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Nonparametric Identification of First-Price Auctions with Non-Separable Unobserved Heterogeneity

Author

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  • David McAdams
  • Yingyao Hu
  • Matthew Shum

Abstract

We propose a novel methodology for nonparametric identification of first-price auction models with independent private values, which allows for one-dimensional auctionspecific unobserved heterogeneity, based on recent results from the econometric literature on nonclassical measurement error in Hu and Schennach (2008). Our approach can accommodate a wide variety of applications in which some location of the conditional distribution of bids (e.g. min or max of the support, mean, etc.) is increasing in the unobserved heterogeneity. This includes settings in which the econometrician fails to observe the reserve price, the cost of bidding, the number of bidders, or some factor (“quality”) with a non-linear effect on bidder values.

Suggested Citation

  • David McAdams & Yingyao Hu & Matthew Shum, 2010. "Nonparametric Identification of First-Price Auctions with Non-Separable Unobserved Heterogeneity," Working Papers 10-63, Duke University, Department of Economics.
  • Handle: RePEc:duk:dukeec:10-63
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    Cited by:

    1. Hickman Brent R. & Hubbard Timothy P. & Sağlam Yiğit, 2012. "Structural Econometric Methods in Auctions: A Guide to the Literature," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 67-106, August.
    2. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Merlo, Antonio & Tang, Xun, 2015. "Bargaining with Optimism: A Structural Analysis of Medical Malpractice Litigation," Working Papers 15-005, Rice University, Department of Economics.

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