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Estimation of semiparametric models when the criterion function is not smooth

Xiaohong Chen (), Oliver Linton () and Ingrid Van Keilegom ()

No CWP02/02, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: We provide easy to verify suffcient 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.

New Economics Papers: this item is included in nep-ecm
Date: 2002-11-07
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Related works:
Journal Article: Estimation of Semiparametric Models when the Criterion Function Is Not Smooth (2003) Downloads
Working Paper: Estimation of Semiparametric Models when the Criterion Function is not Smooth (2003) Downloads
Working Paper: Estimation of semiparametric models when the criterion function is not smooth (2003) Downloads
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