Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … instability in a forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to … improve the forecasting performance. …

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

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 …

volatility specifications, in terms of point forecasting to some degree and density forecasting to a greater degree. …

-of-sample forecasting experiment. Our results show that exploiting the informational content in a common global business cycle factor … improves forecasting accuracy in terms of both point and density forecast evaluation across a large panel of countries. In line … earlier in the evaluation sample. However, this time is different also in other respects. On longer forecasting horizons the …

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 with the most promising …