k bidders each demand one object. Before the auction, each bidder receives an informative but imperfect signal about the state of the world. The good that is auctioned is a common-value object for the bidders, and a bidder’s valuation for the object is determined jointly by the state of the world and an action that he chooses after winning the object but before he observes the state. We show that there are equilibria in which the auction price is completely uninformative about the state of the world and aggregates no information even in an arbitrarily large auction. In the equilibrium that we construct, because prices do not aggregate information, agents have strict incentives to acquire costly information before they participate in the market. Also, market statistics other than price, such as the amount of rationing and bid distributions contain extra information about the state. Our findings sharply contrast with past work which shows that in large auctions where there is no ex-post action, the auction price aggregates information."> k bidders each demand one object. Before the auction, each bidder receives an informative but imperfect signal about the state of the world. The good that is auctioned is a common-value object for the bidders, and a bidder’s valuation for the object is determined jointly by the state of the world and an action that he chooses after winning the object but before he observes the state. We show that there are equilibria in which the auction price is completely uninformative about the state of the world and aggregates no information even in an arbitrarily large auction. In the equilibrium that we construct, because prices do not aggregate information, agents have strict incentives to acquire costly information before they participate in the market. Also, market statistics other than price, such as the amount of rationing and bid distributions contain extra information about the state. Our findings sharply contrast with past work which shows that in large auctions where there is no ex-post action, the auction price aggregates information."> k bidders each demand one object. Before the auction, each bidder receives an infor">
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Auctions, Actions, and the Failure of Information Aggregation

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  • Alp Atakan
  • Mehmet Ekmekci
Abstract
We study a market in which k identical and indivisible objects are allocated using a uniform-price auction where n > k bidders each demand one object. Before the auction, each bidder receives an informative but imperfect signal about the state of the world. The good that is auctioned is a common-value object for the bidders, and a bidder’s valuation for the object is determined jointly by the state of the world and an action that he chooses after winning the object but before he observes the state. We show that there are equilibria in which the auction price is completely uninformative about the state of the world and aggregates no information even in an arbitrarily large auction. In the equilibrium that we construct, because prices do not aggregate information, agents have strict incentives to acquire costly information before they participate in the market. Also, market statistics other than price, such as the amount of rationing and bid distributions contain extra information about the state. Our findings sharply contrast with past work which shows that in large auctions where there is no ex-post action, the auction price aggregates information.

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  • Alp Atakan & Mehmet Ekmekci, 2012. "Auctions, Actions, and the Failure of Information Aggregation," Discussion Papers 1553, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    • Handle: RePEc:nwu:cmsems:1553
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    Cited by:

    1. Aliakbari, Elmira & McKitrick, Ross, 2018. "Information aggregation in a prediction market for climate outcomes," Energy Economics, Elsevier, vol. 74(C), pages 97-106.
    2. Debin Fang & Qiyu Ren & Qian Yu, 2018. "How Elastic Demand Affects Bidding Strategy in Electricity Market: An Auction Approach," Energies, MDPI, vol. 12(1), pages 1-13, December.
    3. José Luis Montiel Olea & Pietro Ortoleva & Mallesh Pai & Andrea Prat, 2021. "Competing Models," Working Papers 2021-89, Princeton University. Economics Department..
    4. Jose Luis Montiel Olea & Pietro Ortoleva & Mallesh M Pai & Andrea Prat, 2019. "Competing Models," Papers 1907.03809, arXiv.org, revised Nov 2021.
    5. Meirowitz, Adam & Pi, Shaoting, 2022. "Voting and trading: The shareholder’s dilemma," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1073-1096.
    6. Ryan Chahrour & Gaetano Gaballo, 2021. "Learning from House Prices: Amplification and Business Fluctuations [House Price Booms and the Current Account]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1720-1759.
    7. Kerry Back & Pierre Collin‐Dufresne & Vyacheslav Fos & Tao Li & Alexander Ljungqvist, 2018. "Activism, Strategic Trading, and Liquidity," Econometrica, Econometric Society, vol. 86(4), pages 1431-1463, July.
    8. Anne-Sophie Radermecker, 2019. "Artworks without names: an insight into the market for anonymous paintings," ULB Institutional Repository 2013/296529, ULB -- Universite Libre de Bruxelles.
    9. Michael Adusei & Ngozi Adeleye, 2022. "Credit information sharing and non‐performing loans: The moderating role of creditor rights protection," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4756-4769, October.
    10. Axelson, Ulf & Makarov, Igor, 2023. "Informational black holes in financial markets," LSE Research Online Documents on Economics 105042, London School of Economics and Political Science, LSE Library.
    11. Boleslavsky, Raphael & Kelly, David L. & Taylor, Curtis R., 2017. "Selloffs, bailouts, and feedback: Can asset markets inform policy?," Journal of Economic Theory, Elsevier, vol. 169(C), pages 294-343.
    12. Sharma, Priyanka, 2017. "Is more information always better? A case in credit markets," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 269-283.
    13. Anne-Sophie V. E. Radermecker, 2019. "Artworks without names: an insight into the market for anonymous paintings," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(3), pages 443-483, September.
    14. Heumann, Tibor, 2019. "An ascending auction with multi-dimensional signals," Journal of Economic Theory, Elsevier, vol. 184(C).
    15. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.
    16. Axelson, Ulf & Makarov, Igor, 2016. "Informational black holes in financial markets," LSE Research Online Documents on Economics 118982, London School of Economics and Political Science, LSE Library.

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    More about this item

    Keywords

    Auctions; Large markets; Information Aggregation JEL Classification Numbers: C73; D44; D82; D83.;
    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
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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