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Dynamic factor models: A review of the literature

Author

Listed:
  • Karim Barhoumi

    (International Monetary Fund (IMF))

  • Olivier Darné

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

  • Laurent Ferrara

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

For few years, the increasing size of available economic and financial databases has led econometricians to develop and adapt new methods in order to efficiently summarize information contained in those large datasets. Among those methods, dynamic factor models have known a rapid development and a large success among macroeconomists. In this paper, we carry out a review of the recent literature on dynamic factor models. First we present the models used, then the parameter estimation methods and finally the statistical tests available to choose the number of factors. In the last section, we focus on recent empirical applications, especially dealing with the building of economic outlook indicators, macroeconomic forecasting and macroeconomic and monetary policy analyses.

Suggested Citation

  • Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Dynamic factor models: A review of the literature," Post-Print hal-01385974, HAL.
  • Handle: RePEc:hal:journl:hal-01385974
    DOI: 10.1787/jbcma-2013-5jz417f7b7nv
    Note: View the original document on HAL open archive server: https://hal.parisnanterre.fr/hal-01385974
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    17. Hallin, Marc & Liska, Roman, 2011. "Dynamic factors in the presence of blocks," Journal of Econometrics, Elsevier, vol. 163(1), pages 29-41, July.
    18. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    19. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    20. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP," Economics Working Papers ECO2009/13, European University Institute.
    21. Marcellino, Massimiliano & Schumacher, Christian, 2007. "Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP," Discussion Paper Series 1: Economic Studies 2007,34, Deutsche Bundesbank.

    More about this item

    Keywords

    dynamic factor models; estimation; tests for the number of factors; macroeconomic applications;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • 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
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles

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