out of 580 participants, or 12%, were between the ages of 55-74), commercially insured, and, if so, whether
they reached their yearly cap at the time. The JAMA article does not report on how the expected out-of-pocket
costs varied across subgroups defined by this information.
Garthwaite Declaration, at ¶¶ 20, 34-36; see also footnote 45.
That is, the 95% confidence interval around the $2,787 mean. $1,839 = $2,787 - 1.96 x (5209.57 / √116); $3,735
= $2,787 + 1.96 x (5209.57 / √116). “Confidence Intervals,” Yale University, Department of Statistics,
http://www.stat.yale.edu/Courses/1997-98/101/confint.htm (viewed June 7, 2019). Using similar calculations, the
implied range for 99% of respondents in the high-price no-disclaimer group is from $1,542 to $4,033. $1,542 =
$2,787 - 2.575 x (5209.57 / √116); $4,033 = $2,787 + 2.575 x (5209.57 / √116).
($1,839 - $8) / $8 = 22,887%.
Garthwaite Declaration, at ¶¶ 20, 25; see also, footnote 45.
Claxton, Gary, Matthew Rae, Michelle Long, Anthony Damico and Heidi Whitmore, “Employer Health Benefits:
2018 Annual Survey,” Kaiser Family Foundation, 2018, at p. 155, http://files.kff.org/attachment/ReportEmployer-Health-Benefits-Annual-Survey-2018.

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from this hypothetical example, even the highest tier drug under that copay structure is only $105
on average.51,52
34.

Thus, the expected out-of-pocket costs for more than 60% of the population (almost

all of Medicaid beneficiaries and the employees with the plans with three or more tiers of costsharing), 53 the out-of-pocket costs would be far lower than the average $2,787/month or the
expected spend of $1,839 to $3,735 for 95% of respondents in this group, demonstrating that the
$15,500 “price” is not indicative of the out-of-pocket costs but likely serves as an arbitrary anchor
that biases respondents’ expectation of the price they will pay.54 Even HHS recognizes that “a
general statement [of WAC] might not provide detailed information about each patient’s [out-ofpocket] cost or address the potential confusion between list price and [out-of-pocket] for a
patient.”55 Thus, the Rule is not likely to help consumers make more informed decisions, but
instead is likely to bias them with arbitrary information.

51

52

53

54

55

Claxton, Gary, Matthew Rae, Michelle Long, Anthony Damico and Heidi Whitmore, “Employer Health Benefits:
2018 Annual Survey,” Kaiser Family Foundation, 2018, at p. 155, http://files.kff.org/attachment/ReportEmployer-Health-Benefits-Annual-Survey-2018. For “specialty drugs,” the average copay is $99 for workers on
a plan with a specialty-only tier (98% of workers at large firms). Data for small firms are not reported (at p. 161).
The JAMA article does not report what share of the study’s commercially-insured participants are on a plan with
three or more tiers.
HHS argues that the majority of Medicare Part D beneficiaries pay a pre-set percentage (32%-50%) of a
“negotiated price,” which supposedly “closely resembles the WAC.” (42 C.F.R. § 403, p. 20740). However,
according to Dr. Garthwaite, the price on which the Medicare “beneficiary’s cost-sharing is based is the price
negotiated by the pharmacy, not WAC. [] This negotiated price is difficult, if not impossible, for a Medicare
beneficiary to discern, as it can vary by pharmacy due to preferred pharmacy networks—limited networks of
pharmacies that Medicare Part D plan sponsors use to lower costs.” (Garthwaite Declaration, at ¶ 47.) Yet at most
12% of the participants in the study would qualify for Medicare (see footnote 45) and it is not discussed in the
study whether that subsample (i.e., those who are on Medicare) differed from the other respondents in their
predictions. Even for Medicare (Part D) beneficiaries, however, I understand from Dr. Garthwaite’s declaration
that a drug with a WAC of $15,500 would quickly result in entering “catastrophic coverage,” with a coinsurance
of 5% of WAC, or $775 in this fictitious example. (Garthwaite Declaration, at ¶ 50.)
21% + 49% x 82% = 61%. Taking into account Medicaid Part D “catastrophic coverage” beneficiaries will further
increase this number.
The Rule compares WAC and out-of-pocket costs for 20 drugs with the highest DTC television advertisement
expenditure (42 C.F.R. § 403, p. 20741, Table 1). The table includes two drugs with WAC similar to the study’s
high price, one with WAC of $16,938 and one with WAC of $12,087. The table implies that the out-of-pocket
costs are likely to be in the $834 to $4,402 range per month and $595 to $5,715 range per month, respectively,
for these drugs. However, these ranges do not cover the entire population (see notes at the bottom of the table)
and show that even within a single plan, out-of-pocket costs may vary by a factor of five.
42 C.F.R. § 403, at p. 20749 (emphasis added).

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V.

BY LEADING MANY CONSUMERS TO OVERESTIMATE THEIR ACTUAL
OUT-OF-POCKET COSTS, THE RULE IS LIKELY TO DETER THEM FROM
SEEKING INFORMATION FROM A DOCTOR OR OBTAINING TREATMENT
35.

An informed decision about whether to get treatment, and which treatment to

choose, or whether to talk to a doctor about a potential treatment, would require that consumers
understand several factors, including the actual costs they would incur (i.e., out-of-pocket costs)
and benefits that various treatments may provide (e.g., efficacy). Studies indicate that DTC
advertising of pharmaceuticals raises awareness of disease conditions and increases the likelihood
that consumers will talk to their doctor about their conditions. By increasing the salience of WAC
to consumers, the Rule is likely to lead many consumers to assume that the drug is too expensive,
thereby deterring them from initiating a conversation with their doctors.
36.

In Section V.A below, I will discuss how DTC pharmaceutical advertising benefits

patients primarily by encouraging patients to seek treatment. Then in Section V.B, I will discuss
how the Rule is likely to diminish the benefits of DTC pharmaceutical television advertising by
creating misimpressions about out-of-pocket costs. Finally in Section V.C, I will discuss how the
disclaimer in the Rule is unlikely to correct the confusion about out-of-pocket costs caused by the
Rule for many consumers or the Rule’s effect of diminishing the likelihood that consumers will
initiate a conversation with their doctors.
A. DTC Pharmaceutical Advertising Encourages Patients to Seek Treatment
37.

As HHS recognizes, “consumers are responsible for critical choices related to their

treatment with prescription drugs. For example, consumers decide whether to make the initial
appointment with a physician[, and] whether to ask the physician about a particular drug or
biological product […].”56 Research shows that DTC advertising spurs patients to make that initial
appointment and ask about available drugs and biological products. For example, a 1999 FDA
consumer survey found that exposure to DTC advertising prompted 27 percent of Americans to
make an appointment with their doctor to talk about a condition they had not previously
discussed.57 A subsequent similar study concluded that 18 percent of Americans spoke with their

56
57

42 C.F.R. § 403, at pp. 20733-20734.
Aikin, Kathryn J., John L. Swasy, and Amie C. Braman, “Patient and Physician Attitudes and Behaviors
Associated with DTC Promotion of Prescription Drugs—Summary of FDA Survey Research Results,” U.S. Food
and
Drug
Administration,
November
19,
2004,
at
p.
2,

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doctor after viewing a DTC advertisement.58 According to the FTC, by providing information
about benefits and risks, DTC advertising has had positive effects for consumers, such as
encouraging consumers to “seek out information about medications and medical conditions, some
of which may not have been diagnosed previously” and “have more fruitful, informed
conversations with their doctors about treatment options and may permit them to make betterinformed health care decisions for themselves.” 59 A recent study of antidepressants similarly
concluded that DTC advertising could be beneficial, especially for “conditions that are seen as
undertreated.”60
38.

