Brad Ross
@bradross.bsky.social
If you want hands-on experience working on applied economics research with a group of fantastic mentors, you should definitely apply--I'll be joining the department next summer and would love to work with you!
🚨 undergrads and masters students interested in careers in applied econ research:
My department is recruiting 4-5 full-time RAs to start summer 2026. See the announcement here for more details: jessiehandbury.com/misc/RAflyer...
A few reasons you should apply...
My department is recruiting 4-5 full-time RAs to start summer 2026. See the announcement here for more details: jessiehandbury.com/misc/RAflyer...
A few reasons you should apply...
jessiehandbury.com
October 14, 2025 at 3:44 PM
If you want hands-on experience working on applied economics research with a group of fantastic mentors, you should definitely apply--I'll be joining the department next summer and would love to work with you!
This paper provides a really nice way of justifying why synthetic controls “work well” at predicting counterfactual post-treatment outcomes.
Large-Sample Properties of the Synthetic Control Method under Selection on Unobservables http://arxiv.org/abs/2311.13575 We analyze the properties of the synthetic control (SC) method in settings with a large number of units. We assume that the selection into treatment is based on unobserved perm 📈🤖
November 23, 2023 at 5:55 AM
This paper provides a really nice way of justifying why synthetic controls “work well” at predicting counterfactual post-treatment outcomes.
Another very cool paper by wonderful people!
Causal clustering: design of cluster experiments under network interference http://arxiv.org/abs/2310.14983 This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of spillovers on a single network. We provide an econometric framework to choose 📈🤖
October 24, 2023 at 2:10 PM
Another very cool paper by wonderful people!
A very clever paper on partial ID by some very cool people!
Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects
http://arxiv.org/abs/2310.08115
Many causal estimands are only partially identifiable since they depend on
the unobservable joint distribution between potential outcomes. Stratification
on pretreatment covariates c
📈🤖
http://arxiv.org/abs/2310.08115
Many causal estimands are only partially identifiable since they depend on
the unobservable joint distribution between potential outcomes. Stratification
on pretreatment covariates c
📈🤖
October 14, 2023 at 2:14 AM
A very clever paper on partial ID by some very cool people!