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dc.contributor.authorDROUMAGUET, Matthieu
dc.contributor.authorWOŹNIAK, Tomasz
dc.date.accessioned2012-03-02T11:35:11Z
dc.date.available2012-03-02T11:35:11Z
dc.date.issued2012
dc.identifier.issn1725-6704
dc.identifier.urihttp://hdl.handle.net/1814/20815
dc.description.abstractRecent economic developments have shown the importance of spillover and contagion effects in financial markets as well as in macroeconomic reality. Such effects are not limited to relations between the levels of variables but also impact on the volatility and the distributions. We propose a method of testing restrictions for Granger noncausality on all these levels in the framework of Markov-switching Vector Autoregressive Models. The conditions for Granger noncausality for these models were derived by Warne (2000). Due to the nonlinearity of the restrictions, classical tests have limited use. We, therefore, choose a Bayesian approach to testing. The inference consists of a novel Gibbs sampling algorithm for estimation of the restricted models, and of standard methods of computing the Posterior Odds Ratio. The analysis may be applied to financial and macroeconomic time series with complicated properties, such as changes of parameter values over time and heteroskedasticity.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesEUI ECOen
dc.relation.ispartofseries2012/06en
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectGranger Causalityen
dc.subjectMarkov Switching Modelsen
dc.subjectHypothesis Testingen
dc.subjectPosterior Odds Ratioen
dc.subjectGibbs Samplingen
dc.titleBayesian Testing of Granger Causality in Markov-Switching VARsen
dc.typeWorking Paperen
dc.neeo.contributorDROUMAGUET|Matthieu|aut|
dc.neeo.contributorWOZNIAK|Tomasz|aut|
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