Nowcasting GDP in Argentina: comparing the predictive ability of different models

Abstract

Having a correct assessment of current business cycle conditions is one of the mayor challenges for monetary policy conduct. Given that GDP figures are available with a significant delay central banks are increasingly using Nowcasting as a useful tool for having an immediate perception of economic conditions. We develop a GDP growth Nowcasting exercise using a broad and restricted set of indicators to construct different models including dynamic factor models as well as a FAVAR. We compare their relative forecasting ability using the Giacomini and White (2004) and find no significant difference in predictive ability among them. Nevertheless a combination of them proves to significantly improve predictive performance.