This paper studies the role of non-pervasive shocks when forecasting with factor models. To this end, we first … model for the idiosyncratic component. Then, we test the forecasting performance of this model both in simulations, and on a …

advantage of common stochastic trends improves forecasting performance over a stationary single-factor model. The common …

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a … data for a wide range of specifications. In order to explain this poor performance, we use a forecasting error decomposition …

forecasting proprieties are still unexplored. In this article we address this problem by examining the quality of forecasts from a … rate and the GDP price index inflation. We evaluate the ex post forecast errors on the basis of the data from the period of … horizons the DSGE model seems to outperform the SPF in forecasting the GDP growth rate. However, this characteristic turned out …

This paper addresses the issue of improving the forecasting performance of vector autoregressions (VARs) when the set …

This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs … Carlo experiment, and in forecasting 4 macroeconomic series of the UK using time-varying parameters vector autoregressions … (TVP-VARs). Restricted models consistently improve upon their unrestricted counterparts in forecasting, showing the merits …

This paper addresses the question of the selection of multivariate GARCH models in terms of variance matrix forecasting …