In Bayesian inference, predictive distributions are typically in the form of samples generated via Markov chain Monte Carlo or related algorithms. In this paper, we conduct a systematic analysis of how to make and evaluate probabilistic forecasts from such simulation output. Based on proper...

Model diagnostics and forecast evaluation are closely related tasks, with the former concerning in-sample goodness (or lack) of fit and the latter addressing predictive performance out-of-sample. We review the ubiquitous setting in which forecasts are cast in the form of quantiles or...

Die vorliegende Dissertation befasst sich mit probabilistischen Prognosen, die seit einigen Jahren ein aktives ökonometrisches Forschungsgebiet darstellen. Da solche Prognosen eine vollständige Verteilung für die interessierende Zufallsvariable angeben, beinhalten sie Information über...