Edited by Baruch Fischhoff, Carnegie Mellon University, Pittsburgh, PA; received September 15, 2025; accepted December 26, 2025
Abstract
The rapid growth of digital platforms has transformed how consumers interact with the marketplace and led to new challenges for consumer protection. This Perspective describes how the Federal Trade Commission’s Bureau of Economics uses behavioral insights and empirical methods to support efforts to prevent unfair or deceptive business practices in digital markets. We highlight two studies that address critical knowledge gaps in digital consumer protection, including how consumers perceive and respond to advertising disclosures and how digital design choices affect the accessibility and effectiveness of consumer reporting tools. The studies illustrate how behavioral research can be used both prospectively, to evaluate potential remedies, and retrospectively, to assess the effects of past Federal Trade Commission (FTC) actions. The first study is a laboratory experiment that examines how the salience of advertising disclosures influences consumer recognition of and engagement with advertising content, where engagement is defined as the time users spend viewing ads. The second is a retrospective analysis of a redesigned consumer complaint website, using a natural experiment to evaluate the effect of usability improvements on complaint submission rates and information quality. Together, these studies demonstrate how applied research on user behavior can inform marketplace oversight and the design of consumer-facing tools. We conclude by outlining ongoing efforts to expand the role of empirical research at the FTC to strengthen the foundation for evidence-based policymaking in an increasingly complex digital environment.
Data, Materials, and Software Availability
There are no data underlying this work.
Acknowledgments
The views expressed in this article are those of the authors. They do not necessarily represent those of the Federal Trade Commission or any of its Commissioners. The US Government retains and the publisher, by accepting this article for publication, acknowledges that the US Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so for US Government purposes. We thank Katherine Chang, Baruch Fischhoff, Patrick McAlvanah, Dave Schmidt, and two anonymous referees for their comments on this article, as well as Alycia Chin and Baruch Fischhoff for organizing this special feature.
Author contributions
N.L. and D.R.R. wrote the paper.
Competing interests
The authors declare no competing interest.
References
1
A. Ferguson, N. Lew, M. Lipsitz, D. Raval, Economics at the FTC: Spatial demand, veterinary hospital mergers, rulemaking, and noncompete agreements. Rev. Ind. Organ. 63, 435–465 (2023).
2
M. W. Sullivan, “Economic analysis of hotel resort fees” (Federal Trade Commission Bureau of Economics, Washington, DC, 2017).
3
H. A. Shelanski et al., Economics at the FTC: Drug and PBM mergers and drip pricing. Rev. Ind. Organ. 41, 303–319 (2012).
4
Federal Trade Commission, Merger retrospective program (2025). https://www.ftc.gov/policy/studies/merger-retrospective-program Accessed 29 June 2025.
5
M. Hastak, M. B. Mazis, Three decades of marketing academic input at the Federal Trade Commission: Contributions to research, policy making, and litigation. J. Public Policy Mark. 33, 232–243 (2014).
6
P. McAlvanah, K. B. Anderson, R. Letzler, J. Mountjoy, Fraudulent advertising susceptibility: An experimental approach. SSRN Electron. J., https://doi.org/10.2139/ssrn.2593898 (2015).
7
D. H. Wood, Communication-Enhancing Vagueness. Games 13, 49 (2022).
8
L. R. Anderson, B. A. Freeborn, P. McAlvanah, A. Turscak, Pay every subject or pay only some? J. Risk Uncertain. 66, 161–188 (2023).
9
S. Bucher, A. Caplin, R. Oprea, E. Spurlino, K. Chang, “Clear disclosures” in FTC Conference on Marketing and Public Policy (Washington, DC, 2024). https://www.ftc.gov/system/files/ftc_gov/pdf/clear-disclosures-eric-spurlino.pdf 18 October 2024.
10
M. T. Jones, Strategic complexity and cooperation: An experimental study. J. Econ. Behav. Organ. 106, 352–366 (2014).
11
C. A. Cox, M. T. Jones, K. E. Pflum, P. J. Healy, Revealed reputations in the finitely repeated prisoners’ dilemma. Econ. Theory 58, 441–484 (2015).
12
E. Spurlino, Rationally inattentive and strategically (un)Sophisticated (2022). https://spurlino.github.io/ericspurlino.com/Spurlino_JMP.pdf Accessed 16 September 2025.
