Empirical likelihood inference in partially linear single-index models with endogenous covariates. Issue 7 (3rd April 2017)

• Record Type: Journal Article
• Authors: Yang, Yiping; Chen, Lifang; Zhao, Peixin
• Is Part Of: Communications in statistics. Volume 46:Issue 7(2017)
• Page Start: 3297
• Page End: 3307
• Publication Date: 2017-04-03
• Subjects: Empirical likelihood -- Endogenous variables -- Instrumental variables -- Partially linear single-index model; 62G05 -- 62G20; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2015.1060341
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: In this article, we consider how to construct the confidence regions of the unknown parameters for partially linear single-index models with endogenous covariates. To eliminate the influence of the endogenous covariates, an empirical likelihood method is proposed based on instrumental variables. Under some regularly conditions, the asymptotic distribution of the proposed empirical log-likelihood ratio is proved to be a Chi-squared distribution. We investigate the finite-sample performance of the proposed method via simulation studies.