Granger Causality and Regime Inference in Markov Switching VAR Models with Bayesian Methods |
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| Authors: | Matthieu Droumaguet Anders Warne Tomasz Wo?niak |
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| Institution: | 1. Department of Economics, European University Institute, Florence, Italy;2. Directorate General Research, European Central Bank, Frankfurt, Germany;3. Department of Economics, University of Melbourne, Victoria, Australia |
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| 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 © 2016 John Wiley & Sons, Ltd. |
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