13
D. Bradford, C. Courtemanche, G. Heutel, P. McAlvanah, C. Ruhm, Time preferences and consumer behavior. J. Risk Uncertain. 55, 119–145 (2017).
14
B. Casner, Learning while shopping: An experimental investigation into the effect of learning on consumer search. Exp. Econ. 24, 238–273 (2021).
15
C. Courtemanche, G. Heutel, P. McAlvanah, Impatience, incentives and obesity. Econ. J. 125, 1–31 (2015).
16
P. McAlvanah, C. C. Moul, The house doesn’t always win: Evidence of anchoring among Australian bookies. J. Econ. Behav. Organ. 90, 87–99 (2013).
17
J. M. Lacko, J. K. Pappalardo, “Improving consumer mortgage disclosures: An empirical assessment of current and prototype disclosure forms” (Federal Trade Commission, Washington, DC, 2007).
18
J. M. Lacko, J. K. Pappalardo, “The effect of mortgage broker compensation disclosures on consumers and competition: A controlled experiment” (Federal Trade Commission, Washington, DC, 2004).
19
R. Letzler, R. Sandler, A. Jaroszewicz, I. Knowles, L. M. Olson, Knowing when to quit: Default choices, demographics and fraud. Econ. J. 127, 2617–2640 (2017).
20
X. Gabaix, D. Laibson, Shrouded attributes, consumer myopia, and information suppression in competitive markets. Q. J. Econ. 121, 505–540 (2006).
21
L. Rayo, I. Segal, Optimal information disclosure. J. Polit. Econ. 118, 949–987 (2010).
22
Federal Trade Commission, “Dot com disclosures: Information on online advertising” (Federal Trade Commission, Washington, DC, 2000).
23
Federal Trade Commission, .com Disclosures: How to Make Effective Disclosures in Digital Advertising (Federal Trade Commission, 2013).
24
Federal Trade Commission, “Blurred lines: An exploration of consumers’ advertising recognition in the contexts of search engines and native advertising” (Federal Trade Commission, Washington, DC, 2017).
25
J. Johnson, M. Hastak, B. J. Jansen, D. Raval, “Analyzing advertising labels: Testing consumers’” in Recognition of Paid Content Online in Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (ACM, 2018), pp. 1–6.
26
J. Johnson, Designing with the Mind in Mind, Second (Elsevier, 2014).
27
Z. Afsari, A. Keshava, J. P. Ossandón, P. König, Interindividual differences among native right-to-left readers and native left-to-right readers during free viewing task. Vis. Cogn. 26, 430–441 (2018).
28
X. Li, C. F. Camerer, Predictable effects of visual salience in experimental decisions and games. Q. J. Econ. 137, 1849–1900 (2022).
29
P. Bordalo, N. Gennaioli, A. Shleifer, Salience. Annu. Rev. Econ. 14, 521–544 (2022).
30
N. S. Sahni, H. S. Nair, Does advertising serve as a signal? Evidence from a field experiment in mobile search. Rev. Econ. Stud. 87, 1529–1564 (2020).
31
N. S. Sahni, H. S. Nair, Sponsorship disclosure and consumer deception: Experimental evidence from native advertising in mobile search. Mark. Sci. 39, 5–32 (2020).
32
A. R. Brough, D. A. Norton, S. L. Sciarappa, L. K. John, The bulletproof glass effect: Unintended consequences of privacy notices. J. Mark. Res. 59, 739–754 (2022).
33
P. Bordalo, N. Gennaioli, A. Shleifer, Salience and consumer choice. J. Polit. Econ. 121, 803–843 (2013).
34
Federal Trade Commission, “Native advertising: A guide for businesses” (Federal Trade Commission, Washington, DC, 2015).
35
Federal Trade Commission, “Enforcement policy statement on deceptively formatted advertisements” (Federal Trade Commission, Washington, DC, 2015).
36
E. Schnadower Mustri, I. Adjerid, A. Acquisti, Behavioral advertising and consumer welfare (2023). https://papers.ssrn.com/abstract=4398428 Accessed 15 December 2025.
37
Federal Trade Commission, Data spotlight (2025). https://www.ftc.gov/news-events/data-visualizations/data-spotlight Accessed 14 December 2025.
