Quantile regression estimation of panel duration models with censored data

Matthew Harding, Carlos Lamarche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This paper studies the estimation of quantile regression panel duration models. We allow for the possibility of endogenous covariates and correlated individual effects in the quantile regression models. We propose a quantile regression approach for panel duration models under conditionally independent censoring. The procedure involves minimizing ℓ1 convex objective functions and is motivated by a martingale property associated with survival data inmodelswith endogenous covariates.Wecarry out a series of Monte Carlo simulations to investigate the small sample performance of the proposed approach in comparison with other existing methods. An empirical application of the method to the analysis of the effect of unemployment insurance on unemployment duration illustrates the approach.

Original languageEnglish
Title of host publicationEssays in Honor of Jerry Hausman
EditorsBadi Baltagi, Carter Hill, Whitney Newey, Halbert White
Pages237-267
Number of pages31
DOIs
StatePublished - 2012

Publication series

NameAdvances in Econometrics
Volume29
ISSN (Print)0731-9053

Keywords

  • Duration models
  • Panel data
  • Quantile regression
  • Unemployment insurance

ASJC Scopus subject areas

  • Economics and Econometrics

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