Empirical estimates of monetary policy reaction functions feature a very high estimated degree of monetary policy inertia. This evidence is very hard to reconcile with the alternative evidence of low predictability of monetary policy rates. In this paper we examine the potential relevance of the...

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and...

Existing methods for data interpolation or backdating are either univariate or based on a very limited number of series, due to data and computing constraints that were binding until the recent past. Nowadays large datasets are readily available, and models with hundreds of parameters are fastly...

This paper evaluates models that exploit timely monthly releases to compute early estimates of current quarter GDP (now-casting) in the euro area. We compare traditional methods used at institutions with a new method proposed by Giannone, Reichlin and Small, 2005. The method consists in bridging...

This paper provides an overview of the panel VAR models used in macroeconomics and finance. It discusses what are their distinctive features, what they are used for, and how they can be derived from economic theory. It also describes how they are estimated and how shock identification is...

This Paper studies empirically the transmission mechanism of European monetary policy by means of time-varying, heterogenous coefficient models estimated in a numerical Bayesian fashion. Based on pre-EMU evidence from Germany, France, Italy, and Spain, we find that (i) the long-run cumulative...

This Paper examines the properties of G-7 cycles using a multicountry Bayesian panel VAR model with time variations, unit specific dynamics and cross country interdependences. We demonstrate the presence of a significant world cycle and show that country specific indicators play a much smaller...

This Paper proposes a method to conduct inference in panel VAR models with cross-unit interdependencies and time variations in the coefficients. The set-up used is Bayesian, and Markov chain Monte Carlo (MCMC) methods are used to estimate the posterior distribution of the features of interest....

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model that accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for...