Work

Estimation of semiparametric models when the criterion function is not smooth

Year: 2017

Type: report

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.

DOI: 10.1920/wp.cem.2002.0202

Authors: Xiaohong Chen, Ingred van Keilegom, Oliver Linton

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: Princeton University, Economic and Social Research Council

OpenAlex ID: W2243572907

Cites: 41

Cited by: 330

Related to: 10