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Nowcasting Mexico's quarterly GDP using factor models and bridge equations

Author

Listed:
  • Oscar de J. Gálvez-Soriano

    (Banco de México
    University of Houston)

Abstract

Short term forecasts of GDP have become a necessary practice among central banks in order to take better informed monetary policy decisions. In this paper, I evaluate five nowcasting models that I used to forecast Mexico's quarterly GDP in the short run: a dynamic factor model (DFM), two bridge equation (BE) models and two models based on principal components analysis (PCA). The results indicate that the average of the two BE forecasts is statistically better than the rest of the models under consideration, according to the Diebold-Mariano accuracy test (Diebold and Mariano, 1995). Using real-time information, I show that the average of the BE models is also more accurate than the median of the forecasts provided by the analysts surveyed by Bloomberg, the median of the experts who answer Banco de México’s Survey of Professional Forecasters and the rapid GDP estimate released by INEGI.

Suggested Citation

  • Oscar de J. Gálvez-Soriano, 2020. "Nowcasting Mexico's quarterly GDP using factor models and bridge equations," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 35(2), pages 213-265.
    • Handle: RePEc:emx:esteco:v:35:y:2020:i:2:p:213-265
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    File URL: https://estudioseconomicos.colmex.mx/index.php/economicos/article/view/402/510
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    Citations

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    Cited by:

    1. Oscar de Jesús Gálvez-Soriano & Miguel Ramírez-Loyola & Dixia Vega Valdivia, 2022. "Informalidad, pobreza y consumo en México: Evidencia empírica entre 1993 y 2019," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 17(2), pages 1-20, Abril - J.

    More about this item

    Keywords

    forecasting; state space model; principal component analysis; monetary policy; Kalman filter; Diebold-Mariano test;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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