Not only does DTC advertising motivate consumers to schedule appointments with

their health care providers, but the conversations that occur during those appointments better
inform the patient about possible treatment—including other available treatment options. As HHS
acknowledges: “[t]riggering conversations about a particular drug or biological product and its
substitutes may lead to conversations not only about price, but also efficacy and side effects, which
in turn may cause both the consumer and the prescriber to consider the cost of various alternatives
(after taking into account the safety, efficacy, and advisability of each treatment for the particular
patient).”61
39.

Furthermore, studies reveal that many patients who are motivated by DTC

advertising to discuss particular prescription drugs with their health care providers 62 may be

58

59

60

61
62

https://www.fda.gov/downloads/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/UCM
600276.pdf.
Aikin, Kathryn J., John L. Swasy, and Amie C. Braman, “Patient and Physician Attitudes and Behaviors
Associated with DTC Promotion of Prescription Drugs—Summary of FDA Survey Research Results,” U.S. Food
and
Drug
Administration,
November
19,
2004,
at
p.
2,
https://www.fda.gov/downloads/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/UCM
600276.pdf.
“Comments of the Staff of the Bureau of Consumer Protection, the Bureau of Economics, and the Office of Policy
Planning of the Federal Trade Commission,” Federal Trade Commission, May 10, 2004, at p. 12,
https://www.ftc.gov/sites/default/files/documents/advocacy_documents/ftc-staff-comment-food-and-drugadministration-concerning-consumer-directed-promotion/040512dtcdrugscomment.pdf.
Shapiro, Bradley T., “Positive Spillovers and Free Riding in Advertising of Prescription Pharmaceuticals: The
Case of Antidepressants,” Journal of Political Economy, Vol. 126, No. 1 (2018): 381-437, at p. 434 (further
concluding that “[a]lthough a brand effect is present, it is short-lived, whereas the category expansion effect is
more persistent”).
42 C.F.R. § 403, at p. 20735.
E.g., research has found that “antidepressant advertising leads to new initiations of treatment followed by
reductions in absenteeism.” Shapiro, Bradley T., “Promoting Wellness or Waste? Evidence from Antidepressant

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prescribed other, potentially less expensive, alternatives.63 For example, a study of five therapeutic
classes of drugs (recent vintage anti-depressants, antihyperlipidemics, proton pump inhibitors,
nasal sprays, and antihistamines) found that DTC advertising “has been effective primarily through
increasing the size of the entire class” rather than the “within-class market share of advertised
drugs.” 64 Similarly, a recent study of DTC advertising of antidepressants concluded that
“[a]lthough a brand effect is present, it is short-lived, whereas the category expansion effect is
more persistent.” 65 A follow-up study found that DTC television advertising had significant
positive spillover effects on prescribing of the therapeutic class as a whole: “antidepressant
advertising leads to new initiations of treatment followed by reductions in absenteeism.”66
B. The Rule Is Likely to Deter Many Consumers from Contacting Their Doctors by
Leading Consumers to Overestimate Their Out-of-Pocket Costs
40.

The Rule is likely to diminish the beneficial effect of DTC advertising by causing

many consumers to overestimate their actual out-of-pocket costs, which can reduce their interest
in a product and potentially delay or deter them from contacting their health care providers.67

63

64

65

66

67

Advertising,” Becker Friedman Institute for Research in Economics Working Paper Series, No. 2018-14 (2019):
1-60, at p. 1.
E.g., “[o]ur findings suggest that, for these classes of drugs, DTCA [“direct-to-consumers advertising”] has been
effective primarily through increasing the size of the entire class. Overall, we estimate that 13 to 22 percent of
the recent growth in prescription drug spending is attributable to the effects of DTCA.” Rosenthal, Meredith B.,
Ernst R. Berndt, Julie M. Donohue, Arnold M. Epstein, and Richard G. Frank, “Demand Effects of Recent
Changes in Prescription Drug Promotion,” Frontiers in Health Policy Research, Vol. 6 (2003): 1-26, at p. 1. See
also, a study on statins sales has found that “a 10% increase in category advertising produces a 0.2% revenue
increase for non-advertised drugs,” suggesting that advertising has “a positive spillover effect to non-advertised
drugs.” Sinkinson, Michael, and Amanda Starc, “Ask Your Doctor? Direct-to-Consumer Advertising of
Pharmaceuticals,” NBER Working Paper Series, No. 21045 (2015): 1-54, at pp. 1, 3.
Rosenthal, Meredith B., Ernst R. Berndt, Julie M. Donohue, Arnold M. Epstein, and Richard G. Frank, “Demand
Effects of Recent Changes in Prescription Drug Promotion,” Frontiers in Health Policy Research, Vol. 6 (2003):
1-26, at pp. 1, 12.
Shapiro, Bradley T., “Positive Spillovers and Free Riding in Advertising of Prescription Pharmaceuticals: The
Case of Antidepressants,” Journal of Political Economy, Vol. 126, No. 1 (2018): 381-437, at pp. 381, 434.
Shapiro, Bradley T., “Promoting Wellness or Waste? Evidence from Antidepressant Advertising,” Becker
Friedman Institute for Research in Economics Working Paper Series, No. 2018-14 (2019): 1-60, at p. 1. See also,
a study on statins sales, Sinkinson, Michael, and Amanda Starc, “Ask Your Doctor? Direct-to-Consumer
Advertising of Pharmaceuticals,” NBER Working Paper Series, No. 21045 (2015): 1-54, at pp. 1-3.
“[L]aw of demand[:] The inverse relationship between the price of a good and the quantity demanded, when all
other factors that influence demand are held fixed.” Besanko, D.A. and R.R. Braeutigam, Microeconomics, Fourth
Edition, Hoboken: John Wiley & Sons, Inc., 2011, at p. 31 (emphasis in the original). “The most enduring legacy
of the RAND experiment [on the impact of consumer cost sharing in health insurance on medical spending] is
not merely the rejection of the null hypothesis that price does not affect medical utilization, but rather the use of
the RAND results to forecast the spending effects of other health insurance contracts. In extrapolating the RAND
results out of sample, analysts have generally relied on the RAND estimate of a price elasticity of demand for

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Indeed, HHS concedes this risk: “consumers, intimidated and confused by high list prices, may be
deterred from contacting their physicians about drugs or medical conditions. … This could
discourage patients from using beneficial medications, reduce access, and potentially increase total
cost of care.”68 The JAMA study (discussed in more detail in section VI) similarly found that
consumers shown a high-priced fictitious drug, Mayzerium, were significantly less likely to ask
their doctor about the drug than those who were not shown price information.69 This was true
whether or not they were also shown a disclaimer that with insurance, their cost could be zero, but
those shown a high price without a disclaimer reported the lowest likelihood to ask their doctor
about the drug across all study groups.70
41.

For these reasons, the Rule will likely not only adversely affect the advertised

pharmaceuticals but, more generally, will likely reduce the effectiveness of the advertisements in
encouraging patients to seek needed treatment.71
C. The Disclaimer in the Rule is Unlikely to Correct the Biased Expectations of Out-OfPocket Costs Caused by the Rule for Many Consumers or the Rule’s Effect of
Diminishing the Likelihood that Consumers Will Initiate a Conversation with Their
Doctors
42.