38
K. B. Anderson, To whom do victims of mass-market consumer fraud complain? (2021). https://papers.ssrn.com/abstract=3852323 Accessed 14 December 2025.
39
D. Raval, Whose voice do we hear in the marketplace? Evidence from consumer complaining behavior. Mark. Sci. 39, 168–187 (2020).
40
A. Sweeting, D. J. Balan, N. Kreisle, M. T. Panhans, D. Raval, Economics at the FTC: Fertilizer, consumer complaints, and private label cereal. Rev. Ind. Organ. 57, 751–781 (2020).
41
M. Grosz, D. Raval, Amplifying consumers’ voice: The Federal Trade Commission’s report fraud website redesign. Mark. Sci. 44, 525–545 (2025).
42
Federal Trade Commission, “Bringing dark patterns to light” (Federal Trade Commission, Washington, DC, 2022).
43
J. Luguri, L. J. Strahilevitz, Shining a light on dark patterns. J. Leg. Anal. 13, 43–109 (2021).
44
B. G. A. Akerlof, “The economics of ‘tagging’ as applied to the optimal income tax, welfare programs, and manpower planning” in Explorations in Pragmatic Economics, G. A. Akerlof, Ed. (Oxford University Press, Oxford, 2005), pp. 100–118.
45
A. L. Nichols, R. J. Zeckhauser, Targeting transfers through restrictions on recipients. Am. Econ. Rev. 72, 372–377 (1982).
46
K. Aquino, A. Reed, The self-importance of moral identity. J. Pers. Soc. Psychol. 83, 1423–1440 (2002).
47
E. Fehr, U. Fischbacher, The nature of human altruism. Nature 425, 785–791 (2003).
48
W. Hofmann, D. C. Wisneski, M. J. Brandt, L. J. Skitka, Morality in everyday life. Science 345, 1340–1343 (2014).
49
J. Zaki, J. P. Mitchell, Equitable decision making is associated with neural markers of intrinsic value. Proc. Natl. Acad. Sci. U.S.A. 108, 19761–19766 (2011).
50
D. S. Lee, T. Lemieux, Regression discontinuity designs in economics. J. Econ. Lit. 48, 281–355 (2010).
51
M. Grootendorst, BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv [Preprint] (2022). https://doi.org/10.48550/ARXIV.2203.05794 (Accessed 16 September 2025).
52
D. Hosken, F. Pinter, D. Raval, How do consumers respond to antitrust policy? Evidence from supermarket divestitures. https://deveshraval.github.io/voiceAntitrust.pdf
53
G. W. Harrison, J. A. List, Field experiments. J. Econ. Lit. 42, 1009–1055 (2004).
54
S. D. Levitt, J. A. List, Field experiments in economics: The past, the present, and the future. Eur. Econ. Rev. 53, 1–18 (2009).
55
O. Bandiera, I. Barankay, I. Rasul, Field experiments with firms. J. Econ. Perspect. 25, 63–82 (2011).
56
Agency Information Collection Activities, Proposed OMB Generic Clearance, Comment Request, Generic clearance for information collection using voluntary surveys for studies conducted by the federal trade commission bureau of economics to support the FTC’s missions to protect consumers and competition. Federal Register (2025). https://www.federalregister.gov/documents/2025/07/08/2025-12627/agency-information-collection-activities-proposed-omb-generic-clearance-comment-request-generic Accessed 14 December 2025.
57
B. C. Dealy et al., Willingness to pay to standardize patient medication information. Appl. Econ. 53, 1112–1126 (2021).
58
J. Duckhorn et al., The FDA’s message testing: Putting health literacy advice into practice. Inf. Serv. Use. 39, 59–67 (2019).
59
B. Fischhoff, Breaking Ground for psychological science: The U.S. food and drug administration. Am. Psychol. 72, 118–125 (2017).
60
B. Bian, M. Pagel, H. Tang, D. Raval, “Consumer surveillance and financial fraud” (National Bureau of Economic Research, 2023).
61
D. Raval, M. Grosz, Fraud across borders (2023). https://papers.ssrn.com/abstract=4333120 Accessed 14 December 2025.
62
D. Raval, T. Rosenbaum, The cyclicality of fraud (2025). https://www.tedrosenbaum.org/publications/52085 Accessed 16 September 2025.
