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Summary 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.
This paper benefitted from the helpful comments by an anonymous referee. Due to space constraints, we had to omit the details
of the empirical application. These can be found in the long version of this paper, Fitzenberger and Wilke (2005). We gratefully
acknowledge financial support by the German Research Foundation (DFG) through the research project ‘Microeconometric modelling
of unemployment durations under consideration of the macroeconomic situation’. Thanks are due to Xuan Zhang for excellent
research assistance. All errors are our sole responsibility. 相似文献
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