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VAR can be applied only if the input series are stationary otherwise VAR may result in spurious correlation. So just evade it. Now the solution to treat the non stationary series to go for cointegrated series (ca.jo test) and if cointegration is viable then build VECM (Vector Error Correction Mechanism). This incorporate the short and long run relationship ...


The test fails to reject the null hypothesis of no cointegration since the p-value for r0 is greater than 0.10, and, instead, it rejects the null hypothesis of 1° rank cointegration r1 at 5.0 % level of significance (since the p-value is 4.01 %). So, looking at the test results, the series is not cointegrated, although I suggest to check for higher ranks ...

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