Semiparametric Bayesian Time-Space Analysis of Unemployment Duration

In this paper, we analyze unemployment duration in Germany with official data from the German Federal Employment Office for the years 1980-1995. Conventional hazard rate models for leaving unemployment cannot cope with simultaneous and flexible fitting of duration dependence, nonlinear covariate effects, 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 effects of several time scales, regional variation and further covariates. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques