Heterogeneity in loss aversion: evidence from field elicitations
Article publication date: 2 May 2017
Prospect theory is now widely accepted as the dominant model of choice under risk, but has not been fully incorporated into applied research because of uncertainty about how to include population-level parameter estimates. The purpose of this paper is to characterize heterogeneity across people to lay a foundation for future applied research.
The paper uses elicitation data from field experiments in Vietnam to fit a finite Gaussian mixture model using the expectation maximization algorithm. Applied results are simulated for investment allocations under myopic loss aversion.
The authors find that about 20 percent of the sample is classified as extremely loss averse, while the rest of the population is only mildly loss averse. This implies a bimodal distribution of loss aversion in the population.
The data set is only moderately sized: 181 subjects. Future research will be needed to extend these results out of sample, and to other regions.
This paper provides empirical evidence that heterogeneity matters in prospect theory modeling. It highlights how policy makers might be misled by assuming that average prospect theory parameters are typical within the population.
The authors would like to thank the editor, Calum Turvey, and an anonymous referee for their insightful comments and suggestions to improve this work. The authors would also like to recognize feedback from the participants of the annual meetings of two USDA multi-state projects: SCC-76 Economics and Management of Risk in Agriculture and Natural Resources, and NC-1177 Agricultural and Rural Finance Markets in Transition. Dr Sproul is grateful for financial support from USDA National Institute of Food and Agriculture Hatch Projects: No. RI00H-108, Accession No. 229284, and No. RI0017-NC1177, Accession No. 1011736, and USDA ERS Cooperative Research Agreement No. 58-6000-5-0091.
Sproul, T. and Michaud, C.P. (2017), "Heterogeneity in loss aversion: evidence from field elicitations", Agricultural Finance Review, Vol. 77 No. 1, pp. 196-216. https://doi.org/10.1108/AFR-05-2016-0045
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