Working Paper Series, Sveriges Riksbank (Central Bank of Sweden)
No 118:
Causality and Regime Inference in a Markov Switching VAR
Anders Warne ()
Abstract: This paper analyses three Granger noncausality hypotheses
within a conditionally Gaussian MS-VAR model. Noncausality in mean is based
on Granger´s original concept for linear predictors by defining
noncausality from the 1-step ahead forecast error variance for the
conditional expectation. Noncausality in mean-variance concerns the
conditional forecast error variance, while noncausality in distribution
refers to the conditional distribution of the forecast errors. Necessary
and sufficient parametric conditions for noncausality are presented for all
hypotheses. As an illustration, the hypotheses are tested using monthly
postwar U.S. data on money and income. We find that money is not Granger
causal in mean for income, but Granger causal in mean-variance, i.e there
is unique information in money for predicting the next period regime and
the regime affects the uncertainty about the income forecast.
Keywords: Granger causality; Markov process; Regime switching; Vector autoregression; (follow links to similar papers)
JEL-Codes: C32; (follow links to similar papers)
41 pages, December 1, 2000
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