Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either be information concerning deep parameters’ values (‘microprior’) or some macroeconomic indicator, e.g. moments of observable variables (‘macroprior’)....

In a highly interlinked global economy a key question for policy makers is how foreign shocks and policies transmit to the domestic economy. We develop a semi-structural multi-country model with rich real and financial channels of international shock propagation for the euro area, the US, Japan,...

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 show how to use a simple perturbation method to solve non-linear rational expectation models. Drawing from the applied mathematics literature we propose a method consisting of series expansions of the non-linear system around a known solution. The variables are represented in terms of their...

In this paper, we outline a version of the New Area-Wide Model (NAWM) of the euro area designed for use in the (Broad) Macroeconomic Projection Exercises regularly undertaken by ECB/Eurosystem staff. We present estimation results for the NAWM that are obtained by employing Bayesian inference...

This paper provides a detailed description of an extended version of the ECB's New Area-Wide Model (NAWM) of the euro area (cf. Christoffel, Coenen, and Warne 2008). The extended model - called NAWM II - incorporates a rich financial sector with the threefold aim of (i) accounting for a genuine...

This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting...

This paper considers Bayesian regression with normal and double-exponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

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...

Periods of economic and financial stress traditionally give rise to profound changes in economic theory and in the way policy decisions are taken. Motivated by the recent interest in renewing macroeconomics after the global financial crisis, we collected the views of senior central bank staff in...