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Insurance Demand Under Prospect Theory: A Graphical Analysis

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  • Ulrich Schmidt

Abstract

This paper analyzes insurance demand under prospect theory in a simple model with two states of the world and fair insurance contracts. We argue that two different reference points are reasonable in this framework, state-dependent initial wealth or final wealth after buying full insurance. Applying the value function of Tversky and Kahneman (1992), we find that for both reference points subjects will either demand full insurance or no insurance at all. Moreover, this decision depends on the probability of the loss: the higher the probability of the loss, the higher is the propensity to take up insurance. This result can explain empirical evidence which has shown that people are unwilling to insure rare losses at subsidized premiums and at the same time take-up insurance for moderate risks at highly loaded premiums.
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  • Ulrich Schmidt, 2016. "Insurance Demand Under Prospect Theory: A Graphical Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 77-89, January.
    • Handle: RePEc:bla:jrinsu:v:83:y:2016:i:1:p:77-89
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    1. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

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    6. Chi, Yichun & Zheng, Jiakun & Zhuang, Shengchao, 2022. "S-shaped narrow framing, skewness and the demand for insurance," Insurance: Mathematics and Economics, Elsevier, vol. 105(C), pages 279-292.
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    8. Chen, Zheng & Li, Zhongfei & Zeng, Yan & Sun, Jingyun, 2017. "Asset allocation under loss aversion and minimum performance constraint in a DC pension plan with inflation risk," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 137-150.
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    10. Daniel Osberghaus, 2017. "Prospect theory, mitigation and adaptation to climate change," Journal of Risk Research, Taylor & Francis Journals, vol. 20(7), pages 909-930, July.
    11. Kunal Rajesh Lahoti & Shivani Hanji & Pratik Kamble & Kavita Vemuri, 2023. "Impact of Loss-Framing and Risk Attitudes on Insurance Purchase: Insights from a Game-like Interface Study," Papers 2310.13300, arXiv.org.
    12. Cardon, James H., 2020. "Loss aversion and health insurance plan switching," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 955-966.
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    14. Shin, Soye & Magnan, Nicholas & Mullally, Conner & Janzen, Sarah, 2022. "Demand for Weather Index Insurance among Smallholder Farmers under Prospect Theory," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 82-104.
    15. Immanuel Lampe & Daniel Würtenberger, 2019. "Loss Aversion And The Demand For Index Insurance," Working Papers on Finance 1907, University of St. Gallen, School of Finance.