63
D. Raval, Which communities complain to policymakers? Evidence from consumer sentinel. Econ. Inq. 58, 1628–1642 (2020).
64
M. DeLiema, P. Witt, Profiling consumers who reported mass marketing scams: Demographic characteristics and emotional sentiments associated with victimization. Secur. J. 37, 921–964 (2024).
65
M. Deliema, D. Shadel, K. Pak, Profiling victims of investment fraud: Mindsets and risky behaviors. J. Consum. Res. 46, 904–914 (2020).
66
D. Raval, Who is victimized by fraud? Evidence from consumer protection cases. J. Consum. Policy 44, 43–72 (2021).
67
Federal Trade Commission, “Serving communities of color” (Federal Trade Commission, 2021).
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Copyright © 2026 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
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Submission history
Published online: July 6, 2026
Published in issue: July 14, 2026
Keywords
Acknowledgments
The views expressed in this article are those of the authors. They do not necessarily represent those of the Federal Trade Commission or any of its Commissioners. The US Government retains and the publisher, by accepting this article for publication, acknowledges that the US Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so for US Government purposes. We thank Katherine Chang, Baruch Fischhoff, Patrick McAlvanah, Dave Schmidt, and two anonymous referees for their comments on this article, as well as Alycia Chin and Baruch Fischhoff for organizing this special feature.
Author contributions
N.L. and D.R.R. wrote the paper.
Competing interests
The authors declare no competing interest.
Notes
This article is a PNAS Direct Submission.
*
With Executive Order 14215, “Ensuring Accountability for All Agencies,” extending Executive Order 12866, “Regulatory Planning and Review,” Office of Information and Regulatory Affairs (OIRA) review to all federal agency regulations that were previously exempt, the FTC’s rulemaking process may increasingly resemble that of other federal agencies. However, certain procedural requirements remain unique to the FTC (1).
†
For the FTC’s settlement with Amazon, see https://www.ftc.gov/news-events/news/press-releases/2025/09/ftc-secures-historic-25-billion-settlement-against-amazon The FTC is now in the process of proposing a rulemaking to address unfair and deceptive fees in rental housing. See: https://www.ftc.gov/news-events/news/press-releases/2026/01/ftc-submits-draft-anprm-related-rental-housing-fees-omb-review On July 8th, 2025, the U.S. Court of Appeals for the Eight Circuit vacated the Negative Option Final Rule amendments. See https://ecf.ca8.uscourts.gov/opndir/25/07/243137P.pdf for more details. The FTC is now considering new amendments to the Negative Option Rule: see https://www.ftc.gov/news-events/news/press-releases/2026/01/ftc-submits-draft-anprm-related-negative-option-plans-omb-review
‡
Independent research undergoes substantive review within BE by the Assistant and Deputy Directors for Research, as well as a distinct review by the Office of the General Counsel to ensure compliance with confidentiality requirements. Directed research is reviewed by multiple Bureaus and Offices and by the offices of all Commissioners, and its external release must be authorized by a Commission vote.
§
Alongside economists, marketing researchers have also contributed behavioral research that supports the FTC’s consumer protection mission (5).
¶
Organic content refers to material that users encounter naturally in digital environments, such as algorithmic search results, social media posts from friends or followed accounts, or editorial content, rather than content that appears because a firm has paid for placement or promotion.
#
The letter stated “Since then [referring to letters sent in 2002], however, we have observed a decline in compliance with the letter’s guidance.” and “In recent years, the features traditional search engines use to differentiate advertising from natural search results have become less noticeable to consumers, especially for advertising located immediately above the natural results (“top ads”). Indeed, a recent online survey by a search strategies company found that nearly half of searchers did not recognize top ads as distinct from natural search results and said the background shading used to distinguish the ads was white.” See https://www.ftc.gov/news-events/news/press-releases/2013/06/ftc-consumer-protection-staff-updates-agencys-guidance-search-engine-industry-need-distinguish For the native advertising workshop, see https://www.ftc.gov/news-events/events/2013/12/blurred-lines-advertising-or-content-ftc-workshop-native-advertising For the Mary Engle quote, see https://searchengineland.com/ftc-search-engine-disclosure-164722
See https://www.ftc.gov/enforcement/consumer-sentinel-network for more details on the Consumer Sentinel Network. The Consumer Sentinel Network received 6.5 million complaints in 2024.
