Working Paper: NBER ID: w27685
Authors: Xiaoxue Sherry Gao; Glenn W. Harrison; Rusty Tchernis
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: Bayesian estimation; risk preferences; behavioral welfare economics; insurance purchases
JEL Codes: C11; D81; G40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Bayesian estimation (C11) | more accurate reflection of individual risk preferences (D81) |
| Bayesian hierarchical methods (C11) | more reliable inference of welfare (D69) |
| Bayesian methods (C11) | better normative evaluations of decisions (D79) |