On the Coefficient of Variation as a Measure of Risk Sensitivity

James Cox and Vjollca Sadiraj

No 2009-06, Experimental Economics Center Working Paper Series from Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University

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.

Pages: 14
Date: 2009-01, Revised 2010-07
New Economics Papers: this item is included in nep-exp and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://excen.gsu.edu/workingpapers/GSU_EXCEN_WP_2009-06.pdf First version, 2009 (application/pdf)
http://excen.gsu.edu/workingpapers/GSU_EXCEN_WP_2010-04.pdf Revised version, 2010 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:exc:wpaper:2009-06

Access Statistics for this paper

More papers in Experimental Economics Center Working Paper Series from Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University Contact information at EDIRC.
Bibliographic data for series maintained by J. Todd Swarthout ().