The Subtlety of Optimal Paternalism in a Population with Bounded Rationality

We study the subtlety of optimal paternalism when a utilitarian planner has the power to design a discrete choice set for a heterogeneous population with bounded rationality. We first consider the planning problem in abstraction. We show that the policy that most effectively constrains or influences choices depends multiplicatively on the preferences of the population and the choice probabilities conditional on preferences that measure the suboptimality of behavior. We then study two settings in which the planner may mandate an action or decentralize decision making. One setting supposes that individuals measure utility with additive random error and maximize mismeasured rather than actual utility. Then optimal planning requires knowledge of the distribution of measurement errors. The other setting studies binary treatment choice when the planner can mandate a treatment conditional on publicly observed personal covariates or can enable individuals to choose their own treatments conditional on private information. Here we focus on situations where bounded rationality takes the form of deviations between subjective and objective probabilities of uncertain outcomes. To illustrate, we consider clinical decision making in medicine. In toto, our cautionary analysis shows that determination of optimal policy requires the planner to possess extensive knowledge that is rarely available. We warn that research in behavioral public economics should avoid overoptimistic claims regarding the nature of optimal paternalistic policies. We argue that credible study of utilitarian planning should consider not only the population but also the planner to be boundedly rational.