††
This case was brought against Ideal Financial, a company that bought consumer payday loan applications and then used the bank account details in the applications to withdraw money from the consumers’ bank accounts without their consent. See ref. 39.
‡‡
§§
For the FTC’s Tableau page, see https://public.tableau.com/app/profile/federal.trade.commission For the FTC’s data spotlights, see https://www.ftc.gov/news-events/data-visualizations/data-spotlight For details on the Division of Consumer and Business Education, see https://www.ftc.gov/about-ftc/bureaus-offices/bureau-consumer-protection/our-divisions/division-consumer-business
¶¶
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User interaction with digital platforms: A consumer protection perspective, Proc. Natl. Acad. Sci. U.S.A.
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https://doi.org/10.1073/pnas.2525996123
(2026).
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References
1
A. Ferguson, N. Lew, M. Lipsitz, D. Raval, Economics at the FTC: Spatial demand, veterinary hospital mergers, rulemaking, and noncompete agreements. Rev. Ind. Organ. 63, 435–465 (2023).
2
M. W. Sullivan, “Economic analysis of hotel resort fees” (Federal Trade Commission Bureau of Economics, Washington, DC, 2017).
3
H. A. Shelanski et al., Economics at the FTC: Drug and PBM mergers and drip pricing. Rev. Ind. Organ. 41, 303–319 (2012).
4
Federal Trade Commission, Merger retrospective program (2025). https://www.ftc.gov/policy/studies/merger-retrospective-program Accessed 29 June 2025.
5
M. Hastak, M. B. Mazis, Three decades of marketing academic input at the Federal Trade Commission: Contributions to research, policy making, and litigation. J. Public Policy Mark. 33, 232–243 (2014).
6
P. McAlvanah, K. B. Anderson, R. Letzler, J. Mountjoy, Fraudulent advertising susceptibility: An experimental approach. SSRN Electron. J., https://doi.org/10.2139/ssrn.2593898 (2015).
7
D. H. Wood, Communication-Enhancing Vagueness. Games 13, 49 (2022).
8
L. R. Anderson, B. A. Freeborn, P. McAlvanah, A. Turscak, Pay every subject or pay only some? J. Risk Uncertain. 66, 161–188 (2023).
9
S. Bucher, A. Caplin, R. Oprea, E. Spurlino, K. Chang, “Clear disclosures” in FTC Conference on Marketing and Public Policy (Washington, DC, 2024). https://www.ftc.gov/system/files/ftc_gov/pdf/clear-disclosures-eric-spurlino.pdf 18 October 2024.
10
M. T. Jones, Strategic complexity and cooperation: An experimental study. J. Econ. Behav. Organ. 106, 352–366 (2014).
11
C. A. Cox, M. T. Jones, K. E. Pflum, P. J. Healy, Revealed reputations in the finitely repeated prisoners’ dilemma. Econ. Theory 58, 441–484 (2015).
12
E. Spurlino, Rationally inattentive and strategically (un)Sophisticated (2022). https://spurlino.github.io/ericspurlino.com/Spurlino_JMP.pdf Accessed 16 September 2025.
13
D. Bradford, C. Courtemanche, G. Heutel, P. McAlvanah, C. Ruhm, Time preferences and consumer behavior. J. Risk Uncertain. 55, 119–145 (2017).
14
B. Casner, Learning while shopping: An experimental investigation into the effect of learning on consumer search. Exp. Econ. 24, 238–273 (2021).
15
C. Courtemanche, G. Heutel, P. McAlvanah, Impatience, incentives and obesity. Econ. J. 125, 1–31 (2015).
16
P. McAlvanah, C. C. Moul, The house doesn’t always win: Evidence of anchoring among Australian bookies. J. Econ. Behav. Organ. 90, 87–99 (2013).
17
J. M. Lacko, J. K. Pappalardo, “Improving consumer mortgage disclosures: An empirical assessment of current and prototype disclosure forms” (Federal Trade Commission, Washington, DC, 2007).
