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Latent Leading and Coincident Factors Model with Markov-Switching Dynamics

Author

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  • Konstantin Kholodilin

    (Institut des recherches économiques et sociales)

Abstract

This paper introduces a two-factor model of leading and coincident economic indicators. The common leading factor is assumed to Granger-cause the common coincident factor. This property is used to estimate the two common factors simultaneously and hence more efficiently. Two models of the latent leading and coincident factors are studied: a model with linear dynamics and a model with Markov-switching dynamics introduced through the leading factor intercept term. The first model encompasses the comovements between the individual time series. The second model, moreover, takes care of possible asymmetries between the business cycle regimes.

Suggested Citation

  • Konstantin Kholodilin, 2001. "Latent Leading and Coincident Factors Model with Markov-Switching Dynamics," Economics Bulletin, AccessEcon, vol. 3(7), pages 1-13.
    • Handle: RePEc:ebl:ecbull:eb-01c50001
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    References listed on IDEAS

    as
    1. Chauvet, Marcelle & Potter, Simon, 2000. "Coincident and leading indicators of the stock market," Journal of Empirical Finance, Elsevier, vol. 7(1), pages 87-111, May.
    2. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    3. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    4. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    5. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
    6. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
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    Citations

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    Cited by:

    1. 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.
    2. repec:ebl:ecbull:v:3:y:2002:i:5:p:1-15 is not listed on IDEAS
    3. 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.
    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.

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    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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