Mam really your explanation is very nice ..... simple and clear..... I just want to ask mam what is source of your motivation ... which miracle is working behind your teaching skill ...
Dear Maam, Why vif command shows "not appropriate after regress, nocons; use option uncentered to get uncentered VIF" beacuse of running any model other than OLS? I run fixed effect model, then write vif command. Then stata shows not appropriate result.
prof my model is pased the multicol by VIF, but after hausman test the selected is fixed effect, do i have to recheck the Multicol after fixed effect regression by doing VIF uncentered? because the result is different thanku syukriyaa
Hi, I checked unit root test and found that some of the variablws are stationary at first and second difference. So in that case when I enter the variables in the command section, should I enter them taking their difference. Thanks
@@komalkanwarshekhawat_ waiting for that video mam it will be really helpful to all the research Scholars. And please tell how to interpret the results of both the GMM models
Your teaching is prefect mam
🙏🙏
Lectures are very interesting and knowledgefull .The way of teaching is outstanding 🥰🤩👍👍
Thank you dear....keep learning 🤗🤗
Thank u dear for such a knowledgeable video
Thanks for your kind words 😊
Mam really your explanation is very nice ..... simple and clear.....
I just want to ask mam what is source of your motivation ... which miracle is working behind your teaching skill ...
Thanks a bunch dear.... Consistency and blessings of well wishers like you are the support system ❤️
@@komalkanwarshekhawat_ 😊😊
Your way of teaching is really very attractive 😊. Keep it up 👍.
Thank you Gagan 😊🤗
Dear Maam,
Why vif command shows "not appropriate after regress, nocons; use option uncentered to get uncentered VIF" beacuse of running any model other than OLS?
I run fixed effect model, then write vif command. Then stata shows not appropriate result.
Check VIF after running the OLS. That is run the regress command and then run the vif command.
fabulous ma'am ,🤩🌸
Thank you Pooja 🤗
i couldn't use the vif in fixed effect panel data multiple regression ? how can i do so ?
You can check VIF individually also.
hlo mam, n you please tell me when to use uncensored vif or censored vif value for calculation of multicollinearity in the stata
To identify the presence of Multicollinearity see censored VIF. However, stata provides with only VIF and 1/VIF values.
@@komalkanwarshekhawat_
Why you have taken log variable in your data set ...
prof my model is pased the multicol by VIF,
but after hausman test the selected is fixed effect, do i have to recheck the Multicol after fixed effect regression by doing VIF uncentered?
because the result is different
thanku syukriyaa
No need to check again. Just mention the VIF values obtained under the said model.
Komal you video is am,azing, however, it was not clear for me which values represent high or low multiocolinearity
Dear, kindly let me know at what level you faced difficulty.
Mam, What about Multicollinearity in case of Dichotomous variables (or with more than two categories) ?
I hope you will find this article helpful.
www.researchgate.net/post/How_to_test_multicollinearity_in_binary_logistic_logistic_regression
Hi, I checked unit root test and found that some of the variablws are stationary at first and second difference. So in that case when I enter the variables in the command section, should I enter them taking their difference. Thanks
No, not necessary.
@@komalkanwarshekhawat_ Thank you so much. Also, I run the fe model in both stata and eviews, but I get different results 😓
Best one
Thank you 😊
Mam kindly upload a video using stata on how to choose between System GMM and Difference GMM method
Sure, will soon upload on this one also. In list already. Thanks.
@@komalkanwarshekhawat_ waiting for that video mam it will be really helpful to all the research Scholars. And please tell how to interpret the results of both the GMM models
thank you so much mem
Your welcome 😊
Thank you
Grateful 💫
👍👍
🤗🤗
thank sir
👌👌👍
😊🤗
🙏🙏
🤗🤗