This paper proposes a new and robust methodology to obtain conditional density forecasts, based on information not contained in an initial econometric model. The methodology allows to condition on expected marginal densities for a selection of variables in the model, rather than just on future...

Forward guidance operates via the expectations formation process of the agents in the economy. In standard quantitative macroeconomic models, the expectations are unobserved state variables and little scrutiny is devoted to analysing the dynamic behaviour of these expectations. We show that the...

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...

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...

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...