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dc.contributor.authorBillio M
dc.contributor.authorCasarin R
dc.contributor.authorRavazzolo F
dc.contributor.authorvan Dijk HK
dc.date2018-01-21T00:00:00Z
dc.date.accessioned2017-10-20T10:03:27Z
dc.date.available2017-10-20T10:03:27Z
dc.date.issued2016
dc.identifier.issn0883-7252
dc.identifier.urihttp://dx.doi.org/10.1002/jae.2501
dc.identifier.urihttp://onlinelibrary.wiley.com/doi/10.1002/jae.2501/abstract
dc.identifier.urihttp://hdl.handle.net/10863/3339
dc.description.abstractThe proposed panel Markov-switching VAR model accommodates changes in low and high data frequencies and incorporates endogenous time-varying transition matrices of country-specific Markov chains, allowing for interconnections. An efficient multi-move sampling algorithm draws time-varying Markov-switching chains. Using industrial production growth and credit spread data, several important data features are obtained. Three regimes appear, with slow growth becoming persistent in the eurozone. Turning point analysis indicates the USA leading the eurozone cycle. Amplification effects influence recession probabilities for Eurozone countries. A credit shock results in temporary negative industrial production growth in Germany, Spain and the USA. Core and peripheral countries exist in the eurozone.en_US
dc.language.isoenen_US
dc.titleInterconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov-Switching VAR Modelen_US
dc.typeArticleen_US
dc.date.updated2016-12-19T14:01:29Z
dc.journal.titleJournal of Applied Econometrics
dc.description.fulltextembargoeden_US


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