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Identifying The Industry Business Cycle Using The Markov Switching Approach In Central And Eastern Europe

Listed author(s):
  • Cristi SPULBAR

    (University of Craiova)

  • Mihai NITOI

    (University of Craiova)

  • Cristian STANCIU

    (University of Craiova)

Registered author(s):

    In this article we use a Markov Switching model with two lags to identify and to compare the business cycle in Romania, Czech Republic, Hungary and Poland using data on industrial production for the 1991-2011 period. We use a model with two regimes that reflect the economic expansions and contractions. The Markov Switching models have been widely used in order to detect and to date the business cycle turning points. However, it should be pointed out that the industrial production may have a little bit different dynamics than the quarterly gross domestic product which is the main measure of economic activity. Based on the smoothed regime probabilities the model track three recessionary periods of the Romanian economy in 1991, 1997 and 2009 and two recessionary periods for the other countries in 1991 and 2009. Mean yoy growth of IPI is 5.01% during expansion periods, while it switches to -18.6% during contraction periods for the Romanian economy. In comparison, mean yoy growth of IPI is 7.25% during expansion periods, while it switches to -13.4% during contraction periods for the Poland economy. Furthermore, in Romania, the duration of the three recessions in months was 25, 25 and 9 months. In Poland, the duration of the two recessions was 16 and 10 months. The results of the study may be used in order to compare the business cycle in Central and Eastern European countries with the Euro Area business cycle.

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    Article provided by University of Craiova, Faculty of Economics and Business Administration in its journal Management and Marketing Journal.

    Volume (Year): X (2012)
    Issue (Month): 2 (November)
    Pages: 293-300

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    Handle: RePEc:aio:manmar:v:x:y:2012:i:2:p:293-300
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    1. Laurence Ball, 1994. "What Determines the Sacrifice Ratio?," NBER Chapters,in: Monetary Policy, pages 155-193 National Bureau of Economic Research, Inc.
    2. Purica, Ionut & Caraiani, Petre, 2009. "Second Order Dynamics Of Economic Cycles," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 36-47, March.
    3. Caraiani, Petre, 2010. "Modeling Business Cycles In The Romanian Economy Using The Markov Switching Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 130-136, March.
    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.
    5. By A. Javier Hamann, 2001. "Exchange-Rate-Based Stabilization: A Critical Look at the Stylized Facts," IMF Staff Papers, Palgrave Macmillan, vol. 48(1), pages 1-4.
    6. Albu, Lucian Liviu, 2001. "Evolution Of Inflation-Unemployment Relationship In The Perspective Of Romania’S Accession To Eu," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-23, December.
    7. Walid Chkili & Duc Khuong Nguyen, 2011. "Modeling the volatility of Mediterranean stock markets: a regime-switching approach," Economics Bulletin, AccessEcon, vol. 31(2), pages 1105-1113.
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