Estimating Risk Aversion from Ascending and Sealed-Bid Auctions: The Case of Timber Auction Data

نویسندگان

  • Jingfeng Lu
  • J. Lu
چکیده

Estimating bidders’ risk aversion in auctions is challeging because of identification issues. This paper takes advantage of bidding data from two auction designs to nonparametrically identify bidders’ utility function within a private value framework. In particular, ascending auction data allow us to recover the latent distribution of private values, while first-price sealed-bid auction data allow us 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 captured by a CRRA specification.

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تاریخ انتشار 2006