product, which in turn are used as an input in the forecasting process. Such forecasts reflect and incorporate the flow of … in a synchronous way. The forecasting power of the dynamic factor model is compared with those of several other models …

across different horizons and real-time datasets. To further improve performances when forecasting with machine learning, we …

best overall performance both in terms of forecasting accuracy and in matching (future) survey forecasts. …

This paper derives new theoretical results for forecasting with Global VAR (GVAR) models. It is shown that the presence … Purchasing Managers Indices (PMIs) for forecasting global (48 countries) growth, and compare forecasts from AugGVAR models with a … number of data-rich forecasting methods, including Lasso, Ridge, partial least squares and factor-based methods. It is found …

This paper analyzes the forecasting performance of financial market data in comparison to other indicator groups to … evaluate the forecasting performance using a significance test. In addition, we investigate the stability of forecasting models …-term forecasting, especially for the US and longer forecast horizons. Nevertheless, the results indicate that the Great Recession was …

- and hard-threshold algorithms improves the forecasting performance, especially during periods of economic crisis. While a … effect on forecasting performance, all the more, if the set of indicators becomes unbalanced. …