1 citations · 1 across the 3 of their papers we have counts for
3 papers
econ.EM2024★ 1 cited
Bandit Algorithms for Policy Learning: Methods, Implementation, and Welfare-performance
Toru Kitagawa, Jeff Rowley
Static supervised learning-in which experimental data serves as a training sample for the estimation of an optimal treatment assignment policy-is a commonly assumed framework of po…
econ.EM2023
Treatment Choice, Mean Square Regret and Partial Identification
Toru Kitagawa, Sokbae Lee, Chen Qiu
We consider a decision maker who faces a binary treatment choice when their welfare is only partially identified from data. We contribute to the literature by anchoring our finite-…
econ.GN2021
Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs
Takanori Ida, Takunori Ishihara, Koichiro Ito +4
Identifying who should be treated is a central question in economics. There are two competing approaches to targeting - paternalistic and autonomous. In the paternalistic approach,…