Simple Non-parametric Estimators for Unemployment Duration Analysis

Laura Wichert, Ralf Wilke

Research output: Contribution to journalJournal articleResearchpeer-review

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-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.
Original languageEnglish
JournalJournal of the Royal Statistical Society, Series C (Applied Statistics)
Volume27
Issue number1
Pages (from-to)117–126
ISSN0035-9254
DOIs
Publication statusPublished - 2008
Externally publishedYes

Cite this