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Markov switching models in the analysis of business cycle synchronization

Author

Listed:
  • Michał Bernardelli

    (Szkoła Główna Handlowa w Warszawie)

  • Monika Dędys

    (Szkoła Główna Handlowa w Warszawie)

Abstract

In this paper the investigation of the possibility of using the Viterbi paths for the analysis of two-dimensional macroeconomic time series has been done. Two-dimensional Gaussian Markov–Switching model with four-state hidden Markov chain was considered. Two pairs of monthly indexes of industrial production were modelled. Industrial production of Italy and Germany was one pair under consideration and industrial production of Poland and Germany was the second one. The most likely sequence of states of the hidden Markov chain was found for each pair. The comparison of that sequence and analogous sequences determined for one-dimensional model with two-state hidden Markov chain was done. The results of comparison suggests that four-state Viterbi path provides more valuable information about business cycle synchronization of two economies, than two separate two-state Viterbi paths.

Suggested Citation

  • Michał Bernardelli & Monika Dędys, 2015. "Markov switching models in the analysis of business cycle synchronization," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 39, pages 213-228.
    • Handle: RePEc:sgh:annals:i:39:y:2015:p:213-228
    as

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    References listed on IDEAS

    as
    1. Penelope A. Smith & Peter M. Summers, 2005. "How well do Markov switching models describe actual business cycles? The case of synchronization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 253-274.
    2. Phillips, Kerk L., 1991. "A two-country model of stochastic output with changes in regime," Journal of International Economics, Elsevier, vol. 31(1-2), pages 121-142, August.
    3. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
    4. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2004. "The European business cycle," Oxford Economic Papers, Oxford University Press, vol. 56(1), pages 1-44, January.
    5. Dufrénot, Gilles & Keddad, Benjamin, 2014. "Business cycles synchronization in East Asia: A Markov-switching approach," Economic Modelling, Elsevier, vol. 42(C), pages 186-197.
    6. Simpson, Paul W & Osborn, Denise R & Sensier, Marianne, 2001. "Modelling Business Cycle Movements in the UK Economy," Economica, London School of Economics and Political Science, vol. 68(270), pages 243-267, May.
    7. Boldin, Michael D, 1994. "Dating Turning Points in the Business Cycle," The Journal of Business, University of Chicago Press, vol. 67(1), pages 97-131, January.
    8. Boldin Michael D., 1996. "A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-14, April.
    9. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    10. Moolman, Elna, 2004. "A Markov switching regime model of the South African business cycle," Economic Modelling, Elsevier, vol. 21(4), pages 631-646, July.
    11. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Markov switching models; Viterbi path; business cycle synchronization;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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