Factor Forests (DFF) for macroeconomic forecasting, which synthesize the recent machine learning, dynamic factor model and … proposed in Zeileis, Hothorn and Hornik (2008). DFTs and DFFs are non-linear and state-dependent forecasting models, which … powerful tree-based machine learning ensembles conditional on the state of the business cycle. The out-of-sample forecasting …

an out-of-sample forecasting exercise, the paper shows that the proposed approach performs well as compared to other well …

walk model suggests that the forecasting performance of the monetary model is superior. …

even more pronounced at longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared … spatial dependence structure into regional forecasting models, especially, when long-term forecasts are made. …

We evaluate the forecasting performance of six different models for short-term forecasting of Macedonian GDP: 1) ARIMA …

-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator …