This Paper proposes a new forecasting method that exploits information from a large panel of time series. The method is …

This paper addresses the issue of forecasting the term structure. We provide a unified state-space modelling framework … forecasting performance of two crucial modelling choices, i.e. the imposition of no-arbitrage restrictions and the size of the … information set used to extract factors. Using US yield curve data, we find that: a. macro factors are very useful in forecasting …

, produces a degree of forecasting accuracy of the federal funds rate similar to that of the markets, and, for output and …

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 …

index and to evaluate the role of financial variables in forecasting. We considered two models which allow forecasting based … univariate methods for forecasting inflation at one, three, six, and twelve months and industrial production at one and three … months. We find that financial variables do help forecasting inflation, but do not help forecasting industrial production. …

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 for US time series with the …

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 …