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

Jun Ma, Vadim Marmer () and Artyom Shneyerov

Papers from arXiv.org

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.

Date: 2019-03
New Economics Papers: this item is included in nep-des and nep-ecm
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Citations: View citations in EconPapers (6)

Published in Journal of Econometrics 211 (2019) 507-538

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Related works:
Journal Article: Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator (2019)
Working Paper: Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's estimator (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1903.06401

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