The Rule requires manufacturers to include the following disclaimer in the

advertisement: “If you have health insurance that covers drugs, your cost may be different.”72
HHS contends that this disclaimer will mitigate the risk that “disclosure of a drug’s WAC in DTC

68
69
70
71

72

medical spending of −0.2.” Aron-Dine, Aviva, Liran Einav, and Amy Finkelstein, “The RAND Health Insurance
Experiment, Three Decades Later,” Journal of Economic Perspectives, Vol. 27, No. 1 (2013): 197-222, at pp.
197, 207-208.
42 C.F.R. § 403, at p. 20756.
JAMA article, at p. 437, Table 2. See also, Section V.C.
JAMA article, at p. 437, Table 2. See also, Section V.C.
The FTC document cited above points out that “DTC ads may create misimpressions about drug risks and benefits,
and doctors may have to correct these misimpressions and not let them affect their prescribing decisions.”
(“Comments of the Staff of the Bureau of Consumer Protection, the Bureau of Economics, and the Office of
Policy Planning of the Federal Trade Commission,” Federal Trade Commission, May 10, 2004, at p. 12,
https://www.ftc.gov/sites/default/files/documents/advocacy_documents/ftc-staff-comment-food-and-drugadministration-concerning-consumer-directed-promotion/040512dtcdrugscomment.pdf.) However, disclosure of
WAC in DTC television advertisements will not correct any misleading impressions of a drug’s risks or benefits;
it will likely prevent consumers from talking to their doctors about the advertised drug and the possible need for
treatment.
42 C.F.R. § 403, at p. 20732.

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television advertisements will overemphasize costs or deter patients from seeking care.” 73 In
support, HHS cites the JAMA study.74 The JAMA study is discussed in more detail in the next
section, but HHS’s specific conclusion from that study about the purported mitigating effect of the
disclaimer is flawed for the following reasons.
43.

First, as discussed above, the results of the JAMA study reinforce my opinion that

viewing a drug’s price reduces a patient’s interest in contacting his or her physician. In the JAMA
study, some of the participants were shown a price for Mayzerium, with the disclaimer that
“eligible patients may be able to get Mayzerium for as little as $0 per month,” while other
participants were not provided the disclaimer.75 HHS appears to refer to the finding in the study
that respondents who viewed a high price for the fictitious drug, but saw the disclaimer, had a
significantly higher intent (in the study’s hypothetical scenario) of asking their doctor about the
drug than those who saw the same price but did not see the disclaimer (an average response of 4.48
on a 1-to-7 scale compared with 2.90).76 However, those respondents who were provided no price
had a significantly higher intent to ask their doctors (average 5.12 response) than both those who
were shown a price with a disclaimer or without it.77
44.

Second, in making its claim, HHS ignores the fact that the disclaimer in the JAMA

study is very different from the disclaimer proposed in the Rule: “If you have health insurance that
covers drugs, your cost may be different.”78 In particular, the disclaimer in the JAMA study evoked
zero price (“$0 per month”). Research shows that zero price is a “special price” and that consumers
experience such a positive affect (good feeling) when encountering something for free that they

73
74
75
76

77

78

42 C.F.R. § 403, at pp. 20741-20742.
42 C.F.R. § 403, at pp. 20741-20742.
JAMA article, at p. 436.
JAMA article, at p. 437, Table 2. Here and throughout, I use “significantly higher” or “significantly lower” as
shorthand to refer to cases when one mean is larger than the other and, unless otherwise specified, the
corresponding medians are statistically significantly different. Table 2 of the study reports means and statistical
tests for medians.
JAMA article, at p. 437, Table 2. While the article does not test for statistical difference between the group
provided no price and the group provided the high price with a disclaimer, a z-test shows that they are statistically
significantly different on this measure (z = 2.65, p = 0.008). “Comparison of Two Means,” Yale University,
Department of Statistics, http://www.stat.yale.edu/Courses/1997-98/101/meancomp.htm (viewed June 7, 2019).
This is a test of means. The tests in the article are tests of medians as explained in Table 2 of the article, but one
cannot conduct such a test of medians without the underlying data.
42 C.F.R. § 403, at p. 20732.

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behave as if the free product not only is available at no cost but also has incremental benefits.79 In
contrast, far from evoking a zero price, HHS’s mandated disclaimer does not even state that a
consumer’s cost may be lower than WAC—only that it may be “different.” The Rule’s disclaimer
does not provide any specific number and because of its ambiguity, cannot be assumed to have the
same impact as the disclaimer used in the JAMA study.
45.

Third, and relatedly, HHS ignores a large body of academic research that shows

that disclaimers are often ineffective. One academic study shows that “remedial statements may
be at least as confusing and misleading as the advertising they are designed to counteract” and that
“comprehension is made more difficult as the number of concepts increases and finite memory
resources are expended to maintain information in active memory for processing.” 80 Other
research points to a multitude of factors which can render disclaimers ineffective, such as
consumers’ limited attention, 81 or information being ignored or discounted as “irrelevant,
incomprehensible, or requiring too much effort,”82 or if consumers do not view the disclaimer as
useful or do not have “the knowledge to be able to make the information from the environment
meaningful.”83,84
46.

Therefore, whether and to what extent a disclaimer impacts consumer response is

an empirical question, which requires careful empirical study of the particular language of a
disclaimer, in the context of its surrounding message. HHS points to no such empirical evidence
79

80

81

82

83

84

Shampanier, Kristina, Nina Mazar, and Dan Ariely, “Zero as a Special Price: The True Value of Free Products,”
Marketing Science, Vol. 26, No. 6 (2007): 742-757, at p. 742.
Jacoby, Jacob, Margaret C. Nelson, and Wayne D. Hoyer, “Corrective Advertising and Affirmative Disclosure
Statements: Their Potential for Confusing and Misleading the Consumer,” Journal of Marketing, Vol. 46, No. 1
(1982): 61-72, at pp. 62-63.
“[L]imited attention, motivated attention, and biased assessments of probability can undermine the goal of
promoting informed consumer choice, potentially rendering disclosure ineffective.” In particular, “there are
serious limitations on the amount of information to which people can attend at any point in time. Bounded
attention renders many disclosures useless because consumers ignore them.” Furthermore, a disclosure “can be
affirmatively counterproductive when it distracts from other, possibly more important, information.”
Loewenstein, George, Cass R. Sunstein, and Russell Golman, “Disclosure: Psychology Changes Everything,”
Annual Review of Economics, Vol. 6 (2014): 391-419, at p. 396; see also pp. 398-399.
Stewart, David W., and Ingrid M. Martin, “Advertising Disclosures: Clear and Conspicuous or Understood and
Used?,” Journal of Public Policy & Marketing, Vol. 23, No. 2 (2004): 183-192, at p. 185.
Brucks, Merrie, Andrew A. Mitchell, and Richard Staelin, “The Effect of Nutritional Information Disclosure in
Advertising: An Information Processing Approach,” Journal of Public Policy & Marketing, Vol. 3 (1984): 1-25,
at p. 23.
The disclaimer is different from WAC itself. As discussed above in Section IV.B, WAC, as a numerical figure—
and one conveying pricing information—is likely to be anchoring information. More generally, the disclaimer is
boilerplate and not specific (unlike WAC). It says that costs may be different but not how different.

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(pertaining to the Rule’s disclaimer) in the preamble to its Rule. To the contrary, HHS relies on a
single study which tests a disclaimer different from the one required by the Rule. Unlike the
disclaimer in the study on which HHS relies, the disclaimer required by the Rule does not specify
that a consumer’s out-of-pocket cost may be $0; indeed, it does not specify any amount or the
extent to which a consumer’s out-of-pocket cost might vary from WAC. As such, the study on
which HHS relies cannot support the general supposition that the actual disclaimer will have any
mitigating effect on whether consumers are deterred from treatment by the inclusion of WAC in
DTC advertising. Regardless of these flaws in HHS’s application of the JAMA study findings,
even the group shown the disclaimer with the high price reported significantly lower intent to talk
to their doctor in the hypothetical scenario than the group not shown a price.
VI.

