Dear Dr.Giles! Thank you for your precious time you spare for sharing your experiences and disseminating the knowledge about various issues in Econometrics. Dr. David! if some of the data on variables are I(1), some is I(0) and some is I(2) , and the aim is to investigate the causality , then what do you suggest in such a case. Which technique is best suitable either VAR, VECM, ARDL, OR TY etc. Please guide me in this regard. Appreciated if you could support the answer step by step with Eviews work-files. I also request you that to write some blogs on forecasting techniques in E-views too. Thanks in advance.
and so you should!
ReplyDeleteThanks!
DeleteDear Dr.Giles! Thank you for your precious time you spare for sharing your experiences and disseminating the knowledge about various issues in Econometrics.
ReplyDeleteDr. David! if some of the data on variables are I(1), some is I(0) and some is I(2) , and the aim is to investigate the causality , then what do you suggest in such a case. Which technique is best suitable either VAR, VECM, ARDL, OR TY etc.
Please guide me in this regard. Appreciated if you could support the answer step by step with Eviews work-files.
I also request you that to write some blogs on forecasting techniques in E-views too.
Thanks in advance.
In this case you should use TY. You can't use ARDL if any of the data are I(2).
Delete