Time Series Modeling with Duration Dependent Markov-Switching Vector Autoregressions: MCMC Inference, Software and Applications

Matteo Pelagatti

Econometrics from University Library of Munich, Germany

Abstract: Duration 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.

Keywords: Markov-switching; Business cycle; Gibbs sampling; Duration dependence; Vector autoregression (search for similar items in EconPapers)
JEL-codes: C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2005-03-11
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: Type of Document - pdf; pages: 19
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0503008

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