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Thanks for the reply mate. And you're totally right, the number of observation is definitely what messing me up here.

Come on guys, any idea?

You could run a Granger test before estimating your VAR, to see if any of your variables actually statically causes any other. The Granger test is also used once you have estimated your VAR to determinate the exogeneity order of your variables, if you're interested in analyzing your model's dynamics.

Good question. First, I think there's no point in differentiating the stationary variable for the Granger test, it should be fine as it is. Second, running a Granger on both stationary variables (one is I(0) and the other I(1)) should give the same results whether or not you estimate a VAR before.

It's not possible. First you've got to run a cointegration test on your stationary variables and a condition to run that test is that your stationary variables are integrated of the same order, otherwise there is no cointegration risk whatsoever. No cointegration, no VECM.

Dear all i have done ADF test and my variables are stationary in the first difference but some are stationary at 1%, some at 5% and some at 10%..they are stationary in the first difference but not at same percentage..but also a little further problem, at the first difference, there are 2 variables ...

Hi guys, First time poster here. I need your help with a VAR that I'm trying to estimate using Eviews. Basically, I have 4 series that I'm trying to estimate a VAR with. 3 out of my 4 series have seasonality though, and I'm not sure whether I should adjust seasonality before estimating my VAR or not...