Abstract
AbstractEstimating bidders' risk aversion in auctions is a challenging problem because of identification issues. This paper takes advantage of bidding data from two auction designs to identify nonparametrically the bidders' utility function within a private value framework. In particular, ascending auction data allow one to recover the latent distribution of private values, while first‐price sealed‐bid auction data allow one to recover the bidders' utility function. This leads to a nonparametric estimator. An application to the US Forest Service timber auctions is proposed. Estimated utility functions display concavity, which can be partly captured by constant relative risk aversion. Copyright © 2008 John Wiley & Sons, Ltd.
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