Forecasting Macro-Financial Variables in an International Data-Rich Environment Vector Autoregressive Model (iDREAM)

We propose a new data-rich environment model of the yield curve, the macroeconomy, monetary policies and effective exchange rates for a panel of 11 countries: the iDREAM. The endogenous variables are observable (short- and long-term interest rates, exchange rates) and latent factors (economic activity, inflation, monetary policy). Local economies are modeled in a FAVECM with weakly exogenous variables and then linked by means of a connectedness matrix estimated with a network approach. We show that our approach outperforms alternative forecasting models, including a standard Global VAR, in particular for predictions on international business cycles and long-term interest rates