• Medientyp: E-Book; Bericht
  • Titel: Nowcasting GDP in Argentina: Comparing the predictive ability of different models
  • Beteiligte: Blanco, Emilio [VerfasserIn]; D'Amato, Laura [VerfasserIn]; Dogliolo, Fiorella [VerfasserIn]; Garegnani, María Lorena [VerfasserIn]
  • Erschienen: Buenos Aires: Banco Central de la República Argentina (BCRA), Investigaciones Económicas (ie), 2017
  • Sprache: Englisch
  • Schlagwörter: Nowcasting ; C22 ; forecast pooling ; E37 ; dynamic factor models ; C53
  • Entstehung:
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  • Beschreibung: 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.
  • Zugangsstatus: Freier Zugang