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Conditional Markov chain and its application in economic time series analysis

  • Bai, Jushan
  • Wang, Peng

Motivated by the great moderation in major U.S. macroeconomic time series, we formulate the regime switching problem through a conditional Markov chain. We model the long-run volatility change as a recurrent structure change, while short-run changes in the mean growth rate as regime switches. Both structure and regime are unobserved. The structure is assumed to be Markovian. Conditioning on the structure, the regime is also Markovian, whose transition matrix is structure-dependent. This formulation imposes interpretable restrictions on the Hamilton Markov switching model. Empirical studies show that this restricted model well identifies both short-run regime switches and long-run structure changes in the U.S. macroeconomic data.

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File URL: http://mpra.ub.uni-muenchen.de/33369/1/MPRA_paper_33369.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 33369.

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Date of creation: Aug 2011
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Publication status: Published in Journal of Applied Econometrics 5.26(2011): pp. 715-734
Handle: RePEc:pra:mprapa:33369
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  1. Emi Nakamura & Jón Steinsson & Robert Barro & José Ursúa, 2010. "Crises and Recoveries in an Empirical Model of Consumption Disasters," NBER Working Papers 15920, National Bureau of Economic Research, Inc.
  2. Chang-Jin Kim & Charles Nelson & Jeremy M. Piger, 2003. "The less volatile U.S. economy: a Bayesian investigation of timing, breadth, and potential explanations," Working Papers 2001-016, Federal Reserve Bank of St. Louis.
  3. Gabriel Perez-Quiros & Margaret M. McConnell, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, vol. 90(5), pages 1464-1476, December.
  4. Olivier Blanchard & John Simon, 2001. "The Long and Large Decline in U.S. Output Volatility," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 32(1), pages 135-174.
  5. John Geweke & Gianni Amisano, 2011. "Hierarchical Markov normal mixture models with applications to financial asset returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 1-29, January/F.
  6. Charles R. Nelson, 2000. "Output fluctuations in the United States: what has changed since the early 1980s? comments," Proceedings, Federal Reserve Bank of San Francisco.
  7. Christopher A. Sims & Daniel F. Waggoner & Tao Zha, 2006. "Methods for inference in large multiple-equation Markov-switching models," Working Paper 2006-22, Federal Reserve Bank of Atlanta.
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