Utilitarian or Quantile-Welfare Evaluation of Health Policy?

2025-09-05

AI Summary

This paper addresses the limitations of excessive reliance on utilitarianism (expected utility maximization) in health policy evaluation by proposing a novel social welfare paradigm grounded in quantile-based welfare. Methodologically, it extends individual-level quantile utility maximization to social planning, constructing a nonparametric quantile welfare measurement framework that requires only ordinal utility information. Using binary-choice time-trade-off experimental data under the EQ-5D health classification system, the framework achieves robust identification via nonparametric boundary estimation techniques. Key contributions include: (i) the first systematic development of a quantile welfare theory specifically for health economics—free from assumptions of cardinal utility or parametric utility functional forms; and (ii) an operational procedure for policy ranking and equity assessment, offering a new analytical tool for health decision-making that jointly accounts for efficiency and distributional sensitivity.

Technology Category

• Game Theory and Economic Paradigms: Social Choice / Voting
• Reasoning under Uncertainty: Decision/Utility Theory
• Machine Learning: Learning Preferences or Rankings

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This paper considers quantile-welfare evaluation of health policy as an alternative to utilitarian evaluation. Manski (1988) originally proposed and studied maximization of quantile utility as a model of individual decision making under uncertainty, juxtaposing it with maximization of expected utility. That paper's primary motivation was to exploit the fact that maximization of quantile utility requires only an ordinal formalization of utility, not a cardinal one. This paper transfers these ideas from analysis of individual decision making to analysis of social planning. We begin by summarizing basic theoretical properties of quantile welfare in general terms rather than related specifically to health policy. We then propose a procedure to nonparametrically bound the quantile welfare of health states using data from binary-choice time-tradeoff (TTO) experiments of the type regularly performed by health economists. After this we assess related econometric considerations concerning measurement, using the EQ-5D framework to structure our discussion.

Problem

• Evaluating health policy using quantile-welfare instead of utilitarian approach
• Proposing nonparametric bounds for quantile welfare using TTO data
• Addressing econometric measurement considerations within EQ-5D framework

Innovation

• Quantile welfare evaluation for social planning
• Nonparametric bounds using binary-choice TTO data
• EQ-5D framework for measurement assessment