Simple non-parametric estimators for unemployment duration analysis

被引：12

作者：

Wichert, Laura ^{[1
]}

Wilke, Ralf A. ^{[2
]}

机构：

[1] Univ Konstanz, Dept Econ, D-78457 Constance, Germany

[2] Univ Nottingham, Nottingham NG7 2RD, England

来源：

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS | 2008年 / 57卷

关键词：

censoring; non-parametric estimation; unemployment duration;

D O I：

10.1111/j.1467-9876.2007.00604.x

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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-type estimator which adapts the non-parametric conditional hazard rate estimator of Beran 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 non-parametric conditional quantile functions with German administrative unemployment duration data.

引用

页码：117 / 126

页数：10

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