Research

Distributional treatment effects of content promotion: evidence from an ABEMA field experiment

with Shota Yasui, Tatsushi Oka and Yuki Oishi

The Japanese Economic Review · 2026

Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials

with Tatsushi Oka, Shota Yasui and Yuta Hayakawa

Econometric Reviews · 2026

Beyond the Average: Distributional Causal Inference under Imperfect Compliance

with Tomu Hirata, Tatsushi Oka and Shota Yasui

Neural Information Processing Systems (NeurIPS) · 2025

On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization

with Tomu Hirata, Tatsushi Oka and Shota Yasui

International Conference on Machine Learning (ICML) · 2025

Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction

with Tatsushi Oka and Shota Yasui

International Conference on Machine Learning (ICML) · 2024

Changing Preferences: An Experiment and Estimation of Market-Incentive Effects on Altruism

with Albert Ma and Daniel Wiesen

Journal of Health Economics, Vol. 92 · December 2023, 102808

Efficient and Scalable Estimation of Distributional Treatment Effects with Multi-Task Neural Networks

with Tomu Hirata, Tatsushi Oka, Shota Yasui and Shingo Uto

The Heterogeneous Impact of Changes in Default Gift Amounts on Fundraising

with Susan Athey, Matias Cersosimo, Kristine Koutout and Shanjukta Nath

Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning

with Susan Athey, Vitor Hadad, Sanath Krishnamurthy, Weiwen Leung and Joseph Jay Williams

Identification and Inference for Welfare Gains without Unconfoundedness

dte-adj — Distributional Treatment Effects and Regression Adjustment

A Python package for estimating distributional treatment effects with regression adjustment.