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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Economic Research Working Papers ; No. 74

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Forecasting Models; Simulation Methods ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
• Subject: Nowcasting ; dynamic factor models ; forecast pooling

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Blanco, Emilio ; D'Amato, Laura ; Dogliolo, Fiorella ; Garegnani, María Lorena
• Event: Veröffentlichung
• (who): Banco Central de la República Argentina (BCRA), Investigaciones Económicas (ie)
• (where): Buenos Aires
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/202481
• Last update: 10.03.2025, 11:41 AM CET