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This paper estimates the impact of training incidence and duration on employment transitions accounting for the endogeneity of program participation and duration. The authors specify a very flexible bivariate random effects probit model for employment and training participation and they use Bayesian Markov Chain Monte Carlo (MCMC) techniques for estimation. They develop a simulation approach that uses the estimated coefficients and individual specific effects from the MCMC iterations to calculate the posterior distributions of different treatment effects of interest. Their estimation results imply positive effects of training on the employment probability of the treated, lying between 12 and 21 percentage points ten quarters after program start. The effects are higher for women than for men and higher in West Germany than in East Germany.
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