Using Quantile Regression for Duration Analysis

Bernd Fitzenberger, Ralf Wilke

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Abstrakt

Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the functional relationship and of the error distribution. Censored quantile regression address the issue of right censoring of the response variable which is common in duration analysis. We compare quantile regression to standard duration models. Quantile regression do not impose a proportional effect of the covariates on the hazard over the duration time. However, the method can not take account of time-varying covariates and it has not been extended so far to allow for unobserved heterogeneity and competing risks. We also discuss how hazard rates can be estimated using quantile regression methods. A small application with German register data on unemployment duration for younger workers demonstrates the applicability and the usefulness of quantile regression for empirical duration analysis.
OriginalsprogEngelsk
TidsskriftAllgemeines Statistisches Archiv
Vol/bind90
Udgave nummer1
Sider (fra-til)103-118
ISSN0002-6018
DOI
StatusUdgivet - 2006
Udgivet eksterntJa

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