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(Stata13):Multicollinearity Explained
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- Опубліковано 17 сер 2024
- Multicollinearity occurs when there exists perfect or exact linear dependence or relationships between two explanatory variables or among explanatory variables in a given model. It has the potential of adversely affecting regression coefficients. It affects the regression beta weights, standard errors and the corresponding statistical significance levels associated with them. You can identify the presence of multicollinearity if you observe any of the following: R-squared will be high, beta coefficients will not be statistically significant, beta coefficients will be contrary to expected a priori or bizarre, large standard errors, small t-statistics, more likely not to reject the null hypothesis, removing or adding a regressor causes substantial changes to the model, and more often than not, the model breaks down. This video explains multicollinearity and how to correct it.
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Great and very helpful to capture within a short time! You're more than expert
Thanks for the encouraging feedback, deeply appreciated 🙏🥰
God bless.
Thank you, Professor!
You are very welcome, Burham!
Thanks Professor. You made a clear explanation.
Compliment is humbly taken, Emma!
Dear CrunchEconometrix. Thank you for your useful video. I have one question: How to calculate Multicollinearity by using multinominal regression? Stay safe and healthy!
Best,
Lanh Nguyen
Unfortunately I have no idea. Perhaps, you may get some hints from the internet.
@@CrunchEconometrix thank for your reply. Stay healthy!
Thank you very much for this tutorial. I would like to ask you question please. How can I check multicollinearity in panel data model?
Hi Aiboud, same way I showed in this video.
Thank you. I would like to know how to check for VIF as an expost test of multicolinearity for System GMM estimation.
First estimate a pooled OLS then VIF. That is:
reg y x1 x2 x3
vif
More power to your elbow... Good job
Thanks for the encouragement Popoola, hope you got something from there. Subscribe for more simplified tutorials from CrunchEconomterix...and share the love (likes) too :), tell colleagues, students etc
Nice job.
Hi, Mohd. I'm encouraged and humbled by your feedback. May God bless you. Please may I know from where (location) you are reaching me?
@@CrunchEconometrix Japan
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@@CrunchEconometrix Of course.
This video will be useful for me but but can't solve the Multicollinearity problem. before starting analysis process, I have already converted my full raw data into natural log. But still it indicates the same problem. Madam, in this situation what I will do?
You didn't pay attention to the suggestions made in the video. DO NOT PUT HIGHLY COLLINEAR variables together in the same model. Kindly watch the video again. Thanks.
But if others have used those variables and the variables are important for the study..then what to do in that case
You may need to look up other online resources about this.
Mam can we log transform the variables of different units.For instance,if FDI is in billions and other variables is in crores,then can I transform all the variables in log or do I have to first transform the FDI in crores??
Plz reply mam
Ride on sis.
Adebayo Ogundare... Thanks bro, help make my channel go viral!👊🏾
How can I export a VIF table?
Hi DonMorloc, I'm not aware of any export command for that.
Thank you very much for this tutorial. I would like to ask you question please. How can I check multicollinearity in a probit model?
Hi Mona, same guide as expressed in this clip.