Time Series Modeling with Duration Dependent Markov-Switching Vector Autoregressions: MCMC Inference, Software and Applications
AbstractDuration dependent Markov-switching VAR (DDMS-VAR) models are time series models with data generating process consisting in a mixture of two VAR processes, which switches according to a two-state Markov chain with transition probabilities depending on how long the process has been in a state. In the present paper I propose a MCMC-based methodology to carry out inference on the model's parameters and introduce DDMSVAR for Ox, a software written by the author for the analysis of time series by means of DDMS-VAR models. An application of the methodology to the U.S. business cycle concludes the article.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0503008.
Length: 19 pages
Date of creation: 11 Mar 2005
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Markov-switching; Business cycle; Gibbs sampling; Duration dependence; Vector autoregression;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-04-16 (All new papers)
- NEP-ECM-2005-04-16 (Econometrics)
- NEP-ETS-2005-04-16 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Working Paper Series / Economic Activity Section
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- Diebold, Francis X & Rudebusch, Glenn D, 1990.
"A Nonparametric Investigation of Duration Dependence in the American Business Cycle,"
Journal of Political Economy,
University of Chicago Press, vol. 98(3), pages 596-616, June.
- Francis X. Diebold & Glenn D. Rudebusch, 1988. "A nonparametric investigation of duration dependence in the American business cycle," Working Paper Series / Economic Activity Section 90, Board of Governors of the Federal Reserve System (U.S.).
- Francis X. Diebold & Glenn Rudebusch & Daniel Sichel, 1993.
"Further Evidence on Business-Cycle Duration Dependence,"
in: Business Cycles, Indicators and Forecasting, pages 255-284
National Bureau of Economic Research, Inc.
- Francis X. Diebold & Glenn D. Rudebusch & Daniel E. Sichel, 1991. "Further evidence on business cycle duration dependence," Working Papers 91-11, Federal Reserve Bank of Philadelphia.
- 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.
- Durland, J Michael & McCurdy, Thomas H, 1994.
"Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 12(3), pages 279-88, July.
- J. Michael Durland & Thomas H. McCurdy, 1993. "Duration Dependent Transitions in a Markov Model of U.S. GNP Growth," Working Papers 887, Queen's University, Department of Economics.
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