THE JAMA STUDY DOES NOT SUPPORT THE RULE
47.

In the Rule, HHS relies extensively on the results of the JAMA study to conclude

that disclosing WAC in DTC pharmaceutical advertisements will lead to more informed decisions
by improving how accurately consumers predict their out-of-pocket costs. 85 In the study, 580
participants were randomly assigned to one of five groups and each group was shown one of five
print DTC pharmaceutical advertisements for Mayzerium, a fictitious Type 2 diabetes prescription
drug.86 The advertisement presented to one group did not display any price information (I will
refer to it as the “no-price” group).87 Four groups were presented with advertisements displaying
a “price,” $50 per month for two groups and $15,500 per month for two others (I will refer to them
as “low-price” and “high-price” groups respectively).88 Advertisements in one of the low-price
groups and in one of the high-price groups also displayed a disclaimer stating that “eligible patients
may be able to get Mayzerium for as little as $0 per month.89 After reviewing the advertisement,
participants were asked a series of questions, including predicting their out-of-pocket cost for the

85
86
87
88

89

42 C.F.R. § 403, at pp. 20734-20735, 20741-20742, 20746-20747, 20752-20753, 20755, 20757.
JAMA article, at p. 436.
JAMA article, at p. 436.
JAMA article, at p. 436. (These “prices” represent “the 1st and 99th percentiles, respectively, of the average
wholesale price in 2016 of diabetic prescription drugs.”)
JAMA article, at p. 436. See also, JAMA article supplemental Appendix. For example, participants in the highprice with-disclaimer group read “[t]he price for Mayzerium is $15,500 a month, but eligible patients may be able
to get Mayzerium for as little as $0 a month” (emphasis in the original).

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drug, and likelihood to ask their doctor about the drug.90
48.

The authors caution about the generalizability of the study to other drugs and

situations.91 Notwithstanding that caution, HHS repeatedly cites and relies on the study in the
Rule.92 In particular, HHS concludes that participants shown the high price (and no disclaimer) got
closer to estimating the purported out-of-pocket cost:
[R]esearchers asked subjects to estimate their monthly OOP [out-of-pocket] costs
for a drug with a hypothetical price of $15,500 per month. When subjects were
provided no information about price, they responded that their OOP costs would
be, on average, $78 per month. This finding tends to support our belief that patients
seem to underestimate the true cost of drugs advertised on television. However,
when subjects were told the price, they more accurately determined their OOP
costs at $2,787 or about 18 percent of the hypothetical price. The informed
estimates were far closer to what one would expect to see paid at the pharmacy
counter under most plans than the uninformed assessment of $78.93
49.

However, as discussed below, HHS overlooks various limitations of the study and

attempts to extend the study’s limited findings well beyond what they actually support.
50.

First, the JAMA study does not support HHS’s claim that $2,787 is a more accurate

estimate of the study drug’s monthly out-of-pocket cost “under most plans.” 94 This is a conclusion
that HHS reaches, but is not a finding in the study. For example, the article makes no claim about
by what percent, on average, respondents’ predicted out-of-pocket costs would have differed from
their actual out-of-pocket costs. Neither does the article state whether, as HHS suggests, the highprice no-disclaimer group performed more accurately in that respect than the no-price group.
51.

As an initial matter, HHS’s conclusion is nonsensical because no one can know the

actual out-of-pocket cost for the drug. Not only is the study’s drug Mayzerium fictitious, but the
study did not report the particulars of each insured participant’s plan.95 Thus, the drug’s true outof-pocket cost for each participant cannot be known. As discussed in Section IV.C, out-of-pocket
90
91

92
93
94
95

JAMA article, at p. 436.
JAMA article, at p. 436 (“results might not be generalizable to drugs of other therapeutic classes [i.e., other than
Type 2 diabetes drugs], in different price ranges [i.e., other than for the $50 and $15,500 ‘price’], or using other
marketing strategies in DTCPA [i.e., other than a print ad].”)
42 C.F.R. § 403, at pp. 20734-20735, 20741-20742, 20746-20747, 20752-20753, 20755, 20757.
42 C.F.R. § 403, at p. 20735 (emphasis added); see also JAMA article, at p. 437, Table 2.
As HHS claims in 42 C.F.R. § 403, at p. 20735.
See footnote 45.

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drug costs differ greatly from consumer to consumer and even for the same consumer over the
course of the year.96 I understand from Dr. Garthwaite that out-of-pocket costs for drugs vary by
whether a consumer is insured or not, who the consumer is insured by (i.e., Medicare, Medicaid,
private commercial insurance), the specific cost-sharing structure of the consumer’s plan (i.e.,
deductibles, copays, and coinsurance), and the status of the drug on the plan’s formulary (i.e.,
covered, high-tier, low-tier, not covered), among many other factors.97 As discussed in detail in
Section IV.C, the $2,787 (as well as the 95% confidence interval surrounding it) is an extremely
inaccurate prediction of the actual out-of-pocket costs paid by a majority of consumers for any
drug. For example, if the JAMA study sample is representative of the U.S. population, following
HHS’s logic, about 21% of respondents (the number corresponding to the percent of the US
population on Medicaid) should have estimated their out-of-pocket costs to be $8 or lower.98
However, the implied range for 95% of respondents in the high-price no-disclaimer group is from
$1,839 to $3,735.99 As a result, a substantial number of participants overestimated their out-ofpocket costs by over 20,000%.100 A similar overestimation is true for most participants covered by
commercial insurance (including those who have already reached their yearly cap) and for some
participants covered by Medicare Part D. 101 Overall, assuming the JAMA study sample is
representative of the U.S. population, for a large section of the sample, there is no basis to state
that $1,839 to $3,735 is a better prediction of their out-of-pocket costs than $78. Based on this
discussion, it would make sense to look at the JAMA study data by participants’ insurance type
(or lack of it), but the article does not do it.
52.

Second, the scenarios in the JAMA study, particularly with respect to those

presented to the high-price groups, are not representative of the overwhelming majority of real
world WAC for diabetes drugs or drugs in general. As the JAMA article acknowledges, 99% of

96
97
98
99
100
101

Garthwaite Declaration, at ¶ 53.
See Section IV.C.
See Section IV.C and in particular footnote 45.
See Section IV.C.
See Section IV.C.
See Section IV.C and in particular footnote 45.

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all diabetes drugs have a lower WAC than $15,500.102 Further, of the 20 drugs with the highest
2016 television advertising expenditures, only one costs more than $15,500 and only one other
costs more than $10,000.103 WAC for the rest is considerably lower, under $6,000 per month.104
Thus, the advertisements presented to the high-price groups in the study are not representative of
most situations that consumers are likely to encounter in DTC advertising once the Rule takes
effect. Generally, one cannot generalize from outliers. And in fact, participants in the two groups
shown a low price ($50, which is lower than 99% of all diabetes drugs,105 i.e., another outlier),
regardless of whether they saw the disclaimer, on average estimated that their out-of-pocket costs
would be the same as the disclosed “price.”106 This outcome is no more accurate than for those
presented with a high price as, generally, out-of-pocket cost is a fraction of WAC, as discussed
above. Yet while HHS references the no-price and high-price groups in the Rule, HHS largely
ignores the low-price groups presented with a $50 “price.”107
53.

