This paper analyzes the dynamic effects of different macroeconomic shocks on unemployment in Germany. In a first step, a cointegration analysis of productivity, prices, real wages, employment, and the unemployment rate reveals two long run relationships, interpreted as a labor demand and a wage...

This paper analyzes the dynamic effects of different macroeconomic shocks on unemployment in Germany. In a first step, a cointegration analysis of productivity, prices, real wages, employment, and the unemployment rate reveals two long run relationships, interpreted as a labor demand and a wage...

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...

The predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models...

We estimate the effects of interest rate forward guidance (FG) using a parsimonious VAR, augmented with survey forecast data. The identification strategy of FG shocks via sign and zero restrictions is successfully tested by the recovery of true IRFs from simulated data. The identified shocks...