Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator
Jun Ma,
Vadim Marmer () and
Artyom Shneyerov
Journal of Econometrics, 2019, vol. 211, issue 2, 507-538
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 et al. (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.
Keywords: Asymptotic normality; Bootstrap; First-price auctions; Gaussian approximation; Independent private values; Two-step nonparametric estimators; Uniform confidence bands (search for similar items in EconPapers)
JEL-codes: C14 C57 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)
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Related works:
Working Paper: 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:eee:econom:v:211:y:2019:i:2:p:507-538
DOI: 10.1016/j.jeconom.2019.02.006
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