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Accommodating Stake Effects under Prospect Theory

Author

Listed:
  • Ranoua Bouchouicha

    (Henley Business School, University of Reading)

  • Ferdinand Vieider

    (Department of Economics, University of Reading)

Abstract

We investigate how to accommodate qualitative changes in risk preferences over outcomes and probabilities under prospect theory. We find a double two-fold pattern of risk preferences for gains, one over probabilities and one over outcomes. While such patterns over probabilities are an integral part of prospect theory, a solution on how to incorporate two-fold patterns over outcomes has only recently been proposed by Scholten and Read (2014) [Prospect theory and the 'forgotten' fourfold pattern of risk preferences. JRU 48(1)]. We use this insight to address violations of probability-outcome separability under prospect theory as stakes increase [Fehr-Duda, Bruhin, Epper, and Schubert (2010). Rationality on the Rise: Why Relative Risk Aversion Increases with Stake Size. JRU 40(2)]. We replicate the violations using traditional functional forms such as power or exponential utility. Using logarithmic utility instead makes the violations disappear, showing the importance of accommodating changing risk preferences across the outcome dimension.

Suggested Citation

  • Ranoua Bouchouicha & Ferdinand Vieider, 2016. "Accommodating Stake Effects under Prospect Theory," Economics Discussion Papers em-dp2016-03, Department of Economics, University of Reading.
    • Handle: RePEc:rdg:emxxdp:em-dp2016-03
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    Cited by:

    1. Salvatore Di Falco & Ferdinand M Vieider, 2022. "Environmental Adaptation of Risk Preferences," The Economic Journal, Royal Economic Society, vol. 132(648), pages 2737-2766.
    2. Aurélien Baillon & Olivier L’Haridon, 2021. "Discrete Arrow–Pratt indexes for risk and uncertainty," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(4), pages 1375-1393, November.
    3. Konstantinos Georgalos & Ivan Paya & David Peel, 2023. "Higher order risk attitudes: new model insights and heterogeneity of preferences," Experimental Economics, Springer;Economic Science Association, vol. 26(1), pages 145-192, March.
    4. Eyal Baharad & Ruth Ben-Yashar, 2021. "Judgment Aggregation by a Boundedly Rational Decision-Maker," Group Decision and Negotiation, Springer, vol. 30(4), pages 903-914, August.
    5. Adam Oliver, 2018. "Your money and your life: Risk attitudes over gains and losses," Journal of Risk and Uncertainty, Springer, vol. 57(1), pages 29-50, August.
    6. Slosse, Wannes & Mutuku, Kennedy Vaati & de Clercq, Michaël & D’Haese, Marijke & Schoors, Koen & Buysse, Jeroen, 2025. "Uncertainty and inequality preferences in the Ultimatum Game: A case study on Kenyan smallholder farmers," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 118(C).
    7. Naranjo, Maria A. & Alpízar, Francisco & Martinsson, Peter, 2019. "Alternatives for Risk Elicitation in the Field: Evidence from Coffee Farmers in Costa Rica," EfD Discussion Paper 19-21, Environment for Development, University of Gothenburg.
    8. Cecchi, Francesco & Lensink, Robert & Slingerland, Edwin, 2024. "Ambiguity attitudes and demand for weather index insurance with and without a credit bundle: experimental evidence from Kenya," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    9. Uri Gneezy & Yoram Halevy & Brian Hall & Theo Offerman & Jeroen van de Ven, 2024. "How Real is Hypothetical? A High-Stakes Test of the Allais Paradox," Working Papers tecipa-783, University of Toronto, Department of Economics.
    10. Oliver, Adam, 2018. "Your money and your life: risk attitudes over gains and losses," LSE Research Online Documents on Economics 88583, London School of Economics and Political Science, LSE Library.
    11. Géraldine Bocquého & Julien Jacob & Marielle Brunette, 2023. "Prospect theory in multiple price list experiments: further insights on behaviour in the loss domain," Theory and Decision, Springer, vol. 94(4), pages 593-636, May.
    12. Puerta, Inmaculada R. & Pinto, José Luis, 2025. "Can reference-dependent loss aversion explain choice behaviour?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 117(C).
    13. Chen Sun & Jan Potters, 2022. "Magnitude effect in intertemporal allocation tasks," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 593-623, April.
    14. Abdellaoui, Mohammed & Kemel, Emmanuel & Panin, Amma & Vieider, Ferdinand M., 2019. "Measuring time and risk preferences in an integrated framework," Games and Economic Behavior, Elsevier, vol. 115(C), pages 459-469.
    15. Géraldine Bocquého & Julien Jacob & Marielle Brunette, 2020. "Prospect theory in experiments : behaviour in loss domain and framing effects," Working Papers hal-02987294, HAL.
    16. Georgalos, Konstantinos & Paya, Ivan & Peel, David A., 2021. "On the contribution of the Markowitz model of utility to explain risky choice in experimental research," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 527-543.
    17. Jozef Klucka & Rudolf Gruenbichler & Jozef Ristvej, 2021. "Relations of COVID-19 and the Risk Management Framework," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    18. Taisuke Imai & Salvatore Nunnari & Jilong Wu & Ferdinand M. Vieider, 2025. "Meta-Analysis of Prospect Theory Parameters," CESifo Working Paper Series 12334, CESifo.
    19. Isaiah Andrews & Drew Fudenberg & Lihua Lei & Annie Liang & Chaofeng Wu, 2022. "The Transfer Performance of Economic Models," Papers 2202.04796, arXiv.org, revised Mar 2025.
    20. 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.

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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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