Simple nonparametric estimators for unemployment duration analysis
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." (Author's abstract, IAB-Doku) ((en)) Additional Information Appendix for the FDZ-Methodenreport No. 09/2007: Programme.zip
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Bibliographic InfoPaper provided by Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] in its series FDZ Methodenreport with number 200709_en.
Length: 19 pages
Date of creation: 16 Oct 2007
Date of revision:
Arbeitslosigkeitsdauer; Schätzung - Methode; IAB-Beschäftigtenstichprobe;
Other versions of this item:
- Laura Wichert & Ralf A. Wilke, 2008. "Simple non-parametric estimators for unemployment duration analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(1), pages 117-126.
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04-24, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
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- Ralf Wilke, . "Unemployment Duration in the United Kingdom: An Incomplete Data Approach," Discussion Papers 09/02, University of Nottingham, School of Economics.
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