Stochastic Treatment Choice with Empirical Welfare Updating

Understand

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 of an assignment rule and about its welfare performance.
• Our approach is to form a prior distribution over assignment rules, not over data generating processes, and to update this prior based upon an empirical welfare criterion, not likelihood.
• The social planner then assigns treatment by drawing a policy from the resulting posterior.