• Media type: Report; E-Book
  • Title: Nowcasting GDP in Argentina: Comparing the predictive ability of different models
  • Contributor: Blanco, Emilio [Author]; D'Amato, Laura [Author]; Dogliolo, Fiorella [Author]; Garegnani, María Lorena [Author]
  • Published: Buenos Aires: Banco Central de la República Argentina (BCRA), Investigaciones Económicas (ie), 2017
  • Language: English
  • Keywords: forecast pooling ; dynamic factor models ; C22 ; E37 ; C53 ; Nowcasting
  • Origination:
  • Footnote: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Description: 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 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) test and find no significant difference in predictive ability among them. Nevertheless a combination of them proves to significantly improve predictive performance.
  • Access State: Open Access