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Analysis of the U.S. Business Cycle with a Vector-Markov-Switching Model


  • Zenon Kontolemis


This paper identifies turning points for the U.S. business cycle using different time series. The model, a multivariate Markov-Swiching model, assumes that each series is characterized by a mixture of two normal distributions (a high and low mean) with switching determined by a common Markov process. The procedure is applied to the series that make up the composite U.S. coincident indicator to obtain business cycle turning points. The business cycle chronology is closer to the NBER reference cycle than the turning points obtained from the individual series using a univariate model. The model is also used to forecast the series, with encouraging results.

Suggested Citation

  • Zenon Kontolemis, 1999. "Analysis of the U.S. Business Cycle with a Vector-Markov-Switching Model," IMF Working Papers 99/107, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:99/107

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    References listed on IDEAS

    1. Drake, Leigh & Hall, Maximilian J. B., 2003. "Efficiency in Japanese banking: An empirical analysis," Journal of Banking & Finance, Elsevier, vol. 27(5), pages 891-917, May.
    2. McKillop, Donal G. & Glass, J. Colin & Morikawa, Yukio, 1996. "The composite cost function and efficiency in giant Japanese banks," Journal of Banking & Finance, Elsevier, vol. 20(10), pages 1651-1671, December.
    3. Gianni De Nicolo & Mary G Zephirin & Philip F. Bartholomew & Jahanara Zaman, 2003. "Bank Consolidation, Internationalization, and Conglomeration; Trends and Implications for Financial Risk," IMF Working Papers 03/158, International Monetary Fund.
    4. Joaquin Maudos & Jose Pastor, 2001. "Cost and profit efficiency in banking: an international comparison of Europe, Japan and the USA," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 383-387.
    5. International Monetary Fund, 2004. "Germany's Three-Pillar Banking System; Cross-Country Perspectives in Europe," IMF Occasional Papers 233, International Monetary Fund.
    6. Altunbas, Yener & Liu, Ming-Hau & Molyneux, Philip & Seth, Rama, 2000. "Efficiency and risk in Japanese banking," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1605-1628, October.
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    Cited by:

    1. Moolman, Elna, 2004. "A Markov switching regime model of the South African business cycle," Economic Modelling, Elsevier, vol. 21(4), pages 631-646, July.
    2. Stéphane GOUTTE & Benteng Zou, 2011. "Foreign exchange rates under Markov Regime switching model," CREA Discussion Paper Series 11-16, Center for Research in Economic Analysis, University of Luxembourg.
    3. Adél Bosch & Franz Ruch, 2012. "An alternative business cycle dating procedure for South Africa," Working Papers 267, Economic Research Southern Africa.
    4. Robert A Buckle & David Haugh & Peter Thomson, 2002. "Growth and volatility regime switching models for New Zealand GDP data," Treasury Working Paper Series 02/08, New Zealand Treasury.
    5. Lars-Erik Öller & Lasse Koskinen, 2004. "A classifying procedure for signalling turning points," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 197-214.
    6. David Bock & Eva Andersson & Marianne Frisén, 2005. "Statistical surveillance of cyclical processes with application to turns in business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 465-490.
    7. Stéphane Goutte & Benteng Zou, 2012. "Continuous time regime switching model applied to foreign exchange rate," Working Papers hal-00643900, HAL.
    8. E. Andersson & D. Bock & M. Frisen, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 257-278.


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