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

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  • Marie Bessec
  • Catherine Doz

Abstract

[eng] Short-Term Forecasting of French GDP Growth Using Dynamic Factor Models. . In recent years, central banks and international organizations have been making ever greater use of factor models to forecastmacroeconomic variables. We examine the performance of thesemodels in forecasting FrenchGDPgrowth over short horizons. The factors are extracted from a large dataset 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. [fre] Les banques centrales et les organismes internationaux recourent de plus en plus aux modèles à facteurs pour prévoir les grands agrégats macroéconomiques. Nous étudions l’apport de ces modèles à la prévision conjoncturelle du taux de croissance trimestriel du PIB français. Les facteurs sont extraits d’une base constituée d’une centaine de variables comprenant des soldes d’enquêtes et des variables réelles, monétaires, financières et internationales. Une évaluation hors échantillon en quasi temps réel sur la dernière décennie montre que les performances prédictives des modèles à facteurs surpassent celles des modèles de référence usuels. Toutefois, les prévisions effectuées avant le début du trimestre à prévoir restent fragiles. Nous montrons également que l’utilisation de variables internationales et financières permet d’améliorer les prévisions aux horizons les plus lointains.

Suggested Citation

  • Marie Bessec & Catherine Doz, 2012. "Prévision à court terme de la croissance du PIB français à l’aide de modèles à facteurs dynamiques," Économie et Prévision, Programme National Persée, vol. 199(1), pages 1-30.
  • Handle: RePEc:prs:ecoprv:ecop_0249-4744_2012_num_199_1_8096
    DOI: 10.3406/ecop.2012.8096
    Note: DOI:10.3406/ecop.2012.8096
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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 95275, 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. 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.
    4. 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.
    5. 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.

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