Bayesian inference for periodic regime-switching models
We present a general class of nonlinear time-series Markov regime-switching models for seasonal data which may exhibit periodic features in the hidden Markov process as well as in the laws of motion in each of the regimes. This class of models allows for non-trivial dependencies between seasonal, cyclical and long-term patterns in the data. To overcome the computational burden we adopt a Bayesian approach to estimation and inference. This paper contains two empirical examples as illustration, one uses housing starts data while the other employs US post-Second World War industrial production. © 1998 John Wiley & Sons, Ltd.
Volume (Year): 13 (1998)
Issue (Month): 2 ()
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References listed on IDEAS
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- Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
- Ghysels, Eric, 1994.
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American Statistical Association, vol. 12(3), pages 289-98, July.
- Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-28, April.
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- Ghysels, E., 1993.
"A Time Series Model with Periodic Stochastic Regime Switching,"
Cahiers de recherche
9314, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Eric Ghysels, 1993. "A time series model with periodic stochastic regime switching," Discussion Paper / Institute for Empirical Macroeconomics 84, Federal Reserve Bank of Minneapolis.
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