This paper shows how to compute the h-step-ahead predictive likelihood for any subset of the observed variables in parametric discrete time series models estimated with Bayesian methods. The subset of variables may vary across forecast horizons and the problem thereby covers marginal and joint...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-step ahead forecasts. In the empirical...

We focus on a quantitative assessment of rigid labor markets in an environment of stable monetary policy. We ask how wages and labor market shocks feed into the inflation process and derive monetary policy implications. Towards that aim, we structurally model matching frictions and rigid wages...