Skip to main content
Article thumbnail
Location of Repository

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 nonparametric estimators that can themselves depend on the parameters to be estimated. Our results extend existing theories like those of Pakes and Pollard (1989), Andrews (1994a) and Newey (1994). We also show that bootstrap provides asymptotically correct confidence regions for the finite dimensional parameters. We apply our results to two examples: a 'hit rate' and a partially linear median regression with some endogenous regressors

Topics: HB Economic Theory
Publisher: Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science
Year: 2003
OAI identifier: oai:eprints.lse.ac.uk:2167
Provided by: LSE Research Online

Suggested articles


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.