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Want to include controls (X) in an IV analysis with binary treatment (W) and binary IV (Z)? DR LATE will cure all your ills! New WP with Tymon Słoczyński and Derya Uysal. Using IPWRA to estimate numerator and denominator works well. Can use teffects ipwra in Stata on each.

Do you use Difference-in-Differences methods? Have you ever wondered how selection into treatment relates to parallel trends? The role of unobservables? Dalia Ghanem, @wuthrich_k, and I are very excited to share our paper: arxiv.org/abs/2203.09001 1/n

Hi #Econtwitter! I am very excited to share my job market paper. We study the role of peer effects in LGBTQ coming out decisions using unique data from… Twitter. (1/18) LINK: jgromadzki.com/papers/Gromadz…

Hooray and congratulations!

I am so happy to see this out in the open! We are finalizing an R package to implement the test in more general cases, including staggered setups. So stay tuned!

I also recommend using methods that actually recover LATE (or LATT) when covariates are needed. Our (Tymon Słoczyński Derya Uysal) DR LATE (LATT) estimators are easy to compute and doubly robust. Let Doctor LATE cure your identification ills. 😬 arxiv.org/pdf/2208.01300…

New paper with Tymon Słoczyński and Derya Uysal! Not very long, but I think it's useful and elegant. Excited we have a working paper version. We study the Graham, Pinto, Egel (2012, REStud) and Imai and Ratkovic (2014, JRSS-B) propensity score estimates. arxiv.org/abs/2310.18563

📢 Check out the latest version of “Recovering Social Networks from Panel Data” with the brilliant Imran Rasul (UCL Economics) and Pedro CL Souza (Queen Mary University of London), just accepted at the The Review of Economic Studies! Here comes a 🧵on what we offer in this paper... 1/6 arxiv.org/abs/1910.07452

Yes!! Oriana is great, and you should interview her if she applies to your position.

The #SEA2023 in NOLA is just around the corner! And we ( Yuya Sasaki, Tymon Słoczyński, and I) have put together several sections on "practical econometrics" that I hope you will enjoy! Let me describe the sessions a little bit so you get the flavor.

Are you using DiD to learn about something *continuous*? If so, then new DiD tools for binary designs don’t seem to help much. But here is something that will help! An update to “DiD with a Continuous Treatment” w/ professional age forecaster and Brant Callaway: psantanna.com/files/CGBS.pdf

Always try to be "sharp". Please check our recent pub, with my amazing co-authors Lixiong Li (JHU), and Desire Kedagni UNC Economics.

This was a super fun paper to work on! I highly recommend it if you are looking for alternatives to 2SLS in LATE estimation.

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I think the most commonly used treatment effect estimators when treatment, D, is unconfounded conditional on X, are the following: 1. Regression adjustment. 2. Inverse probability (propensity score) weighting. 3. Augmented IPW. 4. IPWRA 5. Covariate matching. 6. PS matching.

This paper has been in the making for so long that eight children across the co-author group were born between the time we started and now! But it is finally out, and you can check it at arxiv.org/pdf/2503.13323