18
J. M. Lacko, J. K. Pappalardo, “The effect of mortgage broker compensation disclosures on consumers and competition: A controlled experiment” (Federal Trade Commission, Washington, DC, 2004).
19
R. Letzler, R. Sandler, A. Jaroszewicz, I. Knowles, L. M. Olson, Knowing when to quit: Default choices, demographics and fraud. Econ. J. 127, 2617–2640 (2017).
20
X. Gabaix, D. Laibson, Shrouded attributes, consumer myopia, and information suppression in competitive markets. Q. J. Econ. 121, 505–540 (2006).
21
L. Rayo, I. Segal, Optimal information disclosure. J. Polit. Econ. 118, 949–987 (2010).
22
Federal Trade Commission, “Dot com disclosures: Information on online advertising” (Federal Trade Commission, Washington, DC, 2000).
23
Federal Trade Commission, .com Disclosures: How to Make Effective Disclosures in Digital Advertising (Federal Trade Commission, 2013).
24
Federal Trade Commission, “Blurred lines: An exploration of consumers’ advertising recognition in the contexts of search engines and native advertising” (Federal Trade Commission, Washington, DC, 2017).
25
J. Johnson, M. Hastak, B. J. Jansen, D. Raval, “Analyzing advertising labels: Testing consumers’” in Recognition of Paid Content Online in Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (ACM, 2018), pp. 1–6.
26
J. Johnson, Designing with the Mind in Mind, Second (Elsevier, 2014).
27
Z. Afsari, A. Keshava, J. P. Ossandón, P. König, Interindividual differences among native right-to-left readers and native left-to-right readers during free viewing task. Vis. Cogn. 26, 430–441 (2018).
28
X. Li, C. F. Camerer, Predictable effects of visual salience in experimental decisions and games. Q. J. Econ. 137, 1849–1900 (2022).
29
P. Bordalo, N. Gennaioli, A. Shleifer, Salience. Annu. Rev. Econ. 14, 521–544 (2022).
30
N. S. Sahni, H. S. Nair, Does advertising serve as a signal? Evidence from a field experiment in mobile search. Rev. Econ. Stud. 87, 1529–1564 (2020).
31
N. S. Sahni, H. S. Nair, Sponsorship disclosure and consumer deception: Experimental evidence from native advertising in mobile search. Mark. Sci. 39, 5–32 (2020).
32
A. R. Brough, D. A. Norton, S. L. Sciarappa, L. K. John, The bulletproof glass effect: Unintended consequences of privacy notices. J. Mark. Res. 59, 739–754 (2022).
33
P. Bordalo, N. Gennaioli, A. Shleifer, Salience and consumer choice. J. Polit. Econ. 121, 803–843 (2013).
34
Federal Trade Commission, “Native advertising: A guide for businesses” (Federal Trade Commission, Washington, DC, 2015).
35
Federal Trade Commission, “Enforcement policy statement on deceptively formatted advertisements” (Federal Trade Commission, Washington, DC, 2015).
36
E. Schnadower Mustri, I. Adjerid, A. Acquisti, Behavioral advertising and consumer welfare (2023). https://papers.ssrn.com/abstract=4398428 Accessed 15 December 2025.
37
Federal Trade Commission, Data spotlight (2025). https://www.ftc.gov/news-events/data-visualizations/data-spotlight Accessed 14 December 2025.
38
K. B. Anderson, To whom do victims of mass-market consumer fraud complain? (2021). https://papers.ssrn.com/abstract=3852323 Accessed 14 December 2025.
39
D. Raval, Whose voice do we hear in the marketplace? Evidence from consumer complaining behavior. Mark. Sci. 39, 168–187 (2020).
40
A. Sweeting, D. J. Balan, N. Kreisle, M. T. Panhans, D. Raval, Economics at the FTC: Fertilizer, consumer complaints, and private label cereal. Rev. Ind. Organ. 57, 751–781 (2020).
41
M. Grosz, D. Raval, Amplifying consumers’ voice: The Federal Trade Commission’s report fraud website redesign. Mark. Sci. 44, 525–545 (2025).
42
Federal Trade Commission, “Bringing dark patterns to light” (Federal Trade Commission, Washington, DC, 2022).
