Dear all, I would really appreciate if someone could explain me why does Ben include SAT variable in estimating CA in first stage of 2SLS. Aren't distance and quality of public transportation enough to estimate CA. Thanks
Yeah... why does he include SAT in CA? Would you get highly correlated estimates in the new regression? i.e. beta1 and beta2 being highly correlated...
Filip Popovic I have been wondering the same thing. I think it may have something to do with the fact we have already established/assumed it has a 0 covariance with the error term in which case it is beneficial to include in the first stage of regression.
it is a significant variable for the data generation process of scores. That reflects previous knowledge and background of some particular topic. even tough attendance for some particular students is zero; then scores would be influenced by IQ or any other training in the past.
If you regress CA on SAT and IVs and find out that the coefficient of SAT is significant, isn't that suggesting multicollinearity which should have been avoided?
Yes, I am wondering too. Can anyone explain why include SAT in both first and second stage? I think in the second stage, CA hat and SAT will have multicolinearity problem.
That explanation at the end was money. Definitely going to help me w/ my econometrics final this Sat!
Ben, brother, you are saving my life right now
This belongs in a museum
You explain the concept so clearly! Thx a lot!
Thanks. great ideas are explained with simple words, perfect!
Thank you very much, Ben!
Thanks a lot. This is going to help me a lot in my current thesis.
Thks grand Prof.
Thank you so much for your work.Helped a lot :)
thanks love your videos
Dear all,
I would really appreciate if someone could explain me why does Ben include SAT variable in estimating CA in first stage of 2SLS. Aren't distance and quality of public transportation enough to estimate CA.
Thanks
Yeah... why does he include SAT in CA? Would you get highly correlated estimates in the new regression? i.e. beta1 and beta2 being highly correlated...
I also would like to know this
Filip Popovic I have been wondering the same thing. I think it may have something to do with the fact we have already established/assumed it has a 0 covariance with the error term in which case it is beneficial to include in the first stage of regression.
it is a significant variable for the data generation process of scores. That reflects previous knowledge and background of some particular topic. even tough attendance for some particular students is zero; then scores would be influenced by IQ or any other training in the past.
This is sooooo good an explanation!!
If you regress CA on SAT and IVs and find out that the coefficient of SAT is significant, isn't that suggesting multicollinearity which should have been avoided?
+Yuchen Li Yeah that's what i was wondering to, why SAT is included in the first-stage
Yes, I am wondering too. Can anyone explain why include SAT in both first and second stage? I think in the second stage, CA hat and SAT will have multicolinearity problem.
But how can we know INTEREST is in the error term, what if DISTANCE, PTRANS are also in the error term?
Very Helpful, thank you very much !!
Wow when you say "Exogenous " contra "Endogenous", they sound really familiar.
Thanks very much. It helped
hi! can you use the lagged value of the endogenous variable as an instrument using 2SLS model
Also interested to know
Thanks, very helpful
Thank you
You rock dude!!
awesome