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Simple non‐parametric estimators for unemployment duration analysis
Author(s) -
Wichert Laura,
Wilke Ralf A.
Publication year - 2008
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2007.00604.x
Subject(s) - estimator , statistics , econometrics , mathematics , univariate , quantile , parametric statistics , semiparametric model , multivariate statistics
Summary. 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.