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Auction Design with Data-Driven Misspecifications


We study the existence of e¢cient auctions in private value settings in which some bidders choose their bids based on the accessible data from past similar auctions consisting of bids and ex post 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 show our main result that there is no e¢cient auction in such environments.
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halshs-03735747 , version 1 (21-07-2022)


  • HAL Id : halshs-03735747 , version 1


Philippe Jehiel, Konrad Mierendorff. Auction Design with Data-Driven Misspecifications. 2022. ⟨halshs-03735747⟩
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