An empirical likelihood approach to quantile regression with auxiliary information

We consider how to incorporate auxiliary information to improve quantile regression via empirical likelihood. We propose a novel framework and show that our approach yields more efficient estimates compared to those from the conventional quantile regression. The efficiency gain is quantified theoretically and demonstrated empirically via simulation studies.

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Year of publication:	2012
Authors:	Tang, Cheng Yong ; Leng, Chenlei
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 82.2012, 1, p. 29-36
Publisher:	Elsevier
Subject:	Auxiliary information \| Empirical likelihood \| Estimating equations \| Quantile regression

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010582242