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Choosing information variables for transition probabilities in a time-varying transition probability Markov switching model

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  • Andrew J. Filardo

Abstract

This paper discusses a practical estimation issue for time-varying transition probability (TVTP) Markov switching models. Time-varying transition probabilities allow researchers to capture important economic behavior that may be missed using constant (or fixed) transition probabilities. Despite its use, Hamilton’s (1989) filtering method for estimating fixed transition probability Markov switching models may not apply to TVTP models. This paper provides a set of sufficient conditions to justify the use of Hamilton’s method for TVTP models. In general, the information variables that govern time-variation in the transition probabilities must be conditionally uncorrelated with the state of the Markov process.

Suggested Citation

  • Andrew J. Filardo, 1998. "Choosing information variables for transition probabilities in a time-varying transition probability Markov switching model," Research Working Paper 98-09, Federal Reserve Bank of Kansas City.
  • Handle: RePEc:fip:fedkrw:98-09
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    References listed on IDEAS

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    1. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July.
    2. Kiefer, Nicholas M, 1978. "Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model," Econometrica, Econometric Society, vol. 46(2), pages 427-434, March.
    3. Engel, Charles & Hakkio, Craig S, 1996. "The Distribution of Exchange Rates in the EMS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(1), pages 55-67, January.
    4. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September.
    5. Francis X. Diebold & Joon-Haeng Lee & Gretchen C. Weinbach, 1993. "Regime switching with time-varying transition probabilities," Working Papers 93-12, Federal Reserve Bank of Philadelphia.
    6. Hamilton, James D., 1986. "State-space models," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 50, pages 3039-3080 Elsevier.
    7. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    8. Huntley Schaller & Simon Van Norden, 1997. "Regime switching in stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 7(2), pages 177-191.
    9. Cosslett, Stephen R. & Lee, Lung-Fei, 1985. "Serial correlation in latent discrete variable models," Journal of Econometrics, Elsevier, vol. 27(1), pages 79-97, January.
    10. 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.
    11. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
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    Citations

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    Cited by:

    1. Lopes, José Mário & Nunes, Luis C., 2012. "A Markov regime switching model of crises and contagion: The case of the Iberian countries in the EMS," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 1141-1153.
    2. Carlos Ulibarri, 2005. "Bayesian Learning from Arts Goods? – A Comment," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 29(2), pages 137-141, May.
    3. Grand Nathalie & Dropsy Vincent, 2005. "Exchange Rate And Inflation Targeting In Morocco And Tunisia," Macroeconomics 0507018, University Library of Munich, Germany.
    4. JdD Tena & E. Otranto, 2008. "A Realistic Model for Official Interest Rates," Working Paper CRENoS 200802, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Beine, Michel & Laurent, Sebastien & Lecourt, Christelle, 2003. "Official central bank interventions and exchange rate volatility: Evidence from a regime-switching analysis," European Economic Review, Elsevier, vol. 47(5), pages 891-911, October.
    6. repec:eee:finana:v:54:y:2017:i:c:p:176-191 is not listed on IDEAS
    7. Erlandsson, Ulf, 2005. "Transition Variables in the Markov-switching Model: Some Small Sample Properties," Working Papers 2005:25, Lund University, Department of Economics.
    8. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Possibly Misspeci ed Dynamic Models with Time-Inhomogeneous Markov Regimes," Department of Economics Working Papers 2016_04, Universidad Torcuato Di Tella.
    9. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

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    Keywords

    Time-series analysis ; Estimation theory;

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