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

Econometrics

Umberto Triacca¹ 

[1] Department of Computer Engineering, Computer Science and Mathematics, University of L’Aquila, Via Vetoio I-67010 Coppito, L’Aquila, Italy; E-Mail

关键词: covariance matrix;    Granger causality;    time series;   

DOI  :  10.3390/econometrics3020233

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the author; licensee MDPI, Basel, Switzerland.