partial-identification

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

R package for regression sensitivity analysis to omitted variable bias: identified sets and breakdown points following Diegert, Masten & Poirier (2026) and Oster (2019).

What competitive H/T and D/T kinetics identifies about enzymatic hydrogen transfer: data, code and verification suite

Cross-asset price impact is set-identified, not point-identified: the confounding gap has rank at most K + rank(B). A diagonal truth still yields a dense cross-impact matrix, and the trades immune to the resulting cost error form a large but measure-zero subspace. Preregistered and reproducible.

Sharp performance bounds for early-warning evaluation with interval-uncertain event onset.

Reproducible code and derived data for testing how present-day stellar constraints identify cumulative EUV and wind histories in TOI-700 and LHS 1140.

Replication files for Jun and Lee (2022)

Replication: Lee and Weidner (forthcoming, Journal of Econometrics)

Privacy suppression makes the Anthropic Economic Index automation–augmentation measure partially identified. Only 42 of 775 occupations are usably identified.

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.

Claim-relative identified sets across benchmark evaluation specifications

Beyond Return Ratios: identification, partial identification, timing effects, mechanism evidence, simulations, and reproducibility for leveraged ETFs (LETFs) in quantitative finance.

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).