As we have learned in previous posts, that, causality defines the relationship between two variables. In this section, we will test the relationship between two unidirectional variable by using Granger causality test in Eviews and then we will study the interpretation of the output generated in Eview.
To investigate the causal relationship between two variables with the help of granger causality test eviews you need to follow below steps:
1. Open Eviews6.exe
2. Click on File -> Open -> Foreign Data as Workfile…
3. Open the data file “broadband_1 “ by selecting through the path C:\Program Files\SPSSInc\Statistics17\Samples\English
4. Select MARKET_1 and MARKET_2 -> OK
5. Click on Quick -> Group Statistics -> Ganger Causality Test
6. Write down the dependent variables followed by independent variables and then click OK:
7. Select lags to include = 2 and then click OK:
8. Following output will be displayed:
Two null hypotheses are being displayed in the above output.
If F ≥ 3.84 then H (A) (Alternate hypothesis is accepted)
If F < 3.84 then H (o) (Null hypothesis is accepted)
For the null hypothesis 1, in the above figure F ≥ 3.84, therefore Alternate hypothesis is going to be accepted which means MARKET_2 Causes MARKET_1.
Whereas, for the null hypothesis 2, in the above figure F < 3.84, therefore null hypothesis is going to be accepted which means MARKET_1 does not Causes MARKET_2.
Hence this proves that the above cause and effect relationship is unidirectional and not bidirectional.
For further details click here granger causality test eviews.
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View Comments
Brother where you get the value of 3.84. kindly explain.
3.84 is the criteria for F value to test which hypothesis is accepted. This is a globally verified criteria and this is how it is.
3.84 is the criteria for F value to test which hypothesis is accepted. This is a globally verified criteria and this is how it is.
Wow that was unusual. I just wrote an very long comment but after I clicked submit my comment didn't show up.
Grrrr... well I'm not writing all that over again.
Anyways, just wanted to say excellent blog!
Sound deep to me.
What is this method used for? I doubt the banks use it to analyze products or sales.
hmm nice
Sounds like a very complicated formula to understand. I tried but did not fully understand the model. I hope this works for you.
can we just use prob value for the decision rule? like 0.05 =reject the null
Great and detailed technical overview.
Yes. The P-values can serve the same purpose. You however notice that whenever the F is greater than or equal to 3.84, the P-value will also be less than or equal to 0.05. Thus both approaches yield same conclusions.
Great. Thanks