Estimation in English auctions with unobserved heterogeneity

• 成果类型: Article
• 署名作者: Hernandez, Cristian; Quint, Daniel; Turansick, Christopher
• 署名单位: University of Wisconsin System; University of Wisconsin Madison; Georgetown University
• 刊物名称: RAND JOURNAL OF ECONOMICS
• ISSN/ISSBN: 0741-6261
• DOI: 10.1111/1756-2171.12343
• 发表日期: 2020
• 页码: 868-904
• 关键词: nonparametric-estimation; private information; ascending auctions; 1st-price auctions; identification; MODEL; inference

摘要

We propose a framework for identification and estimation of a private values model with unobserved heterogeneity from bid data in English auctions, using variation in the number of bidders across auctions, and extend the framework to settings where the number of bidders is not cleanly observed in each auction. We illustrate our method on data from eBay Motors auctions. We find that unobserved heterogeneity is important, accounting for two thirds of price variation after controlling for observables, and that welfare measures would be dramatically misestimated if unobserved heterogeneity were ignored.