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New directions in business cycle research and financial analysis

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Author Info

  • James D. Hamilton

    ()
    (Department of Economics, 0508, University of California, San Diego, La Jolla, CA 92093-0508)

  • Baldev Raj

    ()
    (School of Business and Economics, Wilfrid Laurier University, 75 University Aveneu, Waterloo, Ontario, Canada N2L 3C5)

Abstract

This paper serves as a partial introduction to and survey of the literature on Markov-switching models. We review the history of this class of models, describe their mathematical structure, and exposit the basic ideas behind estimation and inference. The paper also describes how the approach can be extended in a variety of directions, such as non-Gaussian distributions, time-varying transition probabilities, vector processes, state-space and GARCH models, and surveys recent methodological advances. The contributions of the other papers in this volume are reviewed. A final section offers conclusions and implications for policy.

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 27 (2002)
Issue (Month): 2 ()
Pages: 149-162

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Handle: RePEc:spr:empeco:v:27:y:2002:i:2:p:149-162

Note: Received: August 2001/Final Version Received: October 2001
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Related research

Keywords: Markov-switching; regime-switching; business cycles;

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Citations

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Cited by:
  1. Torsten Schmidt & Torge Middendorf, 2004. "Characterizing Movements of the U.S. Current Account Deficit," RWI Discussion Papers 0024, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.
  2. Robinson Kruse & Michael Frömmel & Lukas Menkhoff & Philipp Sibbertsen, 2009. "What do we know about real exchange rate non-linearities?," CREATES Research Papers 2009-50, School of Economics and Management, University of Aarhus.
  3. Carlo Altavilla & Luigi Luini & Patrizia Sbriglia, 2005. "Social Learning in Market Games," Labsi Experimental Economics Laboratory University of Siena 003, University of Siena.
  4. Alexandros E. Milionis, 2003. "Modelling Economic Time Series in the Presence of Variance Non-Stationarity: A Practical Approach," Working Papers 07, Bank of Greece.
  5. Hyginus Leon & Serineh Najarian, 2005. "Asymmetric adjustment and nonlinear dynamics in real exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(1), pages 15-39.
  6. Chao-Chun Chen & Wen-Jen Tsay, 2007. "Estimating Markov-Switching ARMA Models with Extended Algorithms of Hamilton," IEAS Working Paper : academic research 07-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  7. Bradley, Michael D. & Jansen, Dennis W., 2004. "Forecasting with a nonlinear dynamic model of stock returns and industrial production," International Journal of Forecasting, Elsevier, vol. 20(2), pages 321-342.
  8. Chen, Chao-Chun & Tsay, Wen-Jen, 2006. "The Beveridge-Nelson decomposition of Markov-switching processes," Economics Letters, Elsevier, vol. 91(1), pages 83-89, April.
  9. Ihle, Rico & von Cramon-Taubadel, Stephan, 2008. "Nonlinear Vector Error Correction Models in Price Transmission Analysis: Threshold Models vs. Markov-Switching Models," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44198, European Association of Agricultural Economists.
  10. Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," NBER Working Papers 9839, National Bureau of Economic Research, Inc.
  11. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October.
  12. Yukalov, V.I. & Sornette, D. & Yukalova, E.P., 2009. "Nonlinear dynamical model of regime switching between conventions and business cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 206-230, May.

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