Optimal Default Options

Abstract

Previous studies of optimal default options demonstrate that either opt-out minimization or maximization is optimal under restrictive conditions. We obtain a general characterization of the solution by studying optimal defaults when one of the problem's parameters approaches a limiting value. We interpret these “asymptotic optima” as approximate optima for non-limiting cases and justify this interpretation through numerical simulations. When the designer and choosers agree about the activity's value, simple forms of weighted opt-out minimization are asymptotically optimal. Additional results encompass Pigouvian fees, normative ambiguity, and cases in which the designer and choosers disagree about the activity's value.

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