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Behavioral welfare economics and risk preferences: a Bayesian approach

Published online by Cambridge University Press:  14 March 2025

Xiaoxue Sherry Gao ,
Glenn W. Harrison Open the ORCID record for Glenn W. Harrison [Opens in a new window]  and
Rusty Tchernis
Xiaoxue Sherry Gao*
Affiliation:
Department of Resource Economics, University of Massachusetts Amherst, Amherst, USA
Glenn W. Harrison*
Affiliation:
Department of Risk Management & Insurance and Center for the Economic Analysis of Risk, Robinson College of Business, Georgia State University, Atlanta, USA School of Economics, University of Cape Town, Cape Town, South Africa
Rusty Tchernis*
Affiliation:
Department of Economics, Andrew Young School of Policy Studies, Georgia State University, Atlanta, USA
*
xiaoxuegao@umass.edu
gharrison@gsu.edu
rtchernis@gsu.edu
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Abstract

We propose the use of Bayesian estimation of risk preferences of individuals for applications of behavioral welfare economics to evaluate observed choices that involve risk. Bayesian estimation provides more systematic control of the use of informative priors over inferences about risk preferences for each individual in a sample. We demonstrate that these methods make a difference to the rigorous normative evaluation of decisions in a case study of insurance purchases. We also show that hierarchical Bayesian methods can be used to infer welfare reliably and efficiently even with significantly reduced demands on the number of choices that each subject has to make. Finally, we illustrate the natural use of Bayesian methods in the adaptive evaluation of welfare.

Keywords

Behavioral welfare economicsBayesian analysisRisk preferencesInsurance

JEL classification

D6: Welfare Economics C11: Bayesian Analysis: General G40: General‡ D81: Criteria for Decision-Making under Risk and Uncertainty
Type
Original Paper
Information
Experimental Economics , Volume 26 , Issue 2 , April 2023 , pp. 273 - 303
Copyright
Copyright © The Author(s), under exclusive licence to Economic Science Association 2022

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Footnotes

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10683-022-09751-0.

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