-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting performance. …

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus … matrix of h-steps 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 …

that, in this case, adding stochastic volatility can further improve the forecasting performance of a single-factor BVAR …

) 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. …

Macroeconomic forecasting in recessions is not easy due to the inherent asymmetry of business cycle phases and the …-frequency setting. A real-time forecasting experiment highlights the advantage of including the threshold feature for the asymmetry as …

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. …

from the weather forecasting literature known as `ensemble modelling'. In this approach, uncertainty about model … provide two examples of this modelling strategy: (i) forecasting inflation with a disaggregate ensemble; and (ii) forecasting …