Estimating First-Price Auctions with an Unknown Number of Bidders: A Misclassification Approach
Yingyao Hu and
Matthew Shum ()
Economics Working Paper Archive from The Johns Hopkins University,Department of Economics
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.
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Journal Article: Estimating first-price auctions with an unknown number of bidders: A misclassification approach (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:jhu:papers:541
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