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Estimating first-price auctions with an unknown number of bidders: A misclassification approach

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  • An, Yonghong
  • Hu, Yingyao
  • Shum, Matthew

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.

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  • An, Yonghong & Hu, Yingyao & Shum, Matthew, 2010. "Estimating first-price auctions with an unknown number of bidders: A misclassification approach," Journal of Econometrics, Elsevier, vol. 157(2), pages 328-341, August.
  • Handle: RePEc:eee:econom:v:157:y:2010:i:2:p:328-341
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