Introduction to Instrumental Variables (IV)

preview_player
Показать описание
MIT's Josh Angrist introduces one of econometrics most powerful tools: instrumental variables.

Instrumental variables (IV, for those in the know), allow masters of econometrics to draw convincing causal conclusions when a treatment of interest is incompletely or imperfectly randomized.

For example, arguments over American school quality often run hot, boiling over with selection bias. See a school with strong graduation rates and enticing test scores? Is that a good school or just an ordinary school fortuitously located in a good neighborhood?

Lotteries that randomize offers of a school seat at in-demand schools should unravel the school quality conundrum. But lotteries only offer seats. Families are free to accept or go elsewhere and these choices are far from random.

IV provides a path to causal conclusions even in the face of this sort of incomplete randomization.

In this video, we cover the following:

- Incomplete random assignment

- IV terminology: first stage, second stage, instrument, reduced form

- Three key IV assumptions: substantial first stage, independence assumption, exclusion restriction

***INSTRUCTOR RESOURCES***

***MORE LEARNING***
Рекомендации по теме
Комментарии
Автор

I had to comment. This is more clearly presented and understandable than I ever would have imagined. I am taking a 4000 level econometrics course and the professor couldn't explain it this eloquently. Fantastic job!

brayanlondono_
Автор

Incredibly well done! Thank you for putting this together - it was so clear, easy to follow, and engaging. I wish all instruction was done like this. Really love and appreciate your educational approach - it makes such a difference!

lilsleekstallion
Автор

waiting for more to come! this is greatly illustrative!

smyumyu
Автор

I can't tell how badly and desperately I was waiting for this video since I had completed the previous ones already !
Thank

chalantika
Автор

This is actually a better refresher after a few years away from econometrics than any textbook or other video I’ve tried watching. Anyone can plug and play equations, really understanding what drives causality is much more difficult to explain and y’all killed it, cheers👌🏻

austinlentsch
Автор

Thanks a lof for making lessons so entertaining and clear, I wished I had them back when I was at University... I can't wait to watch the next ones!

raulfernandez
Автор

Finally back!!! I was waiting for it as it was my fav series on Netflix 😃

ibrahimisrafilov
Автор

This is a very good explanation of this concept. I am masters student and have had 3 professors who have not explained this concept as beautifully as this video. Thank you so much for this video

foxhyde
Автор

Love the animation style, like archer, and the fact that I’m also learning econometrics is just the best

bababouibababoui
Автор

What an astonishingly engaging, clear and succinct summary, thank you!

cmmissar
Автор

At long last! Another econometrics video!

freedman
Автор

Well said!!! Unfortunatelly, journalists don't know econometrics and they reach all the aforementioned inferences (the wrong ones)...

PatapiaPapakalodouka
Автор

I love this series! Just wished there were more episodes!!

linhdanxauxi
Автор

Awesome, sadly i already finished my studies but I am learning for life here now!

alexfrank
Автор

These videos are so helpful! When are the other parts going to be released?? Looking forward to the regression analysis video!

lavacake
Автор

I don't usually comment, but I randomly stumbled across this video as I'm covering it in class. The examples immediately seemed familiar and that's because I'm using your textbook too! Just a recommendation to anyone watching this that the textbook is great as well

vilhelmjuhler
Автор

This is the sixth video in our Mastering Econometrics course.

MarginalRevolutionUniversity
Автор

Great lessons! Will more videos in the series be published soon?

vascoamaralgrilo
Автор

That's a great video but when part 2 coming?

appex
Автор

You beautiful human being. Thank you for this video

Stella-yrcu