Judging by the number of hits, comments, and questions that I've had in relation to my various posts on testing for Granger (Non-) Causality, this seems to be a topic that a lot of followers find interesting. For instance, see the posts
here,
here,
here, and especially
here.
In the comments, and in a large number of related emails that I've received, several questions seem to recur, and I thought it would be worth addressing them in one place - right here, to be specific!
The following discussion relates to the (usual) case where there is the
possibility that one or more of the time-series variables under consideration
may be non-stationary, and some of the variables
may be cointegrated. In such cases we have to be especially careful when we apply tests for Granger causality. The reasons for this, and for adopting a modified testing procedure, such as that proposed by Toda and Yamamoto (1995), or that of
Dolado and Lütkepohl (1996) and Saikkonen and Lütkepohl (1996), are laid out in this
earlier post, and I won't repeat them here. I'll make the bold assumption that you've done your homework.
