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Estimation of Semiparametric Models when the Criterion Function is not Smooth

By Xiaohong Chen, Oliver Linton and Ingrid Van Keilegom

Abstract

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some preliminary nonparametric estimators. Our results extend existing theories like those of Pakes and Pollard (1989), Andrews (1994a), and Newey (1994). We apply our results to two examples: a ‘hit rate’ and a partially linear median regression with some endogenous regressors

Year: 2002
OAI identifier: oai:CiteSeerX.psu:10.1.1.196.72
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