The Gauss-Markov Theorem proof - matrix form - part 3
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- Опубліковано 15 вер 2024
- This video is the last in a series of videos where we prove the Gauss-Markov Theorem, using the matrix formulation of econometrics. Check out ben-lambert.co... 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.co... Accompanying this series, there will be a book: www.amazon.co....
Wow! Thank you so much for a very thorough explanation of the GM theorem. You just made my Sunday night a whole lot better!
Hi, thanks for your comment. Glad to hear that the video was useful to you. Best, Ben
Really thank you so much for giving such precise and thorough explanation! Definitely did better than my lecturer!
Great job in explaining the G-M theorem. I read so many different proofs but I did not get it until I saw these videos.Excellent job. I am looking forward to your other videos
bro, understood this finally. Why are my profs soooo bad. Thank you very much.
Hi Thomas, Thank you for your message. Yes, it is my intention to continue moving through this syllabus. I will be covering endogeneity, IVs, ML and multinomial logistic regressions in the next few weeks. If you subscribe to me you should be notified when I put up new videos. Thanks, Ben
That is great. Thank you so much already. I will suggest your videos to all who are interested in advanced econometrics. Thomas
Awesome!
How would you show that a + d is a BLU Estimate of alpha + delta? Please do a video on this too!
Hi, I am Thomas from the TU Munich. Thank you for you great and clear videos. I am currently working through the "Econometric analysis" book by WH Greene an your videos really helped me to understand the first 2-3 chapters. Would it be possible, if you could also make some videos on e.g. Endogeneity, Instrumental variables, Maximum Likelihood estimation, or (multinomial) logit in matrix form. I and probably many other who struggle with matrix econometrics would be very thankful. Thomas
Sir, what is the meaning of scalar analog? How do you conclude that DD' is scalar analog just because X'AX is a positive scalar number , where A=DD' is positive semidefinitematrix.
you are a life saver....Thank you=)
Hi, I had a quick question. Why does Var(B~)>= Var(B LS) prove that B~ is the best estimator, or that there are no other linear unbiased estimators that have a lower sampling variance? Isn't it possible that another Beta estimator exists with variance that is even closer or equal to Var(B LS)? Is it ever possible to have a B~ with variance that is LESS than B LS?
Thank you!
***** Beta tilde is just an arbitrary unbiased linear estimator in that DX=0, and it is a linear combination of Y. This proof shows that B_LS is the best (lowest variance) unbiased linear estimator :)