Identification and Estimation of First-Price Auctions Under Ambiguity

Abstract

This paper studies identification and estimation of first-price auctions if the bidders face ambiguity about the distribution of valuations. Ambiguity is modeled using Gilboa and Schmeidler's (1989) Maxmin Expected Utility preferences. We exploit variation in the number of bidders to identify the essential primitives of the model. The identification result yields a closed form for the inverse bid function, which suggests a two-step estimation procedure. We study asymptotic and finite sample properties of the estimators. We find evidence of ambiguity in USFS timber auctions which leads to aggressive bidding for bidders with high valuations and has important implications for auction design.

Keywords: First-Price Auctions, Ambiguity Aversion, Maxmin Expected Utility, Nonparametric Identification, Timber Auctions

JEL Classification: C14, D44, L70