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

<p>In your case, the direction of the Granger causality is the following:</p>

<p>$DRS \rightarrow DLRGDP$</p>

<p>$DRS \rightarrow DLRM2$</p>

<p>$DLRGDP \rightarrow DRS$</p>

<p>$DLRM2 \rightarrow DRS$</p>

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

CC BY-SA 3.0
2016-07-17T13:21:30.917Z
2016-07-17T13:21:30.917Z
Übel Yildmar
<p>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).</p>

<p>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.</p>

CC BY-SA 3.0
2016-07-14T20:11:55.733Z
2017-02-23T14:14:02.787Z
2017-02-23T14:14:02.787Z
DiogoLespagnol
<p>I have run a VAR model, and done granger causality tests (results pasted below) and am trying to answer a textbook question which asks:</p>

<p>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?</p>

<p><a href="https://i.sstatic.net/HLosq.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/HLosq.jpg" alt="enter image description here"></a></p>

<p>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.</p>

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

<macroeconomics><econometrics><time-series>
VAR Models - Identifying Block Exogenous Variables Through Granger Tests
Adrian_P
# VAR Models - Identifying Block Exogenous Variables Through Granger Tests

(Asked by: username_0 on 2016-07-14)

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?

[![enter image description here](https://i.sstatic.net/HLosq.jpg)](https://i.sstatic.net/HLosq.jpg)

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?

**Tags:** macroeconomics, econometrics, time-series


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## 2 answers

### Answer by username_1 on 2016-07-17. Score: 1

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.


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### Answer by username_2 on 2016-07-14. Score: 1

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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