Structural VARs have been extensively used in empirical macroeconomics during the last two decades, particularly in analyses of monetary policy. Existing Bayesian procedures for structural VARs are at best confined to a severly limited handling of cointegration restrictions. This paper extends...

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 introduce a Bayesian Mixed-Frequency VAR model for the aggregate euro area labour market that features a structural identification via sign restrictions. The purpose of this paper is twofold: we aim at (i) providing reliable and timely forecasts of key labour market variables and (ii)...

We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...

This paper assesses the impact of weather shocks on inflation components in the four largest euro area economies. We combine high-frequency weather data with monthly data on inflation and output growth within a set of Bayesian Vector Autoregressions which explicitly considers the seasonal...

We propose a framework to identify a rich set of structural drivers of inflation in order to understand the role of the multiple and concomitant sources of the post-pandemic inflation surge. We specify a medium-sized structural Bayesian VAR on a comprehensive set of variables for the euro area...