HHS ignores other limitations of the JAMA study as well. Among other things, the

study addresses print advertisements, not television advertisements. Television advertisements
elicit different responses from consumers than print advertisements.108 Further, any survey should
target the relevant population about which it seeks to draw conclusions. Therefore, one of the first
steps in deciding whether the survey results are relevant and meaningful is to evaluate the target
population or universe for the survey.109 The universe is that segment of the population whose
beliefs are relevant to the issues in the case. As Professor Thomas McCarthy, an expert on proper
survey methodology, points out, “[s]election of the proper universe is a crucial step, for even if the
102

103
104
105
106
107

108
109

“The remaining 4 advertisements disclosed either a low ($50 per month) or high ($15 500 per month) price,
representing the 1st and 99th percentiles, respectively, of the average wholesale price in 2016 of diabetic
prescription drugs.” JAMA article, at p. 436.
42 C.F.R. § 403, at p. 20741, Table 1.
42 C.F.R. § 403, at p. 20741, Table 1.
JAMA article, at p. 436.
JAMA article, at p. 437, Table 2.
HHS references the no-price and high-price groups nine times (42 C.F.R. § 403, at pp. 20734-20735, 2074120742, 20746-20747, 20752, 20755, 20757) and the low-price groups one time (42 C.F.R. § 403, at pp. 2075220753).
See footnotes 30, 31.
“Identification of the proper target population or universe is recognized uniformly as a key element in the
development of a survey.” Diamond, Shari Seidman, “Reference Guide on Survey Research,” in Reference
Manual on Scientific Evidence, Third Edition, Federal Judicial Center, (2011): 359-423, footnote 76, at p. 376;
see also, pp. 376-387.

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proper questions are asked in a proper manner, if the wrong persons are asked, the results are likely
to be irrelevant.”110 By contrast, while the JAMA study focuses on a fictitious type 2 diabetes drug,
only 6% of respondents in the study had a history of type 2 diabetes.111 In other words, for 94% of
the study participants, the study scenario was likely irrelevant. The sample is also skewed in the
sense that 20% of participants did not have health insurance while the corresponding value in the
U.S. population is only 9%.112
54.

For these reasons, HHS is stretching the JAMA study beyond what its findings

logically support, especially in light of its design limitations.

I declare and state the foregoing is true and accurate to the best of my knowledge.

___________________________________
Ravi Dhar
June 14, 2019

110

111
112

McCarthy, J. Thomas, McCarthy on Trademarks and Unfair Competition, Fourth Edition, Thomson Reuters,
2013, § 32:159, at p. 32-363.
JAMA article, at p. 436, Table 1.
JAMA article, at p. 436, Table 1; Garthwaite Declaration, at ¶ 52.

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APPENDIX A
CURRICULUM VITAE

Case 1:19-cv-01738-APM Document 1-2 Filed 06/14/19 Page 29 of 43

April 2019
RAVI DHAR
Yale School of Management
165 Whitney Avenue
Yale University
New Haven, CT 06520
[phone]

Employment
George Rogers Clark Professor of Management
Professor of Psychology (joint appointment)
Director, Yale Center for Customer Insights
Professor of Marketing,
Associate Professor of Marketing,
Assistant Professor of Marketing
Yale School of Management
Other Appointments
Visiting Faculty, HEC Paris
Visiting Associate Professor, Stanford University
Visiting Professor, Erasmus University
Visiting Professor, New York University
Education
Haas School of Business, UC Berkeley
Ph. D. (Business Administration)
M.S. (Business Administration)
Indian Institute of Management
M.B.A.
Indian Institute of Technology
B.Technology

2005 - Present
2003 – Present
2004 – Present
2000 – Present
1997 - 2000
1992 - 1997

Summer 1996
Spring 1998
Summer 2000, 2001
Spring 2005, Spring 2010

1988-1992
1992
1990
1987
1985

Academic Honors and Fellowships
Distinguished Alumnus Award, Indian Institute of Management, 2013
Distinguished Scientific Contribution Award, SCP, 2012
Yale SOM Alumni Association Teaching Award, 2012
Finalist O’Dell Award 2012
Finalist, O’Dell Award, 2008
Winner, O’Dell Award 2005
Finalist, O’Dell Award, 2004
Finalist, Paul Green Award, 2004
AMA Consortium Faculty Fellow, 2003- 2009, 2010, 2012, 2013
INFORMS Doctoral Consortium Faculty – Multiple Years
ACR Doctoral Consortium Faculty – Multiple Years
John A. Howard Doctoral Dissertation Award (Honorable Mention), 1993
AMA Doctoral Consortium Fellow, 1991
A-1

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Research Interests
Consumer Behavior
Judgment and Decision Making
E-Commerce

Marketing Strategy
Branding
Behavioral Finance

Teaching Interests
Marketing Management
Marketing Strategy
Financial Services

Consumer Behavior
Behavioral Decision Theory
E-Commerce Marketing

Professional Affiliation (Member)
American Marketing Association
Association for Consumer Research
Society of Judgment and Decision Making
Professional Activities
Editorial Board,

Journal of Consumer Research, 1997 – Present, Past Associate Editor
Journal of Consumer Psychology, 1997 – 2002, 2005 - Present
Journal of Marketing Research, 2001 – Present, Associate Editor
Journal of Marketing, 2005 - Present
Marketing Letters, 2000 - Present
Marketing Science, 2002- 2011, Past Area Editor

Occasional Reviewer, Marketing, Management, Psychology Journals, NSF, etc.

Publications in Journals
Approximate Number of Citations in Google Scholar: 14,000+

1. “By-Brand or By-Category? The Effect of Display Format on Brand
Extension Evaluation,” (with Xiaoying Zheng and Ernest Baskin), Journal of
Retailing, in press.
2. “You Don’t Blow Your Diet on Twinkies: Choice Processes When Choice Options
Conflict with Incidental Goals,” (with K. Goldsmith and EMS Friedman), Journal of
the Association for Consumer Research, 2019.
3. “The Uncertain Self: How Self-Concept Structure Affects Subscription Choice,”
(with Jennifer Savary), Journal of Consumer Research, conditional accept, 2018.

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4. “Apples, Oranges and Erasers: The Effect of Considering Similar versus Dissimilar
Alternatives on Purchase Decisions,” (with Liz Friedman and Jennifer Savary),
Journal of Consumer Research, 2018.
5. “Seeing Stars: How the Binary Bias Distorts the Interpretation of Customer Ratings,”
(with Matt Fisher and George Newman), Journal of Consumer Research, 2018.
6. “Effect of Intelligence on Consumers’ Responsiveness to a Pro-Environmental Tax:
Evidence from Large-Scale Data on Car Acquisitions of Male Consumers,” (with
Jaakko Aspara and Xueming Luo), Journal of Consumer Psychology, 2017.
7. “Proximity of Snacks to Beverages Increases Food Consumption in the Workplace:
A Field Study,” (with E. Baskin, M. Gorlin, Z. Chance, N. Novemsky, K Huskey, M.
Hatzis), Appetite, 2016.
8. “Mental Representation Changes the Evaluation of Green Product Benefits,” (with
Kelly Goldsmith and George Newman), Nature Climate Change, 2016.
9. “Closer to the Creator: Temporal Contagion Explains The Preference for Earlier
Serial Numbers,” (with R. Smith and G. Newman), Journal of Consumer Research,
2016.
10. “Sophisticated by Design: the Nonconscious Influences of Primed Concepts and
Atmospheric Variables on Consumer Preferences,” (with T. Andrew Poehlman and
John A. Bargh), Customer Needs and Solutions, 2015.
11. “Positive Consequences of Conflict on Decision Making,” (with J. Savary, T.
Kleiman, and R. Hassin), Journal of Experimental Psychology: General, 2015.
12. “The Technological Conundrum: How Rapidly Advancing Technology Can Lead To
Commoditization,” (with T. Chan and W. Putsis), Customer Needs and Solutions,
2015.
13. “When Going Green Backfires: How firm Intentions Shape the Evaluation of
Socially Beneficial Product Enhancements,” (with G. Newman and M. Gorlin),
Journal of Consumer Research, 2014.
14. “Why Choosing Healthy Foods Is Hard, and How to Help: Presenting 4P’s
Framework for Behavior Change,” (with Z. Chance and M. Gorlin), Customer Needs
and Solutions, 2014.
15. “Giving Against the Odds: When Tempting Alternatives Increase Willingness to
Donate,” (with J. Savary and K. Goldsmith), Journal of Marketing Research, 2014.
16. “Authenticity is Contagious: Brand Essence and the Original Source of Production,”
(with George Newman), Journal of Marketing Research, 2014.

