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Bibliographic Details
Main Authors: Song, Yilin, Guo, F. Richard, Chan, K. C. Gary, Richardson, Thomas S.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.09510
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Table of Contents:
  • 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.