7 citations · 8 across the 7 of their papers we have counts for
5 papers · 1 filter
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
Undral Byambadalai, Tomu Hirata, Tatsushi Oka +1
This paper focuses on the estimation of distributional treatment effects in randomized experiments that use covariate-adaptive randomization (CAR). These include designs such as Ef…
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
We propose a novel regression adjustment method designed for estimating distributional treatment effect parameters in randomized experiments. Randomized experiments have been exten…
Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials
Tatsushi Oka, Shota Yasui, Yuta Hayakawa +1
In this paper, we address the issue of estimating and inferring distributional treatment effects in randomized experiments. The distributional treatment effect provides a more comp…
Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning
Susan Athey, Undral Byambadalai, Vitor Hadad +3
We design and implement an adaptive experiment (a ``contextual bandit'') to learn a targeted treatment assignment policy, where the goal is to use a participant's survey responses…
Identification and Inference for Welfare Gains without Unconfoundedness
Undral Byambadalai
This paper studies identification and inference of the welfare gain that results from switching from one policy (such as the status quo policy) to another policy. The welfare gain…