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A Pitfall in Using the Characterization of Granger Non-Causality in Vector Autoregressive Models

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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)

Abstract

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.

Suggested Citation

  • Umberto Triacca, 2015. "A Pitfall in Using the Characterization of Granger Non-Causality in Vector Autoregressive Models," Econometrics, MDPI, vol. 3(2), pages 1-7, April.
    • Handle: RePEc:gam:jecnmx:v:3:y:2015:i:2:p:233-239:d:47896
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    References listed on IDEAS

    as
    1. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    2. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    3. Gonzalo, Jesus & Lee, Tae-Hwy, 1998. "Pitfalls in testing for long run relationships," Journal of Econometrics, Elsevier, vol. 86(1), pages 129-154, June.
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