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PAIRWISE DIFFERENCE ESTIMATION WITH NONPARAMETRIC CONTROL VARIABLES *
Author(s) -
AradillasLopez Andres,
Honoré Bo E.,
Powell James L.
Publication year - 2007
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/j.1468-2354.2007.00457.x
Subject(s) - endogeneity , estimator , pairwise comparison , nonparametric statistics , econometrics , mathematics , logit , asymptotic analysis , inference , instrumental variable , asymptotic distribution , conditional expectation , statistics , computer science , artificial intelligence
This article extends the pairwise difference estimators for various semilinear limited dependent variable models proposed by Honoré and Powell ( Identification and Inference in Econometric Models . Essays in Honor of Thomas Rothenberg Cambridge: Cambridge University Press, 2005) to permit the regressor appearing in the nonparametric component to itself depend upon a conditional expectation that is nonparametrically estimated. This permits the estimation approach to be applied to nonlinear models with sample selectivity and/or endogeneity, in which a “control variable” for selectivity or endogeneity is nonparametrically estimated. We develop the relevant asymptotic theory for the proposed estimators and we illustrate the theory to derive the asymptotic distribution of the estimator for the partially linear logit model.