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Auction design with data-driven misspecifications: Inefficiency in private value auctions with correlation

Author

Listed:
  • Philippe Jehiel

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, UCL - University College of London [London])

  • Konrad Mierendorff

    (UCL - University College of London [London])

Abstract

We study the existence of efficient auctions in private value settings in which some bidders form their expectations about the distribution of their competitor's bids based on the accessible data from past similar auctions consisting of bids and expost values. We consider steady states in such environments with a mix of rational and data-driven bidders, and we allow for correlation across bidders in the signal distributions about the ex post values. After reviewing the working of the approach in second-price and first-price auctions, we establish our main result that there is no efficient auction in such environments.

Suggested Citation

  • Philippe Jehiel & Konrad Mierendorff, 2024. "Auction design with data-driven misspecifications: Inefficiency in private value auctions with correlation," Post-Print halshs-04928908, HAL.
    • Handle: RePEc:hal:journl:halshs-04928908
    DOI: 10.3982/te5655
    as

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