Ah, thank you!

Thank you for putting this list together; I hope this response isn't too late for me to be added to the list.

Brad Ross (Stanford GSB) - Measuring and Mitigating Traffic Externalities - brad-ross.github.io

Definitely in the top echelon, especially this version

Would it not be GLS for efficiency reasons at least?

Thank you for the kind words!

Thank you so much! This project really was a team effort and wouldn’t have happened without @lihualei.bsky.social, who presented the paper when you saw it and is such a wonderful coauthor and mentor! I’ve learned so much from him.

I’m so sorry Andrew—may her memory continue to be a blessing to you

As an end-of-alphabeter, I would appreciate an alternative to et al., but unfortunately it’s not clear this is the right one from a paper recognition perspective, although it’s better than numbered citations…

Not sure they have a package yet, but this awesome paper by Dorn, Guo, and Kallus suggests a “doubly robust” sensitivity analysis under the same Marginal Sensitivity Model as Zhao et al with some very neat properties: arxiv.org/abs/2112.11449

So glad the feet have stuck

One of my absolute favorites!

I initially read this as “good biology science writing” and got very confused lol