FAQ
Dear Community,

I am new to R and have a question concerning the causality () test in
the vars package. I need to test whether, say, the variable y Granger
causes the variable x, given z as a control variable.

I estimated the VAR model as follows: >model<-VAR(cbind(x,y,z),p=2)

Then I did the following: >causality(model, cause="y"). I thing this
tests the Granger causality of y on the vector (x,z), though. How can
I implement the test for y causing x controlled for z? Thus, the
F-test comparing the two models M1:x~lagged(x)+lagged(z) and
M2:x~lagged(x)+lagged(y)+lagged(z)?

Best Regards

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•  at Apr 5, 2011 at 8:11 am ⇧
The below email was cross-posted to R-Sig-Finance and has been answered there.
-----Urspr?ngliche Nachricht-----
Von: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] Im Auftrag von ivan
Gesendet: Montag, 4. April 2011 20:24
An: r-help at r-project.org
Betreff: [R] Granger Causality in a VAR Model

Dear Community,

I am new to R and have a question concerning the causality ()
test in the vars package. I need to test whether, say, the
variable y Granger causes the variable x, given z as a
control variable.

I estimated the VAR model as follows: >model<-VAR(cbind(x,y,z),p=2)

Then I did the following: >causality(model, cause="y"). I
thing this tests the Granger causality of y on the vector
(x,z), though. How can I implement the test for y causing x
controlled for z? Thus, the F-test comparing the two models
M1:x~lagged(x)+lagged(z) and M2:x~lagged(x)+lagged(y)+lagged(z)?

Best Regards

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and provide commented, minimal, self-contained, reproducible code.
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