Ascending auctions with bidder asymmetries

• 成果类型: Article
• 署名作者: Coey, Dominic; Larsen, Bradley; Sweeney, Kane; Waisman, Caio
• 署名单位: Facebook Inc; Stanford University; National Bureau of Economic Research; Uber Technologies, Inc.
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE474
• 发表日期: 2017
• 页码: 181-200
• 关键词: Ascending auction; partial identification; correlated values; asymmetries

摘要

We present a partial identification approach for ascending auctions with bidder asymmetries, where bidders' asymmetric types may be unobservable to the econometrician. Our approach yields sharp bounds and builds on and generalizes other recent bounds approaches for correlated private values ascending auctions. When bidder identities are observable, our approach yields tighter bounds than previous approaches that ignore asymmetry, demonstrating that bidder asymmetries can function as an aid rather than a hindrance to identification. We present a nonparametric estimation and inference approach relying on our identification argument and apply it to data from U.S. timber auctions, finding that bounds on optimal reserve prices and other objects of interest are noticeably tighter when exploiting bidder asymmetries.