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Title:Estimating first-price auctions with an unknown number of bidders: A misclassication approach PDF Logo
Authors:Hu, Yingyao
Shum, Matthew
Issue Date:2007
Series/Report no.:Working papers // the Johns Hopkins University, Department of Economics 541
Abstract:In this paper, we consider nonparametric identification and estimation of first-price auction models when N*, the number of potential bidders, is unknown to the researcher, but observed by bidders. Exploiting results from the recent econometric literature on models with misclassification error, we develop a nonparametric procedure for recovering the distribution of bids conditional on the unknown N*. Monte Carlo results illustrate that the procedure works well in practice. We present illustrative evidence from a dataset of procurement auctions, which shows that accounting for the unobservability of N* can lead to economically meaningful differences in the estimates of bidders' profit margins.
Document Type:Working Paper
Appears in Collections:Working Papers, Department of Economics, The Johns Hopkins University

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