liquidity forecasting. …

useful for macro-forecasting and monetary policy analysis. …

models for forecasting, although this proved to be problem- atic due to estimation and identification issues. Hybrid DSGE … the EU debt crisis. The results of this study can be useful in conducting monetary policy analysis and macro-forecasting …

increasingly featured, along with linear counterparts, in the forecasting literature. In this study, we focus on forecasting South … consistently and signicantly beats the LoLiMoT's performance in forecasting South African in ation. …

, as well as 20 bivariate regression models, capture the influence of fundamentals in forecasting residential investment …-wide factors, in addition to specific housing market variables, prove important when forecasting in the real estate market. …

interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting … Vector Regression (SVR) methodology that originates from machine learning. We test the forecasting ability of the proposed …-of-sample forecasting. Finally, we argue that this new methodology can be used as an early warning system for forecasting sudden house …