Optimal Paternalism in a Population with Bounded Rationality: with Focus on Discrete Choice

We consider a utilitarian planner with the power to design a discrete choice set for a population with bounded rationality. We find that optimal paternalism is subtle. The policy that most effectively constrains or influences choices depends on both the preference distribution and the choice probabilities measuring the extent to which persons behave suboptimally. We caution against implementation of paternalistic policies that optimize welfare using behavioral assumptions that lack credible foundation. In the absence of firm empirical understanding of behavior, such policies may do more harm than good. To develop these themes, we first consider the planning problem in abstraction. We next examine policy choice when individuals are boundedly rational in a specific way, this being that they measure utility with additive random error and maximize mismeasured rather than actual utility functions. A numerical example shows the subtlety of the planning problem. We then analyze binary treatment choice under uncertainty, supposing that a planner can mandate a particular treatment or can decentralize decision making, enabling variation in treatment. We apply the analysis to medical treatment, observing that clinical practice guidelines pose quasi-mandates for clinical care of patients.