43
J. Luguri, L. J. Strahilevitz, Shining a light on dark patterns. J. Leg. Anal. 13, 43–109 (2021).
44
B. G. A. Akerlof, “The economics of ‘tagging’ as applied to the optimal income tax, welfare programs, and manpower planning” in Explorations in Pragmatic Economics, G. A. Akerlof, Ed. (Oxford University Press, Oxford, 2005), pp. 100–118.
45
A. L. Nichols, R. J. Zeckhauser, Targeting transfers through restrictions on recipients. Am. Econ. Rev. 72, 372–377 (1982).
46
K. Aquino, A. Reed, The self-importance of moral identity. J. Pers. Soc. Psychol. 83, 1423–1440 (2002).
47
E. Fehr, U. Fischbacher, The nature of human altruism. Nature 425, 785–791 (2003).
48
W. Hofmann, D. C. Wisneski, M. J. Brandt, L. J. Skitka, Morality in everyday life. Science 345, 1340–1343 (2014).
49
J. Zaki, J. P. Mitchell, Equitable decision making is associated with neural markers of intrinsic value. Proc. Natl. Acad. Sci. U.S.A. 108, 19761–19766 (2011).
50
D. S. Lee, T. Lemieux, Regression discontinuity designs in economics. J. Econ. Lit. 48, 281–355 (2010).
51
M. Grootendorst, BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv [Preprint] (2022). https://doi.org/10.48550/ARXIV.2203.05794 (Accessed 16 September 2025).
52
D. Hosken, F. Pinter, D. Raval, How do consumers respond to antitrust policy? Evidence from supermarket divestitures. https://deveshraval.github.io/voiceAntitrust.pdf
53
G. W. Harrison, J. A. List, Field experiments. J. Econ. Lit. 42, 1009–1055 (2004).
54
S. D. Levitt, J. A. List, Field experiments in economics: The past, the present, and the future. Eur. Econ. Rev. 53, 1–18 (2009).
55
O. Bandiera, I. Barankay, I. Rasul, Field experiments with firms. J. Econ. Perspect. 25, 63–82 (2011).
56
Agency Information Collection Activities, Proposed OMB Generic Clearance, Comment Request, Generic clearance for information collection using voluntary surveys for studies conducted by the federal trade commission bureau of economics to support the FTC’s missions to protect consumers and competition. Federal Register (2025). https://www.federalregister.gov/documents/2025/07/08/2025-12627/agency-information-collection-activities-proposed-omb-generic-clearance-comment-request-generic Accessed 14 December 2025.
57
B. C. Dealy et al., Willingness to pay to standardize patient medication information. Appl. Econ. 53, 1112–1126 (2021).
58
J. Duckhorn et al., The FDA’s message testing: Putting health literacy advice into practice. Inf. Serv. Use. 39, 59–67 (2019).
59
B. Fischhoff, Breaking Ground for psychological science: The U.S. food and drug administration. Am. Psychol. 72, 118–125 (2017).
60
B. Bian, M. Pagel, H. Tang, D. Raval, “Consumer surveillance and financial fraud” (National Bureau of Economic Research, 2023).
61
D. Raval, M. Grosz, Fraud across borders (2023). https://papers.ssrn.com/abstract=4333120 Accessed 14 December 2025.
62
D. Raval, T. Rosenbaum, The cyclicality of fraud (2025). https://www.tedrosenbaum.org/publications/52085 Accessed 16 September 2025.
63
D. Raval, Which communities complain to policymakers? Evidence from consumer sentinel. Econ. Inq. 58, 1628–1642 (2020).
64
M. DeLiema, P. Witt, Profiling consumers who reported mass marketing scams: Demographic characteristics and emotional sentiments associated with victimization. Secur. J. 37, 921–964 (2024).
65
M. Deliema, D. Shadel, K. Pak, Profiling victims of investment fraud: Mindsets and risky behaviors. J. Consum. Res. 46, 904–914 (2020).
66
D. Raval, Who is victimized by fraud? Evidence from consumer protection cases. J. Consum. Policy 44, 43–72 (2021).
67
Federal Trade Commission, “Serving communities of color” (Federal Trade Commission, 2021).
Sentinel — Human
This text is highly characteristic of academic scholarship, demonstrating the structured synthesis of empirical research to inform policy, suggesting a human-led analytical process.
