Document Type
Article
Publication Date
2024
Abstract
The social welfare function (SWF) framework converts the possible outcomes of governmental policy choice into vectors (lists) of interpersonally comparable well-being numbers, measuring the lifetime well-being of each individual in the population of interest. The SWF proper is a rule for ranking these vectors. The utilitarian SWF adds up well-being numbers. A prioritarian SWF adds up well-being numbers plugged into a strictly increasing and strictly concave transformation function. Governmental policies are conceptualized as probability distributions over well-being vectors. A recent literature applies the SWF framework to health policy. This article first provides a brief overview of the SWF framework and then reviews some of the key concepts and findings that have emerged from this literature. One such concept is the “social value of risk reduction” (SVRR): the marginal social value (as calculated by the SWF) per unit of reduction in fatality risk for a given individual. The SVRR is the analogue, within the SWF framework, to the value-of-statistical-life (VSL) concept within benefit–cost analysis. This article explicates the SVRR concept and reports on recent theoretical findings and simulations that illustrate the properties of utilitarian and prioritarian SVRRs and their differences from VSL.
Citation
Matthew D. Adler, Social Welfare Functions and Health Policy: A New Approach, 2024 Journal of Benefit-Cost Analysis 1-26 (2024)
Library of Congress Subject Headings
Well-being, Quality of life--Measurement, Welfare economics
Included in
Behavioral Economics Commons, Health Policy Commons, Law Commons, Social Welfare Commons
DOI: https://doi.org/10.1017/bca.2024.6
Available at: https://scholarship.law.duke.edu/faculty_scholarship/4317