Thanks for this brilliant video Mike! You explain things in a super clear way and it is easy to understand. It helped me a lot with my model specification in my PhD dissertation.
Dear Mike Jonas, thank you so much for your useful video. I have one question: how to calculate multicollinearity by using multinomial regression? Stay safe and healthy!
Thank you so much for this lesson. It was really helpful. I was wondering what might be the options to check for multicollinearity when our explanatory variables are both categorical and numerical; and that we would want to check the multicollinearity between categorical variables, as well as between categorical and numerical variables. Thank you.
Hello Steven - the VIF tells us the multiple by which the coefficient variance is increased due to multicollinearity among independent variables. For example, if the VIF=5, then the variance is 5 times larger than it otherwise would be. This is technically not a 'test' in that there is no critical value. It is suggested that a value of 5 or higher is "problematic", but since MC does not cause bias, it is only a concern if it makes otherwise significant coefficients appear insignificant.
Thank you very much sir! Excellent and simple explanation! Keep it this way!
Thanks for this brilliant video Mike! You explain things in a super clear way and it is easy to understand. It helped me a lot with my model specification in my PhD dissertation.
Great to hear and you are very welcome. Congrats on the dissertation being completed!
Dear Mike Jonas, thank you so much for your useful video. I have one question: how to calculate multicollinearity by using multinomial regression?
Stay safe and healthy!
Thank you so much for this lesson. It was really helpful. I was wondering what might be the options to check for multicollinearity when our explanatory variables are both categorical and numerical; and that we would want to check the multicollinearity between categorical variables, as well as between categorical and numerical variables. Thank you.
I've been wondering as well. Please advise if you have found the answer
I learnt a lot and need more on dummy
(categorical variables) variables how to generate, replace in stata
Thank you Mike for the Multicollinearity explanation. In you model, R-square is around 5%, how do you interpret the same? how to improve R-square?
Hi, please is it possible to run a cross-sectional comparative analysis on STATA with only data for 4 years?
Thank you so much
Hello Mike, how do now interpret the result of the VIF test? Thanks!!
Hello Steven - the VIF tells us the multiple by which the coefficient variance is increased due to multicollinearity among independent variables. For example, if the VIF=5, then the variance is 5 times larger than it otherwise would be. This is technically not a 'test' in that there is no critical value. It is suggested that a value of 5 or higher is "problematic", but since MC does not cause bias, it is only a concern if it makes otherwise significant coefficients appear insignificant.
@@mikejonaseconometrics1886 Thank you so much! This so helpful.