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17. “A Dual System Framework to Understand Preference Construction Processes in
Choice,” (with M. Gorlin), Journal of Consumer Psychology, 2013.
18. “Refining the dual-process theory of preference construction: A reply to Gawronski,
Martin and Sloman, Stanovich, and Wegener and Chien,” (with M. Gorlin), Journal
of Consumer Psychology, 2013.
19. “Negativity Bias and Task Motivation: Testing the Effectiveness of Positively
Versus Negatively Framed Incentives,” (with K. Goldsmith), Journal of
Experimental Psychology: Applied, 2013.
20. “Representation and Perceived Similarity: How Abstract Mindset Aids Choice from
Large Assortments,” (with J. Xu and Z. Jiang), Journal of Marketing Research,
2013.
21. “Comparing Apples to Apples or Apples to Oranges: The Role of Mental
Representation in Choice Difficulty,” (with U. Khan and E. Kim), Journal of
Marketing Research, 2013.
22. “Adding Small Differences Can Increase Similarity and Choice,” (with J. Kim and
N. Novemsky), Psychological Science, 2013.
23. “When Guilt Begets Pleasure: The Positive Effect of a Negative Emotion,” (with K.
Goldsmith and E. Kim), Journal of Marketing Research, 2012.
24. “Bridging the Gap between Joint and Individual Decisions: Deconstructing
Preferences in Relationships,” (with M. Gorlin), Journal of Consumer Psychology,
2012.
25. “The Importance of the Context in Brand Extension: How Pictures and Comparisons
Shift Consumers’ Focus from Fit to Quality,” (with T. Meyvis and K. Goldsmith),
Journal of Marketing Research, 2012.
26. “Self-Signaling and the Costs and Benefits of Temptation in Consumer Choice,”
(with K. Wertenbroch), Journal of Marketing Research, 2012.
27. “Price Framing Effects on Purchase of Hedonic and Utilitarian Bundles,” (with U.
Khan), Journal of Marketing Research, 2010.
28. “Making Products Feel Special: When Metacognitive Difficulty Enhances
Evaluation,” (with A. Pocheptsova and A. Labroo), Journal of Marketing Research,
2010.
29. “Modeling the Under Reporting Bias in Panel Survey Data,” (with Sha Yang and Yi
Zhao) Marketing Science, 2010.

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30. “The Effect of Decision Order on Purchase Quantity Decisions,” (with I. Simonson
and S. M. Nowlis), Journal of Marketing Research, 2010.
31. “Tradeoffs and Depletion in Choice,” (with N. Novemsky, J. Wang, R. Baumeister),
Journal of Marketing Research, 2010.
32. “Opportunity Cost Neglect,” (with S. Frederick, N. Novemsky, J. Wang, and S.
Nowlis), Journal of Consumer Research, 2009.
33. “Anticipating Adaptation to Products,” (with J. Wang and N. Novemsky), Journal of
Consumer Research, 2009.
34. “Deciding Without Resources: Psychological Depletion and Choice in Context,”
(with O. Amir, A. Pochepstova, and R. Baumeister), Journal of Marketing Research,
2009.
35. “Customization Procedures and Customer Preferences,” (with A. Valenzuela and F.
Zettelmeyer), Journal of Marketing Research, 2009.
36. “Beyond Rationality: The Content of Preferences,” (with N. Novemsky), Journal of
Consumer Psychology, 2008.
37. “Of Frog Wines and Frowning Watches: Semantic Priming of Perceptual Features
and Brand Evaluation,” (with A. Labroo and N. Schwarz), Journal of Consumer
Research, 2008.
38. “When Thinking Beats Doing: The Role of Optimistic Expectations in Goal-Based
Choice,” (with A. Fishbach and Y. Zhang), 2007, Journal of Consumer Research.
39. “Seeing The Forest Or The Trees: Implications of Construal Level Theory for
Consumer Choice,” (with E. Kim), Journal of Consumer Psychology, 2007
40. “Where There Is a Way, Is There a Will? The Effect of Future Choices on SelfControl,” (with U. Khan), Journal of Experimental Psychology: General, 2007
41. “Preference Fluency in Choice,” (with N. Novemsky, N. Schwarz, and I. Simonson),
2007, Journal of Marketing Research.
42. “The Shopping Momentum Effect,” (with J. Huber and U. Khan), 2007, Journal of
Marketing Research.
43. “Institutional Perspectives in Real Estate Investing,” (with W. Goetzmann), 2006,
Journal of Portfolio Management.
44. “Are Rheumatologists’ Treatment Decisions Influenced by Patients Age?,” (with L.
Fraenkel and N. Rabidou),” 2006, Rheumatology.

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45. “Sub-goals as Substitutes or Complements: The Role of Goal Accessibility,” (with
A. Fishbach and Y. Zhang), 2006, Journal of Personality & Social Psychology.
46. “Up Close and Personal: A Cross Sectional Study of the Disposition Effect,” (with
N. Zhu), Management Science, 2006.
47. “Licensing Effect in Consumer Choice,” (with U. Khan), Journal of Marketing
Research, 2006.
48. “Goals as excuses or guides: The liberating effect of perceived goal progress on
choice,” (with A. Fishbach), Journal of Consumer Research, 2005.
49. “Goal Fulfillment and Goal Targets in Sequential Choice,” (with N. Novemsky),
Journal of Consumer Research, 2005.
50. “Towards extending the Compromise Effect to Complex Buying Contexts,” (with
Anil Menon and Bryan Maach), Journal of Marketing Research, 2004.
51. “To Buy or Not to Buy: Response Mode Effects on Consumer Choice,” (with S.
Nowlis), Journal of Marketing Research, 2004.
52. “Hedging Customers,” (with R. Glazer), Harvard Business Review, 2003.
53. “The Effect of Forced Choice on Choice,” (with I. Simonson), Journal of Marketing
Research, 2003.
54. “Coping with Ambivalence: The Effect of removing a ‘fence sitting’ option on
Consumer Attitude and Preference Judgments,” (with B. Kahn and S. Nowlis),
Journal of Consumer Research, 2002.
55. “Consumer Psychology: In Search of Identity,” (with Z. Carmon, A. Drolet, S.
Nowlis, and I. Simonson), Annual Review of Psychology, 2001.
56. “An Empirical Analysis of the Determinants of Category Expenditure,” (with W.
Putsis), Journal of Business Research, 2001.
57. “Trying Hard or Hardly Trying: An Analysis of Context Effects in Choice,” (with S.
Nowlis and S. Sherman), Journal of Consumer Psychology, September 2000.
58. “Consumer Choice between Hedonic and Utilitarian Goods,” (with K. Wertenbroch),
Journal of Marketing Research, February 2000.
59. “Assessing the Competitve Interaction Between Private Labels and National
Brands,” (with R. Cotterill and W. Putsis), Journal of Business, January 2000.
60. “Comparison Effects on Preference Construction,” (with S. Nowlis and S. Sherman),
Journal of Consumer Research, December 1999.
A-6

