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

Philippe Jehiel () and Konrad Mierendorff

PSE-Ecole d'économie de Paris (Postprint) from HAL

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.

Keywords: Belief formation; Auctions; Efficiency; Analogy-based expectations (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Published in Theoretical Economics, 2024, 19 (4), pp.1543-1579. ⟨10.3982/te5655⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Auction design with data-driven misspecifications: inefficiency in private value auctions with correlation (2024)
Working Paper: Auction design with data-driven misspecifications: Inefficiency in private value auctions with correlation (2024)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:pseptp:halshs-04928908

DOI: 10.3982/te5655

Access Statistics for this paper

More papers in PSE-Ecole d'économie de Paris (Postprint) from HAL
Bibliographic data for series maintained by Caroline Bauer ().