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

Marie Bessec and Catherine Doz ()
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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
Catherine Doz: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

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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.

Keywords: GDP forecast; factor models (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (4)

Published in Journal of business cycle measurement and analysis, 2014, 2013 (2), ⟨10.1787/jbcma-2013-5jz742l0pt8s⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01515602

DOI: 10.1787/jbcma-2013-5jz742l0pt8s

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