Informationally Robust Optimal Auction Design

Dirk Bergemann, Benjamin Brooks and Stephen Morris

Working Papers from Princeton University, Department of Economics, Econometric Research Program.

Abstract: A single unit of a good is to be sold by auction to one of two buyers. The good has either a high value or a low value, with known prior probabilities. The designer of the auction knows the prior over values but is uncertain about the correct model of the buyers' beliefs. The designer evaluates a given auction design by the lowest expected revenue that would be generated across all models of buyers' information that are consistent with the common prior and across all Bayesian equilibria. An optimal auction for such a seller is constructed, as is a worst-case model of buyers' information. The theory generates upper bounds on the seller's optimal payoff for general many-player and common-value models.

Keywords: Optimal auctions; common values; information structure; mo del uncertainty; ambiguity aversion; robustness; Bayes correlated equilibrium; revenue maximization; revenue equivalence; information rent (search for similar items in EconPapers)
JEL-codes: C72 D44 D82 D83 (search for similar items in EconPapers)
Date: 2016-12
New Economics Papers: this item is included in nep-gth, nep-mic and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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Working Paper: Informationally Robust Optimal Auction Design (2016)
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