A flexible prior distribution for Markov switching autoregressions with Student-t errors
This paper proposes an empirical Bayes approach for Markov switching autoregressions that can constrain some of the state-dependent parameters (regression coefficients and error variances) to be approximately equal across regimes. By flexibly reducing the dimension of the parameter space, this can help to ensure regime separation and to detect the Markov switching nature of the data. The permutation sampler with a hierarchical prior is used for choosing the prior moments, the identification constraint, and the parameters governing prior state dependence. The empirical relevance of the methodology is illustrated with an application to quarterly and monthly real interest rate data.
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- John Geweke, 2004. "Getting It Right: Joint Distribution Tests of Posterior Simulators," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 799-804, January.
- van Dijk, Dick & Teräsvirta, Timo & Franses, Philip Hans, 2000.
"Smooth Transition Autoregressive Models - A Survey of Recent Developments,"
SSE/EFI Working Paper Series in Economics and Finance
380, Stockholm School of Economics, revised 17 Jan 2001.
- Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
- van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Donald W.K. Andrews, 1988.
"Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation,"
Cowles Foundation Discussion Papers
877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
- Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May.
- Sylvia Fruhwirth-Schnattaer & Sylvia Kaufmann, 2000. "Bayesian Analysis of Switching ARCH Models," Econometric Society World Congress 2000 Contributed Papers 1381, Econometric Society.
- Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998.
"Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models,"
Review of Economic Studies,
Wiley Blackwell, vol. 65(3), pages 361-93, July.
- Tom Doan, . "RATS programs to replicate Jacquier, Polson, Rossi (1994) stochastic volatility," Statistical Software Components RTZ00105, Boston College Department of Economics.
- Sangjoon Kim & Neil Shephard, 1994. "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers 3., Economics Group, Nuffield College, University of Oxford.
- Tom Doan, . "KSCPOSTDRAW: RATS procedure to draw from posterior density needed in stochastic volatility model," Statistical Software Components RTS00101, Boston College Department of Economics.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, EconWPA.
- Sangjoon Kim, Neil Shephard & Siddhartha Chib, . "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
- C. P. Robert & T. Rydén & D. M. Titterington, 2000. "Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 57-75.
- Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De.
- Garcia, R. & Perron, P., 1994.
"An Analysis of the Real Interest rate Under Regime Shifts,"
Cahiers de recherche
9428, Universite de Montreal, Departement de sciences economiques.
- Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-25, February.
- Garcia, R. & Perron, P., 1990. "An Anlysis Of The Real Interest Rate Under Regime Shifts," Papers 353, Princeton, Department of Economics - Econometric Research Program.
- René Garcia & Pierre Perron, 1995. "An Analysis of the Real Interest Rate Under Regime Shifts," CIRANO Working Papers 95s-05, CIRANO.
- Garcia, R. & Perron, P., 1994. "An Analysis of the Real Interest rate Under Regime Shifts," Cahiers de recherche 9428, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- John Geweke, 1995.
"Monte Carlo simulation and numerical integration,"
192, Federal Reserve Bank of Minneapolis.
- Fruhwirth-Schnatter S., 2001. "Markov Chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 194-209, March.
- 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.
- Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
- Andrews, Donald W K & Monahan, J Christopher, 1992.
"An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator,"
Econometric Society, vol. 60(4), pages 953-66, July.
- Donald W.K. Andrews & Christopher J. Monahan, 1990. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Cowles Foundation Discussion Papers 942, Cowles Foundation for Research in Economics, Yale University.
- Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
- 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.
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