IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-13-00538.html
   My bibliography  Save this article

Revealing Product Information to Bidders with Differentiated Preferences

Author

Listed:
  • Daniel Z. Li

    (Durham University Business School)

Abstract

We study information disclosure in standard auctions where bidders preferences are horizontally differentiated, whose valuations depend on the matching between the product attribute and their preferences. The seller may reveal product information in the form of partition prior to the auction. Under a symmetric setting, we show in a close-form result that more precise information induces more dispersed distributions of bidders' posterior valuations, which, specifically, are ordered in terms of First Order Stochastic Dominance (FOSD). We also prove that optimal disclosure policy is extreme, in the sense that the seller will reveal either full or no information to the bidders, depending on the number of bidders.

Suggested Citation

  • Daniel Z. Li, 2013. "Revealing Product Information to Bidders with Differentiated Preferences," Economics Bulletin, AccessEcon, vol. 33(3), pages 2235-2244.
  • Handle: RePEc:ebl:ecbull:eb-13-00538
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2013/Volume33/EB-13-V33-I3-P208.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Krishna, Vijay, 2009. "Auction Theory," Elsevier Monographs, Elsevier, edition 2, number 9780123745071.
    2. Lewis, Tracy R & Sappington, David E M, 1994. "Supplying Information to Facilitate Price Discrimination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(2), pages 309-327, May.
    3. Simon Board, 2009. "Revealing information in auctions: the allocation effect," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 38(1), pages 125-135, January.
    4. Juan-José Ganuza, 2004. "Ignorance Promotes Competition: An Auction Model of Endogenous Private Valuations," RAND Journal of Economics, The RAND Corporation, vol. 35(3), pages 583-598, Autumn.
    5. Justin P. Johnson & David P. Myatt, 2006. "On the Simple Economics of Advertising, Marketing, and Product Design," American Economic Review, American Economic Association, vol. 96(3), pages 756-784, June.
    6. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    7. Juan-JosÈ Ganuza & JosÈ S. Penalva, 2010. "Signal Orderings Based on Dispersion and the Supply of Private Information in Auctions," Econometrica, Econometric Society, vol. 78(3), pages 1007-1030, May.
    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. Daniel Z. Li, 2016. "Disclosure or not, When There are Three Bidders?," Economics Bulletin, AccessEcon, vol. 36(1), pages 349-354.
    2. Cristián Troncoso-Valverde, 2018. "Releasing information in private-value second-price auctions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(3), pages 781-817, May.
    3. Ian Jewitt & Daniel Z. Li, 2017. "Cheap Talk Advertising in Auctions: Horizontally vs Vertically Differentiated Products," Working Papers 2017_03, Durham University Business School.
    4. Ganuza, Juan-José & Penalva, Jose, 2019. "Information disclosure in optimal auctions," International Journal of Industrial Organization, Elsevier, vol. 63(C), pages 460-479.
    5. Alexandre de Corniere & Romain De Nijs, 2013. "Online Advertising and Privacy," Economics Series Working Papers 650, University of Oxford, Department of Economics.
    6. Zhou, Jidong, 2021. "Mixed bundling in oligopoly markets," Journal of Economic Theory, Elsevier, vol. 194(C).
    7. Juan-José Ganuza & José S. Penalva, 2005. "On Information and Competition in Private Value Auctions," Working Papers 158, Barcelona School of Economics.
    8. Schweizer, Nikolaus & Szech, Nora, 2017. "Revenues and welfare in auctions with information release," Journal of Economic Theory, Elsevier, vol. 170(C), pages 86-111.
    9. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    10. Hao Li & Xianwen Shi, 2017. "Discriminatory Information Disclosure," American Economic Review, American Economic Association, vol. 107(11), pages 3363-3385, November.
    11. 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.
    12. Florian Hoffmann & Roman Inderst & Marco Ottaviani, 2020. "Persuasion Through Selective Disclosure: Implications for Marketing, Campaigning, and Privacy Regulation," Management Science, INFORMS, vol. 66(11), pages 4958-4979, November.
    13. Agostino Manduchi, 2013. "Non-neutral information costs with match-value uncertainty," Journal of Economics, Springer, vol. 109(1), pages 1-25, May.
    14. Nikandrova, Arina & Pancs, Romans, 2017. "Conjugate information disclosure in an auction with learning," Journal of Economic Theory, Elsevier, vol. 171(C), pages 174-212.
    15. Forand, Jean Guillaume, 2013. "Competing through information provision," International Journal of Industrial Organization, Elsevier, vol. 31(5), pages 438-451.
    16. Maxim Ivanov, 2013. "Information revelation in competitive markets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(1), pages 337-365, January.
    17. Li, Yunan, 2019. "Efficient mechanisms with information acquisition," Journal of Economic Theory, Elsevier, vol. 182(C), pages 279-328.
    18. Maxim Ivanov, 2021. "Optimal monotone signals in Bayesian persuasion mechanisms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(3), pages 955-1000, October.
    19. Shota Ichihashi & Alex Smolin, 2023. "Buyer-Optimal Algorithmic Consumption," Working Papers 23-02, NET Institute.
    20. LI Daniel Zhiyun, 2012. "Seller Cheap Talk in Almost Common Value Auction," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 12(1), pages 1-31, March.

    More about this item

    Keywords

    Information Disclosure; Auction; Preference Differentiation; Valuation Dispersion;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D4 - Microeconomics - - Market Structure, Pricing, and Design

    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:ebl:ecbull:eb-13-00538. 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: John P. Conley (email available below). General contact details of provider: .

    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.