IDEAS home Printed from
   My bibliography  Save this paper

Semi-Markov Regime Switching Regression Models


  • Ingo Bulla

    () (Laboratoire de Mathématiques Université de Bretagne Occidentale)


Markov switching regression processes belong to the class of Hidden Markov models (HMMs). They provide a higher flexibility than, for example, simple (auto)regression. The main reason for their popularity is the convenient interpretability. For sufficiently long time series, the different regimes can be associated with abrupt macroeconomic events (war, changing governmental policy,etc.). However, it is not always intuitively clear why the regime switching follows a Markov law. Hidden semi-Markov models (HSMMs) are an extension of HMMs. The most appealing property of a HSMM lies in the flexibility of the runlength distributions which are given explicitly instead of implicitly following the geometric distributions of a HMM. We present a generalization of the Markov regime switching framework and introduce the semi-Markov switching (auto)regressive processes. In particular, we focus on the theory for right-censored HSMMs introduced by Guédon in 2003. We present an EM algorithm for auto(regression) models with different state occupancy distributions. Subsequently, we investigate a modified, computational convenient M-step in terms of the One-Step-Late. Finally, the performance of the estimation procedure is analyzed using an economic data set

Suggested Citation

  • Ingo Bulla, 2006. "Semi-Markov Regime Switching Regression Models," Computing in Economics and Finance 2006 438, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:438

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    1. Chiarella,Carl & Flaschel,Peter, 2011. "The Dynamics of Keynesian Monetary Growth," Cambridge Books, Cambridge University Press, number 9780521180184, March.
    2. Loren Brandt & Xiaodong Zhu, 2000. "Redistribution in a Decentralized Economy: Growth and Inflation in China under Reform," Journal of Political Economy, University of Chicago Press, vol. 108(2), pages 422-451, April.
    3. Lane, Philip R., 2001. "The new open economy macroeconomics: a survey," Journal of International Economics, Elsevier, vol. 54(2), pages 235-266, August.
    4. Brandt, Loren & Zhu, Xiaodong, 2001. "Soft budget constraint and inflation cycles: a positive model of the macro-dynamics in China during transition," Journal of Development Economics, Elsevier, vol. 64(2), pages 437-457, April.
    5. Dornbusch, Rudiger, 1976. "Expectations and Exchange Rate Dynamics," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1161-1176, December.
    6. Ray C. Fair, 2000. "Testing the NAIRU Model for the United States," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 64-71, February.
    7. Lawrence H. Summers, 2000. "International Financial Crises: Causes, Prevention, and Cures," American Economic Review, American Economic Association, pages 1-16.
    8. Obstfeld, Maurice & Rogoff, Kenneth, 1995. "Exchange Rate Dynamics Redux," Journal of Political Economy, University of Chicago Press, vol. 103(3), pages 624-660, June.
    9. Carl Chiarella & Peter Flaschel & Gang Gong & Willi Semmler, 2002. "Nonlinear Phillips Curves, Complex Dynamics and Monetary Policy in a Keynesian Macro Model," Working Paper Series 120, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    10. Stanley Fischer, 2001. "Exchange Rate Regimes: Is the Bipolar View Correct?," Journal of Economic Perspectives, American Economic Association, vol. 15(2), pages 3-24, Spring.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Hidden semi-Markov model; One-Step-Late algorithm; regime switching; regression; right-censoring;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques


    Access and download statistics


    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:sce:scecfa:438. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.