Kernel-based estimation of semiparametric regression in triangular systems

We propose a kernel-based estimator for a partially linear model in triangular systems where endogenous variables appear both in the nonparametric and linear component functions. Our estimator is easy to implement, has an explicit algebraic structure, and exhibits good finite sample performance in a Monte Carlo study.

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Year of publication:	2012
Authors:	Martins-Filho, Carlos ; Yao, Feng
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 115.2012, 1, p. 24-27
Publisher:	Elsevier
Subject:	Additive semiparametric regression \| Instrumental variables \| Local linear regressions

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Type of publication:	Article
Classification:	C12 - Hypothesis Testing ; C14 - Semiparametric and Nonparametric Methods
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010572207