Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/154227
Authors: 
Droumaguet, Matthieu
Warne, Anders
Woźniak, Tomasz
Year of Publication: 
2015
Series/Report no.: 
ECB Working Paper 1794
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’s state.
Subjects: 
Bayesian hypothesis testing
block Metropolis-Hastings sampling
Markov-switching models
mixture models
posterior odds ratio
JEL: 
C11
C12
C32
C53
E32
ISBN: 
978-92-899-1607-3
Document Type: 
Working Paper

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