(EViews10):VAR and 4-Ways Causality Checks(1)

[@CrunchEconometrix]

KZbin recently changed the way my content will be monetised. My channel now needs 1,000 subscribers. So it would be amazing if you show your support by both watching my videos and subscribing to my channel if you haven’t done so already. Monetising my videos allows me to invest back into the channel with some new equipment so this small gesture from you will be extremely huge for me. Many thanks for your support….CrunchEconometrix loves to teach, help me stay online.

[@Ajitop_Ceo]

i added your name to my project acknowledgement because if not for your video i would not been able to do my analysis myself.. thanks ma i wish i can meet you one on one

[@CrunchEconometrix]

Thanks, Ajitop Media. I find your comment encouraging and heart-warming. Gracias! 🙏

[@dinobrown5956]

Thanks for providing all the ways for causality checks. Good step by step explanation

[@CrunchEconometrix]

U're welcome, Dino...may I know from where (location) you are reaching me?

[@dinobrown5956]

From India.

[@CrunchEconometrix]

@@dinobrown5956 Awesome! Please spread the word about my videos...thanks!

[@baneledludlu7983]

mam you're the best...thank you for your explainations

[@CrunchEconometrix]

Thanks for the encouragement, Banele. Deeply appreciated!

[@mishalkhaled8327]

GREAT ONE THANKS ALOT#

[@CrunchEconometrix]

You are welcome, Jasem!

[@anandarajsaha8697]

Maam nice explanation. Detailed and point to point analysis will help the beginners to understand the idea...

[@CrunchEconometrix]

Thanks Prof, always humbled by your encouraging words. Hope you're doing ok. Kindly tell your students and colleagues about my channel. They can learn difficult stuffs in a very simple way. My aim is to turn rookies to pros of econometrics (lol)

[@mohammedarmah9035]

Tnank you

[@CrunchEconometrix]

U're welcome, Mohd.

[@mohammedarmah9035]

Hello Once again l like the good work you are doing. Please after you finish performing your casualty test and you went ahead to perform the diagnostic test. The results indicate that there is serial correlation in the model you use. what is implication your results in the casualty test result?

[@CrunchEconometrix]

Re-estimate the model at higher-order lags.

[@mohammedarmah9035]

@@CrunchEconometrix Thank you

[@chanchalsaini9655]

mam ,for applying granger causality it is necessary variables are stationary at 1 st difference or we can apply causality test for any order stationery variable??

[@CrunchEconometrix]

Hi Chantal, if you watched this video you will see what procedures I undertook. Thanks.

[@itiverma9098]

Hello ma'am, I have a question.. As you discussed in your previous videos about the techniques which we can use when series are integrated at order 1. So firstly after checking the stationarity we performed cointegration test and if series are cointegrated then we perform vecm but if ECT is not significant and negative which is desirable to achieve then we fails to interpret long run causality . Thereafter should we apply var ????

[@CrunchEconometrix]

Hi Iti, don't get me wrong. You perform VAR only when there is no cointegration. But if the ECT turned out to be statistically insignificant, you can decide to revert to the VAR model.