Identification and Estimation of Auction Models with Unobserved Heterogeneity
研究了投标人成本受共同冲击和私人信息影响的拍卖模型，提出非参数估计方法，并应用于密歇根州公路采购数据，发现私人信息解释34%的成本变化，对租金分配、效率和最优拍卖设计有重要影响。
In many procurement auctions, the bidders' unobserved costs depend both on a common shock and on idiosyncratic private information. Assuming a multiplicative structure, I derive sufficient conditions under which the model is identified and propose a non-parametric estimation procedure that results in uniformly consistent estimators of the cost components' distributions. The estimation procedure is applied to data from Michigan highway procurement auctions. Private information is estimated to account for 34% of the variation in bidders' costs. It is shown that accounting for unobserved auction heterogeneity has important implications for the evaluation of the distribution of rents, efficiency, and optimal auction design.