A Pitfall in Using the Characterization of Granger Non-Causality in Vector Autoregressive Models
Umberto Triacca ()
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Umberto Triacca: Department of Computer Engineering, Computer Science and Mathematics, University of L'Aquila, Via Vetoio I-67010 Coppito, L'Aquila, Italy
Econometrics, 2015, vol. 3, issue 2, 1-7
It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that if this assumption is violated, then the characterization of Granger non-causality in a VAR model fails to hold. In these situations Granger non-causality test results must be interpreted with caution.
Keywords: covariance matrix; Granger causality; time series (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:3:y:2015:i:2:p:233-239:d:47896
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