Winter 2026 (in progress)

See our homepage for future talks.

• Tuesday, Jan 13, 2026: Zoom link (webinar ID: 968 8371 7451, password: 414559)  
  - Speaker: Yilin Song (Columbia University) & Richard Guo (University of Michigan)
  - Title: The Categorical Instrumental Variable Model: Characterization, Partial Identification, and Statistical Inference
  - Abstract: We study categorical instrumental variable (IV) models with instrument, treatment, and outcome taking finitely many values. We derive a simple closed-form characterization of the set of joint distributions of potential outcomes that are compatible with a given observed data distribution in terms of a set of inequalities. These inequalities unify several different IV models defined by versions of the independence and exclusion restriction assumptions and are shown to be non-redundant. Finally, given a set of linear functionals of the joint counterfactual distribution, such as pairwise average treatment effects, we construct confidence intervals with simultaneous finite-sample coverage, using a tail bound on the Kullback--Leibler divergence. We illustrate our method using data from the Minneapolis Domestic Violence Experiment.
  - Discussant: Desire Kedagni (University of North Carolina - Chapel Hill)
  [Slides][Paper][Video][Discussion slides]