variables in the model, rather than just on future paths as it is usually done in the conditional forecasting literature. The … forecasting densities of a BVAR and a DSGE model on information about the marginal densities of future oil prices. The results …-inflation over the considered forecasting horizon. Finally, a real-time forecasting exercise yields that introducing market …

) models affects their forecasting performance. We apply this analysis to medium-scale DSGE models with and without financial … with financial frictions outperform in forecasting inflation but not the GDP growth rate. …

out-of-sample forecasting exercise and is able to reproduce most of the cross-series co-variances observed in the data. It …

This paper analyzes the forecasting performance of an open economy DSGE model, estimated with Bayesian methods, for the … forecasting models such as vector autoregressions (VAR) and vector error correction models (VECM), estimated both by maximum …-dimensional summaries, e.g. the log determinant statistic, as measures of overall forecasting performance. …

represent nicely the two opposing forecasting philosophies. The DSGE model on the one hand has a strong theoretical economic …-horizon forecasting and structural models should be used in long-horizon forecasting. Our paper compareds both state-of-the art data …

pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE …