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

Working papers | 2017 | N 74

Abstract

Having a correct assessment of current business cycle conditions is one of the major challenges for monetary policy conduct. Given that GDP figures are available with 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) test and find no significant difference in predictive ability among them. Nevertheless a combinations of them proves to significantly improve predictive performance.

JEL classification: C22, C53, E37