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GDP Nowcasting: Assessing the Cyclical Conditions of the Argentine Economy

Author

Listed:
  • Laura D'Amato

    (Central Bank of Argentina)

  • Lorena Garegnani

    (Central Bank of Argentina)

  • Emilio Blanco

    (Central Bank of Argentina)

Abstract

Having a contemporaneus 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.

Suggested Citation

  • Laura D'Amato & Lorena Garegnani & Emilio Blanco, 2016. "GDP Nowcasting: Assessing the Cyclical Conditions of the Argentine Economy," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(74), pages 7-26, December.
    • Handle: RePEc:bcr:ensayo:v:1:y:2016:i:74:p:7-26
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    More about this item

    Keywords

    bridge equations; dynamic factor models; nowcasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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