Backfitting and smooth backfitting in varying coefficient quantile regression. Issue 2 (22nd April 2014)

• Record Type: Journal Article
• Authors: Lee, Young K.; Mammen, Enno; Park, Byeong U.
• Is Part Of: Econometrics journal. Volume 17:Issue 2(2014)
• Page Start: S20
• Page End: S38
• Publication Date: 2014-04-22
• Subjects: Econometrics -- Periodicals; 330.015195
• DOI: 10.1111/ectj.12017
• Languages: English
• ISSNs: 1368-4221

Abstract

<abstract abstract-type="main"> <title>Summary</title> <p>In this paper, we study ordinary backfitting and smooth backfitting as methods of fitting varying coefficient quantile models. We do this in a unified framework that accommodates various types of varying coefficient models. Our framework also covers the additive quantile model as a special case. Under a set of weak conditions, we derive the asymptotic distributions of the backfitting estimators. We also briefly report on the results of a simulation study.</p> </abstract>