Granger causality and regime inference in Bayesian Markov-Switching VARs

Anders Warne, Matthieu Droumaguet and Tomasz Woźniak

No 1794, Working Paper Series from European Central Bank

Abstract: We derive restrictions for Granger noncausality in Markov-switching vector autoregressive models and also show under which conditions a variable does not affect the forecast of the hidden Markov process. Based on Bayesian approach to evaluating the hypotheses, the computational tools for posterior inference include a novel block Metropolis-Hastings sampling algorithm for the estimation of the restricted models. We analyze a system of monthly US data on money and income. The test results in MS-VARs contradict those in linear VARs: the money aggregate M1 is useful for forecasting income and for predicting the next period JEL Classification: C11, C12, C32, C53, E32

Keywords: Bayesian hypothesis testing; block Metropolis-Hastings sampling; Markov-switching models; mixture models; posterior odds ratio (search for similar items in EconPapers)
Date: 2015-05
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
Note: 563011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20151794

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