Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/24617 
Year of Publication: 
2005
Series/Report no.: 
ZEW Discussion Papers No. 05-67 [rev.]
Publisher: 
Zentrum für Europäische Wirtschaftsforschung (ZEW), Mannheim
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
older Version: 
Document Type: 
Working Paper

Files in This Item:
File
Size
227.01 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.