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The multi-chain Markov switching model

  • Edoardo Otranto

    (Università di Sassari, Italy)

In many real phenomena the behaviour of a certain variable, subject to different regimes, depends on the state of other variables or the same variable observed in other subjects, so the knowledge of the state of the latter could be important to forecast the state of the former. In this paper a particular multivariate Markov switching model is developed to represent this case. The transition probabilities of this model are characterized by the dependence on the regime of the other variables. The estimation of the transition probabilities provides useful information for the researcher to forecast the regime of the variables analysed. Theoretical background and an application are shown. Copyright © 2005 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.965
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 24 (2005)
Issue (Month): 7 ()
Pages: 523-537

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Handle: RePEc:jof:jforec:v:24:y:2005:i:7:p:523-537
DOI: 10.1002/for.965
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
  2. Garcia, R. & Schaller, H., 1995. "Are the Effects of Monetary Policy Asymmetric?," Cahiers de recherche 9505, Universite de Montreal, Departement de sciences economiques.
  3. Bruce E. Hansen, 1995. "Erratum: The Likelihood ratio Test Under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Boston College Working Papers in Economics 296., Boston College Department of Economics.
  4. Edoardo Otranto & Giampiero M. Gallo, 2001. "A Nonparametric Bayesian Approach to Detect the Number of Regimes in Markov Switching Models," Econometrics Working Papers Archive wp2001_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  5. Charles Engel, 1992. "Can the Markov Switching Model Forecast Exchange Rates?," NBER Working Papers 4210, National Bureau of Economic Research, Inc.
  6. 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 357-84, March.
  7. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
  8. Andrew J. Filardo, 1993. "Business cycle phases and their transitional dynamics," Research Working Paper 93-14, Federal Reserve Bank of Kansas City.
  9. Warne, Anders, 2000. "Causality and Regime Inference in a Markov Switching VAR," Working Paper Series 118, Sveriges Riksbank (Central Bank of Sweden).
  10. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  11. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-88, August.
  12. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De.
  13. Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
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