Duration Dependent Markov-Switching Vector Autoregression: Properties, Bayesian Inference, Software and Application
Duration dependent Markov-switching VAR (DDMS-VAR) models are time series models with data generating process consisting in a mixture of two VAR processes. The switching between the two VAR processes is governed by a two state Markov chain with transition probabilities that depend on how long the chain has been in a state. In the present paper we analyze the second order properties of such models and propose a Markov chain Monte Carlo algorithm to carry out Bayesian inference on the model’s unknowns. Furthermore, a freeware software written by the author for the analysis of time series by means of DDMS-VAR models is illustrated. The methodology and the software are applied to the analysis of the U.S. business cycle.
|Date of creation:||Aug 2003|
|Date of revision:||Nov 2005|
|Contact details of provider:|| Postal: |
Web page: http://www.statistica.unimib.it
More information through EDIRC
References listed on IDEAS
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.:
- 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.
- 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.).
- Daniel E. Sichel, 1989.
"Business cycle duration dependence: a parametric approach,"
Working Paper Series / Economic Activity Section
98, Board of Governors of the Federal Reserve System (U.S.).
- Sichel, Daniel E, 1991. "Business Cycle Duration Dependence: A Parametric Approach," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 254-60, May.
- Kim, Chang-Jin, 1994.
"Dynamic linear models with Markov-switching,"
Journal of Econometrics,
Elsevier, vol. 60(1-2), pages 1-22.
- Francis X. Diebold & Glenn D. Rudebusch & Daniel E. Sichel, 1991.
"Further evidence on business cycle duration dependence,"
91-11, Federal Reserve Bank of Philadelphia.
- Francis X. Diebold & Glenn Rudebusch & Daniel Sichel, 1993. "Further Evidence on Business-Cycle Duration Dependence," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 255-284 National Bureau of Economic Research, Inc.
- 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.
When requesting a correction, please mention this item's handle: RePEc:mis:wpaper:20051101. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matteo Pelagatti)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.