On the Coefficient of Variation as a Measure of Risk Sensitivity

Abstract

Weber, Shafir, and Blais (2004) advocate use of the coefficient of variation (CV) as a measure of risk sensitivity and apply CV in a meta-analysis of data for risky choices by humans and animals. We critically re-examine the CV measure as either a normative or descriptive criterion for decision under risk. CV fails as a normative criterion because it violates first order stochastic dominance. Whether or not CV succeeds as a descriptive criterion depends on its consistency or inconsistency with data from experiments designed to test its distinctive properties. We report an experiment with human subjects motivated by salient monetary payoffs. The data are inconsistent with the hypothesis that the CVs of risky lotteries are a significant determinant of subjects’ choices between the lotteries and certain payoffs.