IDEAS home Printed from https://ideas.repec.org/p/cde/cdewps/346.html
   My bibliography  Save this paper

Optimal (Non-) Disclosure Defaults

Author

Listed:
  • Giuseppe Dari-Mattiacci

    (University of Amsterdam)

  • Sander Onderstal

    (University of Amsterdam)

  • Francesco Parisi

    (University of Minnesota)

  • Ram Singh

    (Department of Economics, Delhi School of Economics)

Abstract

It is well known that sellers have a general obligation to disclose “negative” information about hidden defects of their products. In contrast, buyers usually do not have a binding obligation to disclose “positive” information about the hidden qualities of the products. The leading explanation for the asymmetric treatment of the two sides - buyers and sellers - is provided by appealing to incentives to invest in relevant information. It is argued that the imposition of disclosure duties on buyers would undermine their incentives to acquire socially useful but costly information ex-ante. This explanation is unsatisfactory. First, the failure to correct asymmetric information problems ex-post would cause, as we will show,an inverse adverse selection problem ex-ante. This would lead to the uninformed sellers’withdrawal from the market. Consequently, resources would not move to (informed)buyers with higher valuations. In this paper, we develop a model to balance the benefits of information acquisition, on the one hand, with the costs of asymmetric information, on the other hand. We use the framework to study the incentives created by different defaultdisclosure and non-disclosure - rules. We examine the optimum default rules by showing that the choice of alternative disclosure rules makes a difference when parties can contract around defaults at a moderate cost. Unlike disclosure rules, non-disclosure default rules yield partially separating equilibria that preserve the buyers’ incentives to acquire information and foster trade opportunities between expert and uninformed sellers. JEL Code: D44, D82, D86, K12

Suggested Citation

  • Giuseppe Dari-Mattiacci & Sander Onderstal & Francesco Parisi & Ram Singh, 2024. "Optimal (Non-) Disclosure Defaults," Working papers 346, Centre for Development Economics, Delhi School of Economics.
  • Handle: RePEc:cde:cdewps:346
    as

    Download full text from publisher

    File URL: http://www.cdedse.org/pdf/work346.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hinloopen, Jeroen & Onderstal, Sander & Treuren, Leonard, 2020. "Cartel stability in experimental first-price sealed-bid and English auctions," International Journal of Industrial Organization, Elsevier, vol. 71(C).
    2. Bebchuk, Lucian Ayre & Shavell, Steven, 1991. "Information and the Scope of Liability for Breach of Contract: The Rule of Hadley vs. Baxendale," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 7(2), pages 284-312, Fall.
    3. Grossman, Sanford J, 1981. "The Informational Role of Warranties and Private Disclosure about Product Quality," Journal of Law and Economics, University of Chicago Press, vol. 24(3), pages 461-483, December.
    4. Hirshleifer, Jack, 1971. "The Private and Social Value of Information and the Reward to Inventive Activity," American Economic Review, American Economic Association, vol. 61(4), pages 561-574, September.
    5. Paul R. Milgrom, 1981. "Good News and Bad News: Representation Theorems and Applications," Bell Journal of Economics, The RAND Corporation, vol. 12(2), pages 380-391, Autumn.
    6. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miguel Faria-e-Castro & Joseba Martinez & Thomas Philippon, 2017. "Runs versus Lemons: Information Disclosure and Fiscal Capacity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(4), pages 1683-1707.
    2. Beyer, Anne & Cohen, Daniel A. & Lys, Thomas Z. & Walther, Beverly R., 2010. "The financial reporting environment: Review of the recent literature," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 296-343, December.
    3. Benjamin Hermalin & Michael Katz, 2006. "Privacy, property rights and efficiency: The economics of privacy as secrecy," Quantitative Marketing and Economics (QME), Springer, vol. 4(3), pages 209-239, September.
    4. Giuseppe Dari-Mattiacci & Sander Onderstal & Francesco Parisi & Ram Singh, 2023. "Information-Forcing Effects of Non-Disclosure Rules," Working papers 338, Centre for Development Economics, Delhi School of Economics.
    5. Glode, Vincent & Opp, Christian C. & Zhang, Xingtan, 2018. "Voluntary disclosure in bilateral transactions," Journal of Economic Theory, Elsevier, vol. 175(C), pages 652-688.
    6. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    7. Georgakopoulos, Nicholas L., 1996. "Why should disclosure rules subsidize informed traders?," International Review of Law and Economics, Elsevier, vol. 16(4), pages 417-431, December.
    8. Ginger Zhe Jin & Andrew Kato & John A. List, 2010. "That’S News To Me! Information Revelation In Professional Certification Markets," Economic Inquiry, Western Economic Association International, vol. 48(1), pages 104-122, January.
    9. Haisken-DeNew, John & Hasan, Syed & Jha, Nikhil & Sinning, Mathias, 2018. "Unawareness and selective disclosure: The effect of school quality information on property prices," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 449-464.
    10. Alvarez, Fernando & Barlevy, Gadi, 2021. "Mandatory disclosure and financial contagion," Journal of Economic Theory, Elsevier, vol. 194(C).
    11. B. Charumathi & Latha Ramesh, 2020. "Impact of Voluntary Disclosure on Valuation of Firms: Evidence from Indian Companies," Vision, , vol. 24(2), pages 194-203, June.
    12. Seth Freedman & Ginger Zhe Jin, 2008. "Do Social Networks Solve Information Problems for Peer-to-Peer Lending? Evidence from Prosper.com," Working Papers 08-43, NET Institute.
    13. Müller, Raphael & Spengel, Christoph & Vay, Heiko, 2020. "On the determinants and effects of corporate tax transparency: Review of an emerging literature," ZEW Discussion Papers 20-063, ZEW - Leibniz Centre for European Economic Research.
    14. Sendhil Mullainathan & Joshua Schwartzstein & Andrei Shleifer, 2008. "Coarse Thinking and Persuasion," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(2), pages 577-619.
    15. Sergiu Hart & Ilan Kremer & Motty Perry, 2017. "Evidence Games: Truth and Commitment," American Economic Review, American Economic Association, vol. 107(3), pages 690-713, March.
    16. Christof Beuselinck & Marc Deloof & Sophie Manigart, 2008. "Private Equity Investments and Disclosure Policy," European Accounting Review, Taylor & Francis Journals, vol. 17(4), pages 607-639.
    17. Benndorf, Volker & Kübler, Dorothea & Normann, Hans-Theo, 2015. "Privacy concerns, voluntary disclosure of information, and unraveling: An experiment," European Economic Review, Elsevier, vol. 75(C), pages 43-59.
    18. Hong, Xianpei & Zhou, Menghuan & Gong, Yeming, 2021. "Dilemma of quality information disclosure in technology licensing," European Journal of Operational Research, Elsevier, vol. 294(2), pages 543-557.
    19. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    20. Florian Hoffmann & Roman Inderst & Marco Ottaviani, 2013. "Hypertargeting, Limited Attention, and Privacy: Implications for Marketing and Campaigning," Working Papers 479, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    More about this item

    Keywords

    asymmetric information; penalty default rules; inverse adverse selection;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • K12 - Law and Economics - - Basic Areas of Law - - - Contract Law

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cde:cdewps:346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sanjeev Sharma (email available below). General contact details of provider: https://edirc.repec.org/data/cdudein.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.