Statistical Children

Abstract

This Article provides the first comprehensive analysis of how cost-benefit analysis should value child mortality. Recent research suggests that parents are willing to pay twice as much to reduce risks that their children face, compared to the amount that they are willing to pay to reduce their own risks. In fact, all demographic groups-old, young, parents, and non-parents-give priority to children when allocating scarce health-care resources. This simple fact is currently ignored in cost-benefit analyses even though this "child premium " has strong theoretical and empirical support. This Article uses the child premium to illuminate a potential point of agreement between proponents and critics of cost-benefit analysis and then uses it to highlight recurring deficiencies in the way agencies respond to scientific innovation more generally. Drawing on adaptive management theory and the concept of model uncertainty, this Article proposes a framework-the alternate-models approach-that allows agencies to experiment with innovations to cost-benefit analysis like the child premium. This approach helps mitigate two problems in administrative law. First, it allows agencies to drive innovation rather than merely following it. Second, it forces agencies to communicate model uncertainty more effectively than existing proposals. Overall, this Article seeks to offer proponents and critics of cost-benefit analysis a way to move forward and explore a host of innovations to cost-benefit analysis and its main competitor, cost-effectiveness analysis.