# VAR for Non Stationary series using R

Are there any suggested approaches for using non-stationary series in a VAR model? As per otexts.org:

If the series are non-stationary we take differences to make them stationary and then we fit a VAR model (known as a “VAR in differences”).

Are there any other approaches for creating a forecasting model non-stationary series in a multivariate series?

Any leads on this would be helpful. I'm looking for implementing this model in R.

• Either a VAR in first differences or a vector error correction model (VECM) depending on whether your series are cointegrated. See e.g. this which is a more general case, but easy to simplify. See also this for a general cookbook approach to VAR modelling. – Richard Hardy Feb 14 '17 at 15:18
• Thanks a lot for the information provided. The only way to identify stationarity of var is to check the stationarity of constituent variables? – Lal Prasad R Feb 15 '17 at 4:48
• Yes, that's right. – Richard Hardy Feb 16 '17 at 17:54
• @LalPrasadR you DON'T need to first difference data to forecast with VAR (sorry this is one of my pet pervs)!!! Read my post here: stats.stackexchange.com/questions/191851/… – Jacob H Jan 7 at 19:07