Fixed Effects estimators: an introduction
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- Опубликовано: 14 янв 2014
- This video explains the motivation, and mechanics behind Fixed Effects estimators in panel econometrics.
Check out oxbridge-tutor.co.uk/undergrad... for course materials, and information regarding updates on each of the courses. Check out ben-lambert.com/econometrics-... for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: ben-lambert.com/bayesian/ Accompanying this series, there will be a book: www.amazon.co.uk/gp/product/1... 
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Ben seriously thank you for all your videos, you have made Econometrics infinitely more palatable for me.
I am glad that there are people like you out there Ben! People that transform something unappealing into an easy and understandable model with good structure. For sure there isn't everything someone can know about the topic in each video but it has great introduction and intuition. Thanks for all the help!
Great video! I really appreciate that you go through the mathematical aspects of this relatively thoroughly. Thank you.
Hi, glad to hear it was helpful. Best, Ben
Perfect introduction. I am preparing for an exam in statistics and this helps just great.
God bless you.I had spent 3 entire days on this without a conclusion. You illuminated me in just 7 minutes.
Ben u are a legend, I'm gonna go full steam and be ahead of everyone else in my class
To clear some confusion. Weak exogeneity (+ no collinearity and linearity) is enough to show an OLS estimator is consistent. But to show OLS is unbiased we NEED the strict exogeneity assumption. Check chapter 11, page 385 of intro to econometrics by Woolridge.
Amazing Ben. You're so amazing.
I love your videos so much! :)
Hi Ben, do you have any videos explaining how to do an F -test and explaining the degrees of freedom on a FE estimator?
Thank you sir, very clear!
Very nice Video!! Could you help me using Fixed-effects model on a case where we want to measure if board independence has an effect on firm performance? Do I also need to refer to time? How is the equation then? Thanks a lot! Thank you so much!
Hey great video I have watched the other ones too. I am working on a paper and as far as I´m concerned FE is used to determine unobservable effects of mothers. They say mothers differ in observable and unobservable ways. What could it mean when it says Mother fixed effects? Are they basically comparing mothers that have the same traits (as of the questionaire) and comparing the outcome of this group?
why doesn't alpha i vary across time?
Can you please explain me the difference in Fixed effect estimator and first differencing estimator?
Hi Ben,
Great video! Just a small question: Don't we need strict exogeneity here to establish consistency? Because after we demean the data the error term became (miu - miu bar), and miu bar contains all the error terms, which means we need all the error terms to be uncorrelated to all the HPs to achieve consistency in OLS estimates right?
I agree with you
I agree also.
Thanks for saving my degree
You explain in less than 8 minutes what a professor could not explain in 2 hours
you are godlike
Where does the error term in the lastequationn go? Does it convert into u tilda?
is there no constant term in fixed effects model?
It gets absorbed into the time-invariant parameter
@@jaspalchanna4025 But it was not even present in the first model, where we should have added it in theory - to make it consistent with the previous videos, or not?
I might be wrong, but Fixed Effects model does require strong exogeneity assumption, not the weak, or am I wrong?
at 5:40 - strong we need for unbiasedness, but in large samples the weak is enough.
I did not get the condition to be UNBIASED he briefly mentioned...Would it be the covariance between Xit and Uis? What does it mean?
So what will the Beta represent in this case? The change in the difference from the mean with respect to the change in the difference of either covariate? So is this a measure of how certain factors will disrupt an outcome away from it's time trend?
Thanks for the videos!
Hello! Did you ever figure this out? What I find online is that the interpretation is typical OLS marginal effects, but what you said has always made more sense to me
@@gahbor Hey, I have the same question. Has anyone managed to make sense of this yet? Thanks!
why there's not a constant term?
Why is there no beta0 in the model?
Nice video with clear explaination, 1 subscribe from me :)
5:20 why does he say "pooled OLS estimates"?
Good point, fixed effects are used for panel data, not pooled ols, unless I may have missed something
i love you .. i mean, you're lovely !