This paper proposes a novel method to estimate individualised treatment assignment rules.
The method is designed to find rules that are stochastic, reflecting uncertainty in estimation …

In this paper, I study the statistical inference problem for treatment assignment policies. In
typical applications, individuals with different characteristics are expected to differ in their …

This paper studies statistical decisions for dynamic treatment assignment problems. Many
policies involve dynamics in their treatment assignments where treatments are sequentially …

In this paper we study treatment assignment rules in the presence of social interaction. We
construct an analytical framework under the anonymous interaction assumption, where the …

In this paper, we explore optimal treatment allocation policies that target distributional
welfare. Most literature on treatment choice has considered utilitarian welfare based on the …

This paper studies a penalized statistical decision rule for the treatment assignment
problem. Consider the setting of a utilitarian policy maker who must use sample data to …

This paper studies the problem of estimating individualized treatment rules when treatment
effects are partially identified, as it is often the case with observational data. By drawing …

This paper considers the estimation of treatment assignment rules when the policy maker
faces a general budget or resource constraint. Utilizing the PAC-Bayesian framework, we …

There is increasing interest in allocating treatments based on observed individual
characteristics: examples include targeted marketing, individualized credit offers, and …

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 …