economies over the 2001-2018 period, while accounting for model uncertainty and reverse causality. On the one hand, we find …

modeling the sources of heterogeneity when suitable panel data exists. The counterfactual considerations that underlie policy … forecasting, decision making, model evaluation and learning can be considered as parts of the same interactive and iterative …

This paper proposes a new method of forecasting euro area quarterly real GDP that uses area-wide indicators, which are … modeling, we construct the area-wide indicators by utilizing weights that minimize the variance of the out-of-sample forecast … information approach outperforms alternative forecasting methods in terms of forecast accuracy. …

Forecasts play a central role in decision making under uncertainty. After a brief review of the general issues, this … paper considers ways of using high-dimensional data in forecasting. We consider selecting variables from a known active set …-dimensional setting with an application to forecasting UK inflation at different horizons over the period 2020q1-2023q1. This application …

-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature … for forecasting consumption developments. …

nowcasting and forecasting quarterly world GDP using mixed-frequency models. We find that a recently proposed indicator that …

This paper derives new theoretical results for forecasting with Global VAR (GVAR) models. It is shown that the presence … the augmented GVAR model (AugGVAR) uniformly converge in probability to the infeasible optimal forecasts obtained from a … Purchasing Managers Indices (PMIs) for forecasting global (48 countries) growth, and compare forecasts from AugGVAR models with a …

leverage, the optimum and excessive risk and the probability of a debt crisis. The theoretically founded early warning signals …