Hi,
I have some questions relating the causality test. After I did the Engle-Granger cointegration part, I found that most of them are co-integrated. As far as I know, the standard Granger-causality test is invalid and a more comprehensive test of causality based on ECM, am I right?
If that is the case, I want to ask how can I estimate an ECM in Eviews? And then I have to perform a causality test via "view - lag structure - granger causality/block exogeneity test?
Thanks a lot
Causality test with cointegrated series
Moderators: EViews Gareth, EViews Moderator
Re: Causality test with cointegrated series
How Do I apply Panel data causality testing using Eviews7 ? Thanks
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Re: Causality test with cointegrated series
hi terran 190,
i don't really get your question: at first you say, you have done the Engle-Granger cointegration part, then you ask how to estimate an ECM in EViews - so, what have you done actually?
If you mean you've done the Johansen Cointegration test, then, in the test result window, click on "estimate", specify the various tabs in the "VAR specification" window according to your results and click OK. What you'll get is the estimate of your ECM "Vector Error Correction Estimates".
As far as I know, the Granger Causality tests Eviews carries out proceeding from that window ("Vector Error Correction Estimates"> view > lag structure > granger causality) is valid.
Good luck!
Kerstin
i don't really get your question: at first you say, you have done the Engle-Granger cointegration part, then you ask how to estimate an ECM in EViews - so, what have you done actually?
If you mean you've done the Johansen Cointegration test, then, in the test result window, click on "estimate", specify the various tabs in the "VAR specification" window according to your results and click OK. What you'll get is the estimate of your ECM "Vector Error Correction Estimates".
As far as I know, the Granger Causality tests Eviews carries out proceeding from that window ("Vector Error Correction Estimates"> view > lag structure > granger causality) is valid.
Good luck!
Kerstin
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