Identification and Estimation of Auction Models with Unobserved Heterogeneity

• 成果类型: Article
• 署名作者: Krasnokutskaya, Elena
• 署名单位: University of Pennsylvania
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.1093/restud/rdq004
• 发表日期: 2011
• 页码: 293-327
• 关键词: nonparametric deconvolution; 1st-price auctions; empirical-models; COMPETITION; VALUES

摘要

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.