dc.contributor.author | DROUMAGUET, Matthieu | |
dc.contributor.author | WARNE, Anders | |
dc.contributor.author | WOŹNIAK, Tomasz | |
dc.date.accessioned | 2018-11-28T13:12:30Z | |
dc.date.available | 2018-11-28T13:12:30Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Journal of applied econometrics, 2017, Vol. 32, No. 4, pp. 802-818 | |
dc.identifier.issn | 0883-7252 | |
dc.identifier.issn | 1099-1255 | EN |
dc.identifier.uri | https://hdl.handle.net/1814/59586 | |
dc.description | First published: 27 June 2016 | |
dc.description.abstract | In this paper, we derive restrictions for Granger noncausality in MS-VAR models and show under what conditions a variable does not affect the forecast of the hidden Markov process. To assess the noncausality hypotheses, we apply Bayesian inference. The computational tools include a novel block Metropolis-Hastings sampling algorithm for the estimation of the underlying models. We analyze a system of monthly US data on money and income. The results of testing in MS-VARs contradict those obtained with linear VARs: the money aggregate M1 helps in forecasting industrial production and in predicting the next period's state. Copyright (c) 2016 John Wiley & Sons, Ltd. | |
dc.publisher | Wiley | en |
dc.relation.ispartof | Journal of applied econometrics | |
dc.title | Granger causality and regime inference in Markov Switching VAR models with Bayesian methods | |
dc.type | Article | |
dc.identifier.doi | 10.1002/jae.2531 | |
dc.identifier.volume | 32 | |
dc.identifier.startpage | 802 | |
dc.identifier.endpage | 818 | |
eui.subscribe.skip | true | |
dc.identifier.issue | 4 | |