Bounding Treatment Effects by Pooling Limited Information across Observations
Causal Inference in Case-Control Studies
[Experimental] Federated Partial Identification for Causal Inference with OMOP CDM
A unified Python framework for causal effect bounding algorithms
Estimating the Effect of Persuasion in Stata
Replication: Lee and Weidner (forthcoming, Journal of Econometrics)
Replication files for Jun and Lee (2022)
Unrefereed candidate on sharp partial identification of diversification histories, with executable replay and scoped assurance
Estimating the Effect of Persuasion in Stata
A new kind of world model: the PSD coupling kernel K(T,T') of admissible possible worlds. Diagonal = prediction, off-diagonal = counterfactual coupling. Built in public.
Python package for testing whether treatment effects operate through specific mechanisms, implementing finite-support sharp-null tests, minimum-defier bounds, and partial density diagnostics from Kwon and Roth (2026, Review of Economic Studies).
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