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Prévision de court terme de la croissance du PIB français à l’aide de modèles à facteurs dynamiques

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  • 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, LEDA-CGEMP - Centre de Géopolitique de l’Energie et des Matières Premières - 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, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

In recent years, factor models have received increasing interest from central banks and international organizations to forecast macroeconomic variables. We examine the performance of these models in forecasting the French GDP growth rate over short horizons. The factors are extracted from a large data set including surveys balances, real, financial and international variables. A pseudo real time evaluation over the last decade exhibits a gain relative to the usual benchmarks. However, forecasts remain inaccurate before the beginning of the quarter. We also show that the use of international and financial variables can improve forecasts at the longest horizons.

Suggested Citation

  • Marie Bessec & Catherine Doz, 2012. "Prévision de court terme de la croissance du PIB français à l’aide de modèles à facteurs dynamiques," PSE-Ecole d'économie de Paris (Postprint) hal-01515627, HAL.
    • Handle: RePEc:hal:pseptp:hal-01515627
    Note: View the original document on HAL open archive server: https://hal.science/hal-01515627
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    Cited by:

    1. Zouri, Stéphane, 2019. "Business cycles,bilateral trade and international financial intergration : Evidence from Economic Community of West African States (ECOWAS)," MPRA Paper 98748, University Library of Munich, Germany.
    2. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    3. Nicolas Chatelais & Menzie Chinn & Arthur Stalla-Bourdillon, 2022. "Macroeconomic Forecasting Using Filtered Signals from a Stock Market Cross Section," Working papers 903, Banque de France.
    4. Zouri, Stéphane, 2020. "Business cycles, bilateral trade and financial integration: Evidence from Economic Community of West African States (ECOWAS)," International Economics, Elsevier, vol. 163(C), pages 25-43.
    5. Zouri, Stéphane, 2019. "Business cycles,bilateral trade and international financial intergration : Evidence from Economic Community of West African States (ECOWAS)," MPRA Paper 95275, University Library of Munich, Germany.

    More about this item

    Keywords

    modèles à facteurs; Prévision du PIB;

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