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Finite Optimal Penalties for False Advertising

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  • Kenneth S. Corts

Abstract

type="main"> I consider a setting in which firms have unverifiable private information about their type, which corresponds to their probable product quality; firms can expend a learning cost in order to observe their quality; and the regulator can enforce false advertising penalties contingent only on verifiable realized quality. I show that it may be socially optimal for high type firms to signal their type through ‘speculative claims,’ rather than to learn and signal their quality. This implies that socially optimal false advertising penalties are finite, in contrast to the literature's common assumption of arbitrarily high false advertising penalties, and that the regulator optimally tolerates the existence of some false claims in equilibrium.

Suggested Citation

  • Kenneth S. Corts, 2014. "Finite Optimal Penalties for False Advertising," Journal of Industrial Economics, Wiley Blackwell, vol. 62(4), pages 661-681, December.
    • Handle: RePEc:bla:jindec:v:62:y:2014:i:4:p:661-681
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    References listed on IDEAS

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    Cited by:

    1. J. K. Pappalardo, 2022. "Economics of Consumer Protection: Contributions and Challenges in Estimating Consumer Injury and Evaluating Consumer Protection Policy," Journal of Consumer Policy, Springer, vol. 45(2), pages 201-238, June.
    2. Casner, Ben, 2020. "Seller curation in platforms," International Journal of Industrial Organization, Elsevier, vol. 72(C).
    3. Yue Wu & Tansev Geylani, 2020. "Regulating Deceptive Advertising: False Claims and Skeptical Consumers," Marketing Science, INFORMS, vol. 39(4), pages 788-806, July.
    4. Dahm, Matthias & González, Paula & Porteiro, Nicolás, 2018. "The enforcement of mandatory disclosure rules," Journal of Public Economics, Elsevier, vol. 167(C), pages 21-32.
    5. Serafin Grundl & You Suk Kim, 2019. "Consumer mistakes and advertising: The case of mortgage refinancing," Quantitative Marketing and Economics (QME), Springer, vol. 17(2), pages 161-213, June.
    6. Simone Ghislandi & Michael Kuhn, 2016. "Asymmetric information in the regulation of the access to markets," Department of Economics Working Papers wuwp219, Vienna University of Economics and Business, Department of Economics.
    7. Aldo Pignataro, 2019. "The effects of loss aversion on deceptive advertising policies," Theory and Decision, Springer, vol. 87(4), pages 451-472, November.
    8. Chen Jin & Luyi Yang & Kartik Hosanagar, 2023. "To Brush or Not to Brush: Product Rankings, Consumer Search, and Fake Orders," Information Systems Research, INFORMS, vol. 34(2), pages 532-552, June.
    9. Rhodes, Andrew, 2023. "A Survey on Drip Pricing and Other False Advertising," TSE Working Papers 23-1434, Toulouse School of Economics (TSE).
    10. Kemal Kıvanç Aköz & Cemal Eren Arbatli & Levent Celik, 2020. "Manipulation Through Biased Product Reviews," Journal of Industrial Economics, Wiley Blackwell, vol. 68(4), pages 591-639, December.
    11. Zhengkai Wang & Debing Ni & Kaiming Zheng, 2022. "The Role of False-Claims Ban Regulation in Greenwashing of Firms with Imprecise Greenness Information," Sustainability, MDPI, vol. 14(20), pages 1-25, October.
    12. Serafin J. Grundl & You Suk Kim, 2017. "Consumer Mistakes and Advertising : The Case of Mortgage Refinancing," Finance and Economics Discussion Series 2017-067, Board of Governors of the Federal Reserve System (U.S.).
    13. Chen Jin & Luyi Yang & Kartik Hosanagar, 2019. "To Brush or Not to Brush: Product Rankings, Customer Search, and Fake Orders," Working Papers 19-02, NET Institute.
    14. Gupta, Aastha, 2023. "Deceptive advertising, regulation and naive consumers," International Journal of Industrial Organization, Elsevier, vol. 91(C).

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