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Nonparametric identification and estimation of a class of common value auction models
Author(s) -
Février Philippe
Publication year - 2008
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.1041
Subject(s) - common value auction , estimator , nonparametric statistics , econometrics , consistency (knowledge bases) , value (mathematics) , class (philosophy) , function (biology) , identification (biology) , conditional probability distribution , conditional expectation , mathematics , computer science , statistics , artificial intelligence , botany , evolutionary biology , biology
Abstract Structural econometric studies on auctions have mainly focused on the independent private value paradigm. In this paper, we are interested in the ‘opposite’ case known as the pure common value model. More precisely, we restrict our attention to a class of common value models defined by three functions: the density of the true value of the auctioned good, a unique function that appears in the definition of the conditional densities of the signals, and the function that defines the support of the conditional densities. We establish that these common value models are nonparametrically identified without any further restrictions. We then propose a one‐step nonparametric estimation method and prove the uniform consistency of our estimators. We apply our method on simulated data and show that the technique we propose is adequate to recover the distribution functions of interest. Copyright © 2008 John Wiley & Sons, Ltd.