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Use of the Markov switching models for identification of turning points in the business cycles of selected countries

Author

Listed:
  • Monika Kośko

    (Wyższa Szkoła Informatyki i Ekonomii w Olsztynie)

  • Marta Kwiecień

    (Uniwersytet Warmińsko-Mazurski w Olsztynie)

  • Joanna Stempińska

    (Uniwersytet Warmińsko-Mazurski w Olsztynie)

Abstract

The article presents an example of application of the Markov switching models (MS) to identify phases and turning points in the business cycles of selected countries, including Poland. Models are calculated on the basis of GDP series. The Markov switching models constitute a more developed structure of Markov chains. In the MS models it is not necessary to determine states (regimes), because they are unobservable. However, based on the value of the transition probabilities between the states, moments of transition between states and the time of being in the states can be predicted. With regard to business cycles, the states of the process match the phases of the business cycle. The Markov switching model identifies these states and allows to calculate the most important statistic values such as the mean and variance (in states) and to forecast turning points of business cycles.

Suggested Citation

  • Monika Kośko & Marta Kwiecień & Joanna Stempińska, 2015. "Use of the Markov switching models for identification of turning points in the business cycles of selected countries," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 36, pages 511-523.
    • Handle: RePEc:sgh:annals:i:36:y:2015:p:511-523
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    References listed on IDEAS

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    3. Hans-Martin Krolzig, 2001. "Markov-Switching Procedures for Dating the Euro-Zone Business Cycle," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 70(3), pages 339-351.
    4. 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.
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