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61. “The Effect of Time Pressure on Consumer Choice Deferral,” (with S. Nowlis),
Journal of Consumer Research, March 1999.
62. “Making complementary choices in consumption episodes: Highlighting Versus
Balancing,” (with I. Simonson), Journal of Marketing Research, February 1999.
63. “The Many Faces of Competition,” (with W. Putsis), Marketing Letters, July 1998.
64. “Consumer Preference for a No-Choice Option,” Journal of Consumer Research,
September 1997.
65. “Context and Task Effects on Choice Deferral,” Marketing Letters, January 1997.
66. “The Effect of Decision Strategy on the Decision to Defer Choice,” Journal of
Behavioral Decision Making, December 1996.
67. “The Effect of Common and Unique features in Consumer Choice,” (with S. J.
Sherman), Journal of Consumer Research, December 1996.
68. “Similarity in Context: Cognitive Representation and the Violation of Preference
Invariance in Consumer Choice,” (with R. Glazer), Organizational Behavior and
Human Decision Processes, September 1996.
69. “The Effect of the focus of comparison on consumer preferences,” (with I.
Simonson), Journal of Marketing Research, November 1992.

Publications in Book Chapters / Managerial Summary
1. Introduction to the Special Issue: Goals and Motivation (with U. Khan and A.
Fishbach), Journal of the Association for Consumer Research, 2019.
2. “Nudging Healthy Choices with the 4 Ps Framework for Behavioral Change,” (with
Zoe Chance, M. Hatzis, M. Bakker, and L. Ash), Handbook of Marketing Analytics:
Methods and Applications in Marketing Management, Public Policy, and Litigation
Support.”
3.

“How Google Optimized Office Snacks,” (with Zoe Chance, Michelle Hatzis, and
Michiel Bakker,” Harvard Business Review, 2016.

4. “Nudging Individuals Toward Healthier Food Choices with the 4Ps Framework for
Behavior Change,” (with Zoe Chance, Ravi Dhar, Michelle Hatzis, and Kim Huskey),
Behavioral Economics and Public Health, (eds. C. Roberto and I. Kawachi), 2015.
5. “The Power of Customer’s Mindset,” (with Kelly Goldsmith and Jing Xu), Sloan
Management Review, 2010.
A-7

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6. “Giving Consumers License to Enjoy Luxury,” (with U. Khan and S. Schmidt), Sloan
Management Review, 2010.
7. “Brand Permission: A Conceptual and Managerial Framework,” (with Tom Meyvis),
Handbook on Brand and Experience Management, (eds. Bernd H.Schmitt and David
L. Rogers), Elgar Publishing, Northampton, MA, 2008.
8. “Dynamics of goal-based choice,” (with A. Fishbach), Handbook of Consumer
Psychology, (eds. C. P. Haugtvedt, P.M. Herr & F. R. Kardes), Erlbaum Press, 2007.
9. “A Behavioral Decision Theoretic Perspective on Hedonic and Utilitarian Choice,”
(with U. Khan and K. Wertenbroch), Inside Consumption: Frontiers of Research on
Consumer Motives, Goals, and Desires, (eds. S. Ratneshwar and David Glen Mick),
London: Routledge, 2005.
10. “Customer Relations Online,” Wiley Next Generation of Business Thinkers, (ed. Subir
Chowdhury), 2004.
11. “Defining Customers’ Needs and Values for Marketing Success,” Inside the Minds:
Textbook Marketing, Aspatore Press, 2003.
12. “The Online Store,” (with D. R. Wittink), Managing Customer Relationships, (eds.
Martha Rogers and Don Peppers), Wiley, 2003.
13. “Choice Deferral,” The Elgar Companion to Consumer Research and Economic
Psychology, (eds. P. Earl and S. Kemp), 1999.

Select Working Papers / Papers Under Review
1. “Ironic Effects of Goal Activation on Choice,” (with K. Goldsmith), under first review.
2. “The Effect of Goal Breadth on Consumer Preferences,” (with E. Kim), under first
review.
3. “Can Investors Multiply and Divide: Investors’ response to Stock Splits,” (with N. Zhu
and Dan Ariely).
4. "Category Expenditure and Promotion: Can Private Labels Expand the Pie,” (with W.
Putsis), Working Paper.
5. “Mindset over Matter: The Interplay between Goals and Preferences,” (with A.
Pochepstova), Working Paper.

A-8

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Conference Proceedings Publications
1. “Constructing preferences: The role of comparisons in consumer judgment and
choice,” (with S. Zhang) Proceedings of the Association for Consumer Research,
University of Chicago Press (1999).
2. “Sequential Choices and Uncertain Preferences,” Proceedings of the Association for
Consumer Research, University of Chicago Press (1997).
3. “Causes and Effects of Reference Effects in Choice,” Proceedings of the Association
for Consumer Research, University of Chicago Press (1997).
4. “New Directions in Mental Accounting,” Proceedings of the Association for
Consumer Research, University of Chicago Press (1995).
5. “Decision Difficulty and Uncertain Preferences: Implications for Consumer Choice,”
Proceedings of the Association for Consumer Research, University of Chicago Press
(1994).
6. “Behavioral Decision Research: Theory and Applications,” Proceedings of the
Association for Consumer Research, University of Chicago Press (1993).
7. “To Choose Or Not To Choose: This is the Question,” Proceedings of the Association
for Consumer Research, University of Chicago Press (1992).

Invited and Conference Presentations
Invited Academic Presentations (* denotes multiple presentations)
Boston College
Carnegie-Mellon University
Chinese University, Hong Kong
Columbia University*
Cornell University*
Duke University*
Harvard University
Hong Kong University of Science and Technology
IIPM*
INSEAD*
Indiana University
Korea University
London Business School*
MIT*
National University of Singapore
New York University*
Northwestern University*
Ohio State University
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Pennsylvania State University
Stanford University*
Texas A&M University
Tilburg University
Tulane University
University of Alberta
University of British Columbia (planned)
University of California, Berkeley*
University of California, Los Angeles*
University of California, San Diego
University of Chicago*
University of Delaware
University of Colorado
University of Florida
University of Houston
University of Illinois, Urbana-Champaign*
University of Miami
University of Maryland
University of Massachusetts, Amherst
University of Michigan*
University of North Carolina*
University of Peking*
University of Pennsylvania*
University of Rotterdam*
University of Texas, Austin
University of Utah
University of Toronto*
University of Vienna
Washington University, St. Louis*
Conference Presentations (Over 200 presentations at conferences, consortiums, keynotes,
symposiums, workshops, etc.) Recent presentations include:
Keynote Addresses to Practitioners, Various Events
Choice Symposium
CEO Roundtables, New York and New Haven
CMO Roundtables, Various Organizations
ACR
Informs
Judgment and Decision Making
Behavioral Decision Research in Management
Society of Consumer Psychology

A-10

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APPENDIX B
MATERIALS RELIED UPON

Case 1:19-cv-01738-APM Document 1-2 Filed 06/14/19 Page 40 of 43

Case Documents
Expert Declaration of Professor Craig Garthwaite, June 14, 2019.
Academic Articles, Books, and Publications
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Decades Later,” Journal of Economic Perspectives, Vol. 27, No. 1 (2013): 197-222.
Belch, George E., and Michael A. Belch, Advertising and Promotion: An Integrated Marketing
Communications Perspective, Sixth Edition, New York, NY: McGraw-Hill, 2003.
Besanko, D.A. and R.R. Braeutigam, Microeconomics, Fourth Edition, Hoboken: John Wiley & Sons,
Inc., 2011.
Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer, “Salience and Consumer Choice,” Journal of
Political Economy, Vol. 121, No. 5 (2013): 803-843.
Brucks, Merrie, Andrew A. Mitchell, and Richard Staelin, “The Effect of Nutritional Information
Disclosure in Advertising: An Information Processing Approach,” Journal of Public Policy &
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Chandrashekaran, Rajesh, and Dhruv Grewal, “Anchoring Effects of Advertised Reference Price and Sale
Price: The Moderating Role of Saving Presentation Format,” Journal of Business Research, Vol. 59,
No. 10-11 (2006): 1063-1071.
Dhar, Ravi, and Margarita Gorlin, “A Dual‐System Framework to Understand Preference Construction
Processes in Choice,” Journal of Consumer Psychology, Vol. 23, No. 4 (2013): 528-542.
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Psychology Bulletin, Vol. 30, No. 4 (2004): 447-460.
Epley, Nicholas, and Thomas Gilovich, “The Anchoring-and-Adjustment Heuristic: Why the Adjustments
Are Insufficient,” Psychological Science, Vol. 17, No. 4 (2006): 311-318.
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Frederick, Shane W., and Daniel Mochon, “A Scale Distortion Theory of Anchoring,” Journal of
Experimental Psychology: General, Vol. 141, No. 1 (2012): 124-133.
Frederick, Shane, Nathan Novemsky, Jing Wang, Ravi Dhar, and Stephen Nowlis, “Opportunity Cost
Neglect,” Journal of Consumer Research, Vol. 36, No. 4 (2009): 553-561.
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Anderson, “Consumer Responses to Price Disclosure in Direct-to-Consumer Pharmaceutical
Advertising,” JAMA Internal Medicine, Vol. 179, No. 3 (2019): 435-437.

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Jacoby, Jacob, Margaret C. Nelson, and Wayne D. Hoyer, “Corrective Advertising and Affirmative
Disclosure Statements: Their Potential for Confusing and Misleading the Consumer,” Journal of
Marketing, Vol. 46, No. 1 (1982): 61-72.
Jung, Minah H., Hannah Perfecto, and Leif D. Nelson, “Anchoring in Payment: Evaluating a Judgmental
Heuristic in Field Experimental Settings,” Journal of Marketing Research, Vol. 53, No. 3 (2016): 354368.
Kahn, Barbara E., and Rakesh K. Sarin, “Modeling Ambiguity in Decisions under Uncertainty,” Journal
of Consumer Research, Vol. 15, No. 2 (1988): 265-272.
Kahneman, Daniel, “A Perspective on Judgment and Choice: Mapping Bounded Rationality,” American
Psychologist, Vol. 58, No. 9 (2003): pp. 697-720.
Kahneman, Daniel, “Maps of Bounded Rationality: A Perspective on Intuitive Judgment and
Choice,” Nobel Prize Lecture (2002): 449-489.
Kahneman, Daniel, “New Challenges to the Rationality Assumption,” Journal of Institutional and
Theoretical Economics, Vol. 150, No. 1 (1994): 18-36.
Kivetz, Ran, and Itamar Simonson, “The Effects of Incomplete Information on Consumer Choice,”
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Krugman, Herbert E., “The Measurement of Advertising Involvement,” Public Opinion Quarterly,
Vol. 30, No. 4 (1966): 583-596.
Loewenstein, George, Cass R. Sunstein, and Russell Golman, “Disclosure: Psychology Changes
Everything,” Annual Review of Economics, Vol. 6 (2014): 391-419.
McCarthy, J. Thomas, McCarthy on Trademarks and Unfair Competition, Fourth Edition, Thomson
Reuters, 2013.
Mullainathan, Sendhil, and Richard H. Thaler, “Behavioral Economics,” NBER Working Paper Series,
No. 7948 (2000): 1-13.
Park, C. Whan, and S. Mark Young, “Consumer Response to Television Commercials: The Impact of
Involvement and Background Music on Brand Attitude Formation,” Journal of Marketing
Research, Vol. 23, No. 1 (1986): 11-24.
Peters, Ellen, Judith Hibbard, Paul Slovic, and Nathan Dieckmann, “Numeracy Skill and the
Communication, Comprehension, and Use of Risk-Benefit Information,” Health Affairs, Vol. 26, No.
3 (2007): 741-748.
Raghubir, Priya, and Joydeep Srivastava, “Effect of Face Value on Product Valuation in Foreign
Currencies,” Journal of Consumer Research, Vol. 29, No. 3 (2002): 335-347.
Rosenthal, Meredith B., Ernst R. Berndt, Julie M. Donohue, Arnold M. Epstein, and Richard G. Frank,
“Demand Effects of Recent Changes in Prescription Drug Promotion,” Frontiers in Health Policy
Research, Vol. 6 (2003): 1-26.

B-2

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Shafir, Eldar, Peter Diamond, and Amos Tversky, “Money Illusion,” The Quarterly Journal of
Economics, Vol. 112, No. 2 (1997): 341-374.
Shampanier, Kristina, Nina Mazar, and Dan Ariely, “Zero as a Special Price: The True Value of Free
Products,” Marketing Science, Vol. 26, No. 6 (2007): 742-757.
Shapiro, Bradley T., “Positive Spillovers and Free Riding in Advertising of Prescription Pharmaceuticals:
The Case of Antidepressants,” Journal of Political Economy, Vol. 126, No. 1 (2018): 381-437.
Shapiro, Bradley T., “Promoting Wellness or Waste? Evidence from Antidepressant Advertising,” Becker
Friedman Institute for Research in Economics Working Paper Series, No. 2018-14 (2019): 1-60.
Sinkinson, Michael, and Amanda Starc, “Ask Your Doctor? Direct-to-Consumer Advertising of
Pharmaceuticals,” NBER Working Paper Series, No. 21045 (2015): 1-54.
Stewart, David W., and Ingrid M. Martin, “Advertising Disclosures: Clear and Conspicuous or
Understood and Used?” Journal of Public Policy & Marketing, Vol. 23, No. 2 (2004): 183-192.
Strack, Fritz, and Thomas Mussweiler, “Explaining the Enigmatic Anchoring Effect: Mechanisms of
Selective Accessibility,” Journal of Personality and Social Psychology, Vol. 73, No. 3 (1997): 437446.
Tversky, Amos, and Daniel Kahneman, “Judgment under Uncertainty: Heuristics and Biases,” Science,
Vol. 185, No. 4157 (1974): 1124-1131.
van Osselaer, Stijn M. J., and Sarah Lim, “Research Productivity of Faculty at 30 Leading Marketing
Departments,” Marketing Letters (2019): 1-17.
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Reference Dependence of Currency Numerosity Effects,” Journal of Consumer Research, Vol. 34,
No. 1 (2007): 1-10.
Zaichkowsky, Judith L., “Conceptualizing Involvement,” Journal of Advertising, Vol. 15, No. 2 (1986):
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B-3

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“Medicare and Medicaid Programs; Regulation to Require Drug Pricing Transparency,” Centers for
Medicare & Medicaid Services, October 18, 2018,
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