Using Quantile Regression for Duration Analysis

Bernd Fitzenberger () and Ralf Wilke
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Bernd Fitzenberger: J.W. Goethe University Frankfurt

Chapter 8 in Modern Econometric Analysis, 2006, pp 103-118 from Springer

Abstract: Abstract 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 addresses 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 does not impose a proportional effect of the covariates on the hazard over the duration time. However, the method cannot 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.

Keywords: Hazard Rate; Unobserved Heterogeneity; Duration Data; Unemployment Duration; Duration Analysis (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-32693-9_8

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DOI: 10.1007/3-540-32693-6_8

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