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Short-term forecasting of French GDP growth using dynamic factor models

Author

Listed:
  • Marie Bessec

    (LEDa - Laboratoire d'Economie de Dauphine - IRD - Institut de Recherche pour le Développement - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Catherine Doz

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

In recent years, central banks and international organisations have been making ever greater use of factor models to forecast macroeconomic variables. We examine the performance of these models in forecasting French GDP growth over short horizons. The factors are extracted from a large data set of around one hundred variables including survey balances and real, financial, and international variables. An out-of-sample pseudo real-time evaluation over the past decade shows that factor models provide a gain in accuracy relative to the usual benchmarks. However, the forecasts remain inaccurate before the start of the quarter. We also show that the inclusion of international and financial variables can improve forecasts at the longest horizons.

Suggested Citation

  • Marie Bessec & Catherine Doz, 2014. "Short-term forecasting of French GDP growth using dynamic factor models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01515602, HAL.
    • Handle: RePEc:hal:cesptp:hal-01515602
    DOI: 10.1787/jbcma-2013-5jz742l0pt8s
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    Cited by:

    1. Cascaldi-Garcia, Danilo & Ferreira, Thiago R.T. & Giannone, Domenico & Modugno, Michele, 2024. "Back to the present: Learning about the euro area through a now-casting model," International Journal of Forecasting, Elsevier, vol. 40(2), pages 661-686.
    2. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    3. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.

    More about this item

    Keywords

    GDP forecast; factor models;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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