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Cumulative Prospect Theory in the Laboratory: A Reconsideration

In: Models of Risk Preferences: Descriptive and Normative Challenges

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  • Glenn W. Harrison
  • J. Todd Swarthout

Abstract

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

Suggested Citation

  • Glenn W. Harrison & J. Todd Swarthout, 2023. "Cumulative Prospect Theory in the Laboratory: A Reconsideration," Research in Experimental Economics, in: Models of Risk Preferences: Descriptive and Normative Challenges, volume 22, pages 107-192, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:rexezz:s0193-230620230000022003
    DOI: 10.1108/S0193-230620230000022003
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    Cited by:

    1. Doidge, Mary & Feng, Hongli & Hennessy, David A., "undated". "Farmers’ valuation of changes to crop insurance coverage level – a test of third generation prospect theory," 2018 Annual Meeting, August 5-7, Washington, D.C. 274478, Agricultural and Applied Economics Association.
    2. Heckman, James J. & Jagelka, Tomáš & Kautz, Tim, 2019. "Some Contributions of Economics to the Study of Personality," IZA Discussion Papers 12753, IZA Network @ LISER.
    3. Buchanan, Joy A., 2020. "My reference point, not yours," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 297-311.
    4. Balcombe, Kelvin & Fraser, Iain, 2024. "A Note on an Alternative Approach to Experimental Design of Lottery Prospects," MPRA Paper 119743, University Library of Munich, Germany.
    5. Guilhem Lecouteux, 2021. "Behavioral Welfare Economics and Consumer Sovereignty," Post-Print halshs-03418219, HAL.
    6. Kechagia, Varvara & Drichoutis, Andreas C., 2016. "The effect of olfactory sensory cues on economic decision making," MPRA Paper 75293, University Library of Munich, Germany.
    7. Glenn W. Harrison & Jia Min Ng, 2019. "Behavioral insurance and economic theory: A literature review," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 22(2), pages 133-182, July.
    8. Buckley, Penelope & Roussillon, Béatrice & Teyssier, Sabrina, 2025. "Loss and gain framing to encourage repeated real-effort provision: An experiment," Research in Economics, Elsevier, vol. 79(3).
    9. Robert Oxoby & William G. Morrison, "undated". "Asset Integration, Risk Taking and Loss Aversion in the Laboratory," Working Papers 2019-04, Department of Economics, University of Calgary, revised 30 Jan 2019.
    10. Balcombe, Kelvin & Bardsley, Nicholas & Dadzie, Sam & Fraser, Iain, 2019. "Estimating parametric loss aversion with prospect theory: Recognising and dealing with size dependence," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 106-119.
    11. Glenn W. Harrison & Jia Min Ng, 2018. "Welfare effects of insurance contract non-performance," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 43(1), pages 39-76, May.
    12. Hayley Clatterbuck & Clinton Castro & Arvo Mu~noz Mor'an, 2024. "Risk Alignment in Agentic AI Systems," Papers 2410.01927, arXiv.org.
    13. Bocquého, Géraldine & Deschamps, Marc & Helstroffer, Jenny & Jacob, Julien & Joxhe, Majlinda, 2023. "Modelling refugee migration under cognitive biases: Experimental evidence and policy," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    14. Hou, Yanxi & Wang, Xing, 2019. "Nonparametric inference for distortion risk measures on tail regions," Insurance: Mathematics and Economics, Elsevier, vol. 89(C), pages 92-110.
    15. Müller, Stephan & Rau, Holger A., 2019. "Decisions under uncertainty in social contexts," Games and Economic Behavior, Elsevier, vol. 116(C), pages 73-95.
    16. Guilhem Lecouteux, 2021. "Who's Afraid of Incoherence? Behavioural Welfare Economics and the Sovereignty of the Neoclassical Consumer," GREDEG Working Papers 2021-01, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    17. Kechagia, Varvara & Drichoutis, Andreas C., 2017. "The effect of olfactory sensory cues on willingness to pay and choice under risk," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 70(C), pages 33-46.
    18. Lin, Feng & Peng, Liang & Xie, Jiehua & Yang, Jingping, 2018. "Stochastic distortion and its transformed copula," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 148-166.
    19. Louis Eeckhoudt & Anna Maria Fiori & Emanuela Rosazza Gianin, 2018. "Risk Aversion, Loss Aversion, and the Demand for Insurance," Risks, MDPI, vol. 6(2), pages 1-19, May.
    20. David Blake & Edmund Cannon & Douglas Wright, 2025. "Correction: Quantifying loss aversion: Evidence from a UK population survey," Journal of Risk and Uncertainty, Springer, vol. 71(3), pages 293-295, December.
    21. Harrison, Glenn W. & Kairies-Schwarz, Nadja & Han, Johann, 2024. "Deductibles and health care utilization: An experiment on the role of forward-looking behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 717-748.
    22. Ferro, Giuseppe M. & Kovalenko, Tatyana & Sornette, Didier, 2021. "Quantum decision theory augments rank-dependent expected utility and Cumulative Prospect Theory," Journal of Economic Psychology, Elsevier, vol. 86(C).
    23. Glenn W. Harrison, 2019. "The behavioral welfare economics of insurance," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 44(2), pages 137-175, September.

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