IDEAS home Printed from https://ideas.repec.org/a/aio/manmar/vxy2012i2p293-300.html

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

Author

Listed:
  • Cristi SPULBAR

    (University of Craiova)

  • Mihai NITOI

    (University of Craiova)

  • Cristian STANCIU

    (University of Craiova)

Abstract

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.

Suggested Citation

  • Cristi SPULBAR & Mihai NITOI & Cristian STANCIU, 2012. "Identifying The Industry Business Cycle Using The Markov Switching Approach In Central And Eastern Europe," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 293-300, November.
    • Handle: RePEc:aio:manmar:v:x:y:2012:i:2:p:293-300
    as

    Download full text from publisher

    File URL: http://manmar.ucv.ro/Arhiva%20articole/2012/Volume%20X%2C%20issue%202-2012/9-28-2-12-FFF.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    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. Fischer, Stanley & Sahay, Ratna & Vegh, Carlos, 1998. "From transition to market: Evidence and growth prospects," MPRA Paper 20615, University Library of Munich, Germany.
    4. 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.
    5. 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.
    6. Laurence Ball, 1994. "What Determines the Sacrifice Ratio?," NBER Chapters, in: Monetary Policy, pages 155-193, National Bureau of Economic Research, Inc.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Chkili, Walid & Nguyen, Duc Khuong, 2014. "Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 31(C), pages 46-56.
    3. Caraiani, Petre, 2012. "Is the Romanian Business Cycle Characterized by Chaos?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 142-151, September.
    4. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
    5. Mr. A. J Hamann & Mr. Alessandro Prati, 2002. "Why Do Many Disinflations Fail? the Importance of Luck, Timing, and Political Institutions," IMF Working Papers 2002/228, International Monetary Fund.
    6. Hofstetter, Marc, 2008. "Disinflations in Latin America and the Caribbean: A free lunch?," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 327-345, March.
    7. Stanley Fischer & Ratna Sahay & Carlos A. Végh, 2002. "Modern Hyper- and High Inflations," Journal of Economic Literature, American Economic Association, vol. 40(3), pages 837-880, September.
    8. Marc Hofstetter, 2007. "Disinflating from moderate inflation in Latin America and Caribbean," Coyuntura Económica, Fedesarrollo.
    9. Shirly Siew-Ling WONG & Chin-Hong PUAH & Shazali ABU MANSOR & Venus Khim-Sen LIEW, 2016. "Measuring Business Cycle Fluctuations: An Alternative Precursor To Economic Crises," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 235-248.
    10. Owyang, Michael T. & Ramey, Garey, 2004. "Regime switching and monetary policy measurement," Journal of Monetary Economics, Elsevier, vol. 51(8), pages 1577-1597, November.
    11. Marc Hofstetter, 2007. "Disinflating From Moderate Inflation," Documentos CEDE 2373, Universidad de los Andes, Facultad de Economía, CEDE.
    12. Thórarinn G. Pétursson, 2018. "Disinflation and improved anchoring of long-term inflation expectations - The Icelandic experience," Economics wp77, Department of Economics, Central bank of Iceland.
    13. Kutu Adebayo Augustine & Ngalawa Harold, 2017. "Monetary Policy and Industrial Output in the BRICS Countries: A Markov-Switching Model," Folia Oeconomica Stetinensia, Sciendo, vol. 17(2), pages 35-55, December.
    14. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    15. Milan Kumar Das & Anindya Goswami, 2019. "Testing of binary regime switching models using squeeze duration analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-20, March.
    16. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, vol. 249(PC).
    17. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model," Working Papers 2013:17, Department of Economics, University of Venice "Ca' Foscari", revised 2014.
    18. Haldrup, Niels & Nielsen, Frank S. & Nielsen, Morten Ørregaard, 2010. "A vector autoregressive model for electricity prices subject to long memory and regime switching," Energy Economics, Elsevier, vol. 32(5), pages 1044-1058, September.
    19. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    20. Chen, Wenting & Huo, Zhongyao & He, Xin-Jiang, 2025. "Analytically pricing commodity futures options in a regime-switching financialization framework," Finance Research Letters, Elsevier, vol. 85(PE).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • M48 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aio:manmar:v:x:y:2012:i:2:p:293-300. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catalin Barbu (email available below). General contact details of provider: https://edirc.repec.org/data/fecraro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.