Quantile-Based Nonparametric Inference for First-Price Auctions

Vadim Marmer () and Artyom Shneyerov ()

Microeconomics.ca working papers from Vancouver School of Economics

Abstract: We propose a quantile-based nonparametric approach to inference on the probability density function (PDF) of the private values in first-price sealed-bid auctions with independent private values. Our method of inference is based on a fully nonparametric kernel-based estimator of the quantiles and PDF of observable bids. Our estimator attains the optimal rate of Guerre, Perrigne, and Vuong (2000), and is also asymptotically normal with the appropriate choice of the bandwidth.

Keywords: First-price auctions; independent private values; nonparametric estimation; kernel estimation; quantiles; optimal reserve price (search for similar items in EconPapers)
JEL-codes: C14 D44 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2008-01-17, Revised 2013-05-16
New Economics Papers: this item is included in nep-ecm and nep-ore
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Related works:
Journal Article: Quantile-based nonparametric inference for first-price auctions (2012)
Working Paper: Quantile-Based Nonparametric Inference for First-Price Auctions (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:ubc:pmicro:marmer-08-01-17-12-16-12

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