. While the forecasting error of the combined forecast tends to be systematically smaller than that of the individual model …

explores various specifications of decompositions and various forecasting experiments. The result from these horse-races is … for richer forecasting specifications, the paper shows, using Bayesian model averaging techniques (BMA), that the …

. Nevertheless, their forecasting properties are still barely explored. We fill this gap by comparing the quality of real … priors from a DSGE model. We show that the analyzed DSGE model is relatively successful in forecasting the US economy in the … accurate short-term forecasts for interest rates. Conditional on experts' now casts, however, the forecasting power of the DSGE …

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus … matrix of h-step ahead forecasts. In the empirical analysis, we examine the forecasting performance of the New Area … scope for improving the NAWM’s forecasting performance. For example, the model is not able to explain the moderation in wage …

comparison methodology, we find that boosting is a serious competitor for forecasting US industrial production growth in the …

quantitative macroeconomics. However, DSGE models were not considered as a forecasting tool until very recently. The objective of … this paper is twofold. First, we compare the forecasting ability of a canonical DSGE model for the Spanish economy with … VAR operates with artificial series obtained from a DSGE model. The results indicate that the out-of-sample forecasting …