Several Monte Carlo methods have been proposed for computing marginal likelihoods in Bayesian analyses. Some of these involve sampling from a sequence of intermediate distributions between the prior and posterior. A difficulty arises if the support in the posterior distribution is a proper...

We adopt a hidden state approach for the analysis of longitudinal data subject to dropout. Motivated by two applied studies, we assume that subjects can move between three states: stable, crisis, dropout. Dropout is observed but the other two states are not. During a possibly transient crisis...

The structural theoretical framework for the analysis of duration of unemployment has been the optimal job search model. Recent advances in computational techniques in Bayesian inference now facilitate the analysis of incomplete data sets and the recovery of structural model parameters. The...