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AN N-STATE ENDOGENOUS MARKOV-SWITCHING MODEL WITH APPLICATIONS IN MACROECONOMICS AND FINANCE

Published online by Cambridge University Press:  23 December 2019

Shih-Tang Hwu ,
Chang-Jin Kim  and
Jeremy Piger
Shih-Tang Hwu
Affiliation:
California State Polytechnic University
Chang-Jin Kim
Affiliation:
University of Washington
Jeremy Piger*
Affiliation:
University of Oregon
*
Address correspondence to: Jeremy Piger, Department of Economics, 1285 University of Oregon, Eugene, OR97403, USA. e-mail: [email protected]. Phone: 541-346-6075.
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Abstract

We develop an N-regime Markov-switching model in which the latent state variable driving the regime switching is endogenously determined with the model disturbance term. The models structure captures a wide variety of patterns of endogeneity and yields a simple test of the null hypothesis of exogenous switching. We derive an iterative filter that generates objects of interest, including the model likelihood function and estimated regime probabilities. Using simulation experiments, we demonstrate that the maximum likelihood estimator performs well in finite samples and that a likelihood ratio test of exogenous switching has good size and power properties. We provide results from two applications of the endogenous switching model: a three-state model of US business cycle dynamics and a three-state volatility model of US equity returns. In both cases, we find statistically significant evidence in favor of endogenous switching.

Keywords

Regime SwitchingBusiness Cycle AsymmetryNonlinear ModelsVolatility FeedbackEquity Premium
Type
Articles
Information
Macroeconomic Dynamics , Volume 25 , Issue 8 , December 2021 , pp. 1937 - 1965
Copyright
© Cambridge University Press 2019

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Footnotes

We thank seminar participants at the Federal Reserve Bank of St. Louis, the University of Oregon, the University of Washington, the University of California, Santa Barbara, and the 2017 ASSA meetings for helpful comments. Previous versions of this paper circulated under the title N-State Endogenous Markov-Switching Models.

References

REFERENCES

Bekaert, G. and Wu, G. (2000) Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 142.CrossRefGoogle Scholar
Boldin, M. D. (1996) A check on the robustness of Hamiltons Markov-switching model approach to the economic analysis of the business cycle. Studies in Nonlinear Dynamics and Econometrics 1, 3546.Google Scholar
Burns, A. F. and Mitchell, W. C. (1946) Measuring Business Cycles. New York, NY: National Bureau of Economic Research.Google Scholar
Camacho, M. and Perez-Quiros, G. (2007) Jump and rest effects of U.S. business cycles. Studies in Nonlinear Dynamics and Econometrics 11.Google Scholar
Campbell, J. Y. and Hentschel, L. (1992) No news is good news: An asymmetric model of changing volatility in stock returns. Journal of Financial Economics 31, 281318.CrossRefGoogle Scholar
Diebold, F. X., Lee, J.-H. and Weinbach, G. C. (1994) Regime switching with time-varying transition probabilities. In: Hargreaves, C. (ed.), Nonstationary Time Series Analysis and Cointegration, pp. 283302. Oxford, New York: Oxford University Press.Google Scholar
Fama, E. F. and French, K. R. (2002) The equity premium. Journal of Finance 57, 637659.CrossRefGoogle Scholar
Filardo, A. J. (1994) Business cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12, 299308.Google Scholar
French, K. R., Schwert, W. G. and Stambaugh, R. F. (1987) Expected stock returns and volatility. Journal of Financial Economics 19, 329.CrossRefGoogle Scholar
Garcia, R. and Perron, P. (1996) An analysis of the real interest rate under regime shifts. Review of Economics and Statistics 78, 111125.CrossRefGoogle Scholar
Goldfeld, S. M. and Quandt, R. E. (1973) A Markov model for switching regressions. Journal of Econometrics 1, 316.CrossRefGoogle Scholar
Guidolin, M. and Timmermann, A. (2005) Economic implications of bull and bear regimes in UK stock and bond returns. Economic Journal 115, 111143.CrossRefGoogle Scholar
Hamilton, J. D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357384.CrossRefGoogle Scholar
Hamilton, J. D. (2005) Whats real about the business cycle? Federal Reserve Bank of St. Louis Review 87, 435452.Google Scholar
Hamilton, J. D. (2008) Regime switching models. In: Durlauf, S. N. and Blume, L. E. (eds.), New Palgrave Dictionary of Economics, 2nd ed. London, United Kingdom: Palgrave MacMillan.Google Scholar
Kang, K. H. (2014) Estimation of state-space models with endogenous Markov regime-switching parameters. Econometrics Journal 17, 5682.CrossRefGoogle Scholar
Kim, C.-J. (1994) Dynamic linear models with Markov switching. Journal of Econometrics 60, 122.CrossRefGoogle Scholar
Kim, C.-J., Morley, J., and Piger, J. (2005) Nonlinearity and the permanent effects of recessions. Journal of Applied Econometrics 20, 291309.CrossRefGoogle Scholar
Kim, C.-J., Morley, J. C., and Nelson, C. R. (2004) Is there a positive relationship between stock market volatility and the equity premium? Journal of Money, Credit and Banking 36, 339360.CrossRefGoogle Scholar
Kim, C.-J. and Murray, C. J. (2002) Permanent and transitory components of recessions. Empirical Economics 27, 163183.CrossRefGoogle Scholar
Kim, C.-J. and Nelson, C. R. (1999a) Has the U.S. economy become more stable? A Bayesian approach based on a Markov-switching model of the business cycle. Review of Economics and Statistics 81, 608616.CrossRefGoogle Scholar
Kim, C.-J. and Nelson, C. R. (1999b) State-Space Models with Regime Switching. Cambridge, MA: The MIT Press.Google Scholar
Kim, C.-J., Piger, J. and Startz, R. (2008) Estimation of Markov regime-switching regressions with endogenous switching. Journal of Econometrics 143, 263273.CrossRefGoogle Scholar
McConnell, M. M. and Perez-Quiros, G. (2000) Output fluctuations in the United States: What has changed since the early 1980s? American Economic Review 90, 14641476.CrossRefGoogle Scholar
McCulloch, R. E., Polson, N. G. and Rossi, P. E. (2000) A Bayesian analysis of the multinomial probit model with fully identified parameters. Journal of Econometrics 99, 173193.CrossRefGoogle Scholar
Piger, J. (2009) Econometrics: Models of regime changes. In: Mizrach, B. (ed.), Encyclopedia of Complexity and System Science. New York: Springer.Google Scholar
Sichel, D. E. (1994) Inventories and the three phases of the business cycle. Journal of Business and Economic Statistics 12, 269277.Google Scholar
Sims, C. A. and Zha, T. (2006) Were there regime switches in U.S. monetary policy? American Economic Review 96, 5481.CrossRefGoogle Scholar
Smith, A., Naik, P. A., and Tsai, C.-L. (2006) Markov-switching model selection using Kullback-Leibler divergence. Journal of Econometrics 134, 553577.CrossRefGoogle Scholar
Turner, C. M., Startz, R., and Nelson, C. R. (1989) A Markov model of heteroskedasticity, risk, and learning in the stock market. Journal of Financial Economics 25, 322.CrossRefGoogle Scholar