Leads and lags estimator for inference in cointegrated models (advanced)

This video explains how a 'leads and lags' estimator can be used to allow inference on cointegrated relationships. 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....

[@SeanByrneGuero303030]

Hi Ben, As an ABD finishing from off campus, it is incredible to have your videos available. They serve as great refreshers on other topics as well. It is great to watch videos on topics from an alternative interpretation, or i.e., a different take from how we were initially taught the same topics. Thanks so much for putting in all the energy to do such great work. Cheers, Sean

[@SpartacanUsuals]

Yes. That is what I mean. Thanks, Ben

[@mihaililiev5932]

Ben, it would be great if you make a video on cointegration in the context of VAR with matrix algebra

[@pamistry6408]

By "normal errors" do you mean errors which are distributed normally?

[@michaeljpchen6469]

Thank you so much for all the videos you have made. They are so helpful!

[@snakeflash3366]

great videos! could you make a video about VEC-Models, too?

[@SpartacanUsuals]

Hi, glad to hear that they were helpful. I have this topic as a to-do item on my list. Hopefully I will get round to doing it soon. Best, Ben

[@pavybez]

Great videos Ben. Thank you very much.

[@shenggenesis]

Hi Ben, I had a look at your online undergraduate econometrics course. It is amazing! I have two quick question, 1)in this videos, you mentioned that if not taking into account short-run dynamics, we need to use lead-lag model to draw interference on co-integration model. However, for some advance techiques you gonna introduce later, there are some model to combine short-run/long run dynamics, and we are able to draw interference directly using t statistics. However, I couldn't find such models you mentioned in your other videos. Could you please have me on this? 2)in the video of reverse causality, you didn't mention granger causality test? can't we just avoid this problem but running Granger causality test?