The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we … propose three alternative reduced rank forecasting models and compare their predictive performance with the most promising … classical reduced rank regression, a two-step procedure that applies, in turn, shrinkage and reduced rank restrictions, and the …

sample (bayesian shrinkage), the forecasting performance of a VAR can be improved by adding macroeconomic variables and … and Reichlin (2010) shows that, when the degree of shrinkage is set in relation to the cross-sectional dimension of the …

This paper evaluates the performance of 11 vector autoregressive models in forecasting 15 macroeconomic variables for …

forecasting. The empirical results serve as a preliminary guide to understanding the behaviour of BMA under double asymptotics, i …

is known to be hard to forecast, but by exploiting timely information one obtains gains at nowcasting and forecasting one …

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … instability in a forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to … improve the forecasting performance. …

forecasting accuracy and then perform a structural exercise focused on the effect of a monetary policy shock on the macroeconomy …. Results show that BVARs estimated on the basis of hundred variables perform well in forecasting and are suitable for …

In this paper we discuss how the forecasting performance of Bayesian VARs is affected by a number of specification … lag length and of both; compare alternative approaches to h-step ahead forecasting (direct, iterated and pseudo …-iterated); discuss the treatment of the error variance and of cross-variable shrinkage; and address a set of additional issues, including …