Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/24617
Authors: 
Wilke, Ralf A.
Wichert, Laura
Year of Publication: 
2005
Series/Report no.: 
ZEW Discussion Papers 05-67 [rev.]
Abstract: 
We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas (1994) type estimator which adapts the nonparametric conditional hazard rate estimator of Beran (1981) to more typical data situations in applied analysis. We show with simulations that the estimator has nice finite sample properties and our implementation appears to be fast. As an application we estimate nonparametric conditional quantile functions with German administrative unemployment duration data.
Subjects: 
nonparametric estimation
censoring
unemployment duration
JEL: 
C41
C34
C14
Document Type: 
Working Paper

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