Simple Non-parametric Estimators for Unemployment Duration Analysis

Laura Wichert, Ralf Wilke

Publikation: Bidrag til tidsskriftTidsskriftartikel

Abstrakt

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.
OriginalsprogEngelsk
TidsskriftJournal of the Royal Statistical Society, Series C (Applied Statistics)
Vol/bind27
Udgave nummer1
Sider (fra-til)117–126
ISSN0035-9254
DOI
StatusUdgivet - 2008
Udgivet eksterntJa

Emneord

  • Censoring
  • Non-parametric estimation
  • Unemployment duration

Citationsformater