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Two Alternative Approaches to Modelling the Nonlinear Dynamics of the Composite Economic Indicator

Author

Listed:
  • Konstantin A. Kholodilin

    (IRES, Université catholique de Louvain)

Abstract

This paper sets up a common unobserved factor model with smooth transition autoregressive dynamics. This model is compared to the already classical common factor model with regime-switching. Both models' in-sample and out-of-sample performance in terms of capturing and predicting the business cycle turning points is evaluated. The comparison of the model-derived probabilities to the NBER business cycle dating shows statistically equivalent in-sample forecasting accuracy of these techniques. The common factor model with exponential STAR outperforms the model with logistic STAR and that with Markov switching in terms of out-of-sample prediction with up to 3 month horizon.

Suggested Citation

  • Konstantin A. Kholodilin, 2002. "Two Alternative Approaches to Modelling the Nonlinear Dynamics of the Composite Economic Indicator," Economics Bulletin, AccessEcon, vol. 3(26), pages 1-18.
    • Handle: RePEc:ebl:ecbull:eb-02c50010
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    Cited by:

    1. Kholodilin Konstantin A., 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 653-674, December.
    2. Konstantin A. Kholodilin, 2006. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Discussion Papers of DIW Berlin 554, DIW Berlin, German Institute for Economic Research.
    3. Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
    4. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research.
    5. Konstantin A., Kholodilin, 2003. "Identifying and Forecasting the Turns of the Japanese Business Cycle," LIDAM Discussion Papers IRES 2003008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).

    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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