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Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's Estimator

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  • Jun Ma
  • Vadim Marmer
  • Artyom Shneyerov

Abstract

We consider inference on the probability density of valuations in the first-price sealed-bid auctions model within the independent private value paradigm. We show the asymptotic normality of the two-step nonparametric estimator of Guerre, Perrigne, and Vuong (2000) (GPV), and propose an easily implementable and consistent estimator of the asymptotic variance. We prove the validity of the pointwise percentile bootstrap confidence intervals based on the GPV estimator. Lastly, we use the intermediate Gaussian approximation approach to construct bootstrap-based asymptotically valid uniform confidence bands for the density of the valuations.

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  • Jun Ma & Vadim Marmer & Artyom Shneyerov, 2019. "Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's Estimator," Papers 1903.06401, arXiv.org.
  • Handle: RePEc:arx:papers:1903.06401
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    References listed on IDEAS

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    Cited by:

    1. Joris Pinkse & Karl Schurter, 2019. "Estimation of Auction Models with Shape Restrictions," Papers 1912.07466, arXiv.org.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions

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