Arbeitspapier
Estimating first-price auctions with an unknown number of bidders: A misclassication approach
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.
- Language
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Englisch
- Bibliographic citation
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Series: Working Paper ; No. 541
- Classification
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Wirtschaft
- Event
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Geistige Schöpfung
- (who)
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Hu, Yingyao
Shum, Matthew
- Event
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Veröffentlichung
- (who)
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The Johns Hopkins University, Department of Economics
- (where)
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Baltimore, MD
- (when)
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2007
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Hu, Yingyao
- Shum, Matthew
- The Johns Hopkins University, Department of Economics
Time of origin
- 2007
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