Order statistics approaches to unobserved heterogeneity in auctions (Q6597255)

In this article, the authors provide identification results for auction models using order statistics of bids. The following three contributions in this paper are important: First, the paper is the first to study identification of auction models with continuous and nonseparable UH using incomplete bid data. The proposed specification allows for flexibility in how UH affects both bidder value and the equilibrium bidding strategy -- namely the mapping from a bidder's private value to his/her bid. Second, sieve maximum likelihood estimators (MLE) of the model primitives and provide conditions that guarantee their consistency are proposed. The estimation of auction models allows for counterfactual policy analysis, such as computing the optimal reserve price. Lastly, the authors apply the identification and estimation method to a novel dataset from judicial auctions conducted by a municipal court in China. The estimation results suggest substantial gains from accounting for UH when designing reserve prices. The Appendix contains detailed proofs of the identification results and the asymptotic properties.