I have run a VAR model, and done granger causality tests (results pasted below) and am trying to answer a textbook question which asks:

Is there any variable that appears to be close to being block exogenous with respect to the other variables? In any case, what does this mean?

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To me it seems like DLRGDP is the closest. Exogenous means that one variable is not affected by changes in the other variables The p-values on the DLRGDP seem to indicate that we cannot reject the null hypothesis that DLRM2 does not granger cause DLRGDP. But the p-value that DRS granger causes DLRM2 is fairly low, at 0.0025.

What do you think, are any of these variables close to being block exogenous?


2 Answers 2


A variable is block exogenous, if it does not Granger cause ANY other variables of the VAR model.

In your case, the direction of the Granger causality is the following:

$DRS \rightarrow DLRGDP$

$DRS \rightarrow DLRM2$

$DLRGDP \rightarrow DRS$

$DLRM2 \rightarrow DRS$

As you can see, every variable Granger cause at least one other variable. There's no block exogeneity in your VAR model.


Checking the p-values, I would suggest that in the first and second tests, the variables DRLM2 and DlRGDP have granger causality issues (since we reject for a 5% sig. level).

In the third case, DRLM2 is not rejected for a sig. level of 5%, yet, it seems to be very close (4,8%). I don't think there's any particular meaning to having a near non-rejection area. Remember that if you draw the chi-square distribution and use the 1% sig. level for the test, you will not reject the granger causality.


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