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 considers Bayesian regression with normal and doubleexponential 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...

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 examines two competing approaches for calculating current account benchmarks, i.e. the external sustainability approach á la Lane and Milesi-Ferretti (LM) versus the structural current accounts literature (SCA) based on panel econometric techniques. The aim is to gauge the medium...

We investigate the similarities of macroeconomic fluctuations in the Mediterranean basin and their convergence. A model with three indicators, covering the West, the East and the MENA portions of the Mediterranean, characterizes well the historical experience since the early 1980. Convergence...

The global financial crisis has led to a revival of the empirical literature on current account imbalances. This paper contributes to that literature by investigating the importance of evaluating model and parameter uncertainty prior to reaching any firm conclusion. We explore three alternative...

We investigate heterogeneity and spillovers in macro-financial linkages across developed economies, with a particular emphasis in the most recent recession. A panel Bayesian VAR model including real and financial variables identifies a statistically significant common component, which turns out...

This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large...