GDP Nowcasting: Assessing the Cyclical Conditions of the Argentine Economy

Abstract

Having a contemporaneous assessment of the economy cyclical conditions is crucial for monetary policy decisions. Since GDP figures are available with a significant delay, Nowcasting techniques, which allow for an immediate perception of the economic cycle, have been increasingly adopted by central banks. We develop an exercise of GDP growth Nowcast using two approaches: bridge equations and factor models. Both methods improve the predictive capacity compared to an AR(1) benchmark. Additionally, the Nowcast based on a factor model surpasses the predictive ability generated by bridge equations. Finally, using the Giacomini and White (2004) test we confirm that these differences in predictive capacity are statistically significant.

JEL classification: C22 ; C53 ; E37