Publikationsansicht

Summary (2007)

Abstract
In this paper, we analyze unemployment duration in Germany with o#cial data from the German Federal Employment O#ce for the years 1980-1995. Conventional hazard rate models for leaving unemployment cannot cope with simultaneous and flexible fitting of duration dependence, nonlinear covariate e#ects, trend and seasonal calendar time components and a large number of regional effects. We apply a semiparametric hierarchical Bayesian modelling approach that is suitable for time-space analysis of unemployment duration by simultaneously including and estimating e#ects of several time scales, regional variation and further covariates. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques. JEL classification: C11, C41 and J64

Details der Publikation
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.22.2052
Quelle http://www.stat.uni-muenchen.de/~lang/skript/papiabfinal2.ps.gz
Mitarbeiter CiteSeerX
Archiv CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Keywords MCMC, Semiparametric Bayesian Inference, Smoothness priors 1
Typ text
Sprache Englisch
Verknüpfungen 10.1.1.46.8665, 10.1.1.35.9678, 10.1.1.128.1406, 10.1.1.42.6990, 10.1.1.119.2246, 10.1.1.23.5270, 10.1.1.45.5176, 10.1.1.51.8067, 10.1.1.45.4308