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Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP

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  • Pablo Duarte
  • Bernd Süssmuth

Abstract

Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals with the implementation stage of this practice. We propose a two-tiered mechanism consisting in the identification of variables highly correlated with GDP as “core” indicators and a check of robustness of these variables in the sense of extreme bounds analysis. Accordingly selected indicators are used in an approximate DFM framework to exemplarily nowcast Spanish GDP growth. We show that our implementation produces more accurate nowcasts than both a benchmark stochastic process and the implementation based on the total set of core indicators.

Suggested Citation

  • Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo.
    • Handle: RePEc:ces:ceswps:_4574
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    References listed on IDEAS

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    6. Jörg Breitung & Sandra Eickmeier, 2006. "Dynamic Factor Models," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 3, pages 25-40, Springer.
    7. Castle, Jennifer L. & Fawcett, Nicholas W.P. & Hendry, David F., 2009. "Nowcasting is not Just Contemporaneous Forecasting," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210, pages 71-89, October.
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    9. Elena Angelini & Marta Banbura & Gerhard Rünstler, 2010. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-22.
    10. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    11. Maximo Camacho & Agustin Garcia‐Serrador, 2014. "The Euro‐Sting Revisited: The Usefulness of Financial Indicators to Obtain Euro Area GDP Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 186-197, April.
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    Cited by:

    1. Pablo Duarte, 2017. "The relationship between GDP and the size of the informal economy: empirical evidence for Spain," Empirical Economics, Springer, vol. 52(4), pages 1409-1421, June.

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    More about this item

    Keywords

    small-scale nowcasting models; Kalman Filter; extreme bounds analysis;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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