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Markov-Switching Model Selection Using Kullback-Leibler Divergence

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Author Info

  • Smith, Aaron D.
  • Naik, Prasad A.
  • Tsai, Chih-Ling

Abstract

In Markov-switching regression models, we use Kullback-Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. In applying Akaike information criterion (AIC), which is an estimate of KL divergence, we find that AIC retains too many states and variables in the model. Hence, we derive a new information criterion, Markov switching criterion (MSC), which yields a marked improvement in state determination and variable selection because it imposes an appropriate penalty to mitigate the over-retention of states in the Markov chain. MSC performs well in Monte Carlo studies with single and multiple states, small and large samples, and low and high noise. Furthermore, it not only applies to Markov-switching regression models, but also performs well in Markov- switching autoregression models. Finally, the usefulness of MSC is illustrated via applications to the U.S. business cycle and the effectiveness of media advertising.

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Bibliographic Info

Paper provided by University of California, Davis, Department of Agricultural and Resource Economics in its series Working Papers with number 11976.

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Date of creation: 2005
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Handle: RePEc:ags:ucdavw:11976

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Keywords: Research Methods/ Statistical Methods;

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References

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Citations

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Cited by:
  1. Takero Doi & Takeo Hoshi & Tatsuyoshi Okimoto, 2011. "Japanese Government Debt and Sustainability of Fiscal Policy," NBER Working Papers 17305, National Bureau of Economic Research, Inc.
  2. Baba, Naohiko & Sakurai, Yuji, 2011. "When and how US dollar shortages evolved into the full crisis? Evidence from the cross-currency swap market," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1450-1463, June.
  3. José Casals Carro & Miguel Jerez Méndez & Sonia Sotoca López, 2006. "Decomposition of state-space Model with inputs: The theory and an application to estimate the ROI of advertising," Documentos del Instituto Complutense de Análisis Económico 0602, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  4. Kerekes, Monika, 2009. "Growth miracles and failures in a Markov switching classification model of growth," Discussion Papers 2009/11, Free University Berlin, School of Business & Economics.
  5. Eric Ghysels & Pierre Guérin & Massimiliano Marcellino, 2013. "Regime Switches in the Risk-Return Trade-Off," Working Papers 13-51, Bank of Canada.
  6. Legerstee, R. & Franses, Ph.H.B.F., 2010. "Does Disagreement Amongst Forecasters have Predictive Value?," Econometric Institute Research Papers EI 2010-53, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  7. N. Baba & Y. Sakurai, 2011. "Predicting regime switches in the VIX index with macroeconomic variables," Applied Economics Letters, Taylor & Francis Journals, vol. 18(15), pages 1415-1419.
  8. Christian Aßmann & Jens Boysen-Hogrefe, 2010. "Analysis of current account reversals via regime switching models," Economic Change and Restructuring, Springer, vol. 43(1), pages 21-43, February.
  9. Roque Montero & Javier García-Cicco, 2012. "Modelo y Pronóstico del Precio del Cobre: Un Enfoque de Cambio de Regímenes," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(2), pages 099-116, August.
  10. repec:hal:cesptp:halshs-00658540 is not listed on IDEAS
  11. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
  12. ZHENG, Tingguo & WANG, Xia & GUO, Huiming, 2012. "Estimating forward-looking rules for China's Monetary Policy: A regime-switching perspective," China Economic Review, Elsevier, vol. 23(1), pages 47-59.
  13. Maciejowska, Katarzyna, 2013. "Assessing the number of components in a normal mixture: an alternative approach," MPRA Paper 50303, University Library of Munich, Germany.
  14. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
  15. Lee, Hwa-Taek & Yoon, Gawon, 2007. "Does Purchasing Power Parity Hold Sometimes? Regime Switching in Real Exchange Rates," Economics Working Papers 2007,24, Christian-Albrechts-University of Kiel, Department of Economics.
  16. repec:hal:journl:halshs-00658540 is not listed on IDEAS
  17. Rianne Legerstee & Philip Hans Franses, 2010. "Does Disagreement amongst Forecasters have Predictive Value?," Tinbergen Institute Discussion Papers 10-088/4, Tinbergen Institute.
  18. Davide Debortoli & Ricardo Nunes, 2011. "Monetary regime switches and unstable objectives," International Finance Discussion Papers 1036, Board of Governors of the Federal Reserve System (U.S.).
  19. Katarzyna Maciejowska, 2010. "Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 2(4), pages 279-314, September.
  20. Peter Ebbes & Rajdeep Grewal & Wayne DeSarbo, 2010. "Modeling strategic group dynamics: A hidden Markov approach," Quantitative Marketing and Economics, Springer, vol. 8(2), pages 241-274, June.
  21. Xu, Jianjun & Tan, Xianming & Zhang, Runchu, 2010. "A note on Phillips (1991): "A constrained maximum likelihood approach to estimating switching regressions"," Journal of Econometrics, Elsevier, vol. 154(1), pages 35-41, January.

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