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Optimal Nonparametric Estimation of First‐price Auctions
Author(s) -
Guerre Emmanuel,
Perrigne Isabelle,
Vuong Quang
Publication year - 2000
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.1111/1468-0262.00123
Subject(s) - common value auction , nonparametric statistics , estimation , econometrics , economics , computer science , mathematical economics , microeconomics , management
This paper proposes a general approach and a computationally convenient estimation procedure for the structural analysis of auction data. Considering first‐price sealed‐bid auction models within the independent private value paradigm, we show that the underlying distribution of bidders' private values is identified from observed bids and the number of actual bidders without any parametric assumptions. Using the theory of minimax, we establish the best rate of uniform convergence at which the latent density of private values can be estimated nonparametrically from available data. We then propose a two‐step kernel‐based estimator that converges at the optimal rate.