Quantile Regression Methods for Longitudinal Data

Authored by: Antonio F. Galvao , Kengo Kato

Handbook of Quantile Regression

Print publication date:  October  2017
Online publication date:  October  2017

Print ISBN: 9781498725286
eBook ISBN: 9781315120256
Adobe ISBN:

10.1201/9781315120256-19

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Abstract

Since the seminal work of Koenker and Gilbert (1978), quantile regression (QR) has been a pivotal statistical technique; it offers an easy-to-implement method to estimate conditional quantiles, and by estimating several different conditional quantiles, one is able to make inference on the effects of the regressors on the entire conditional distribution. The properties of the QR method are well established for cross-sectional models; see the landmark monograph by Koenker (2005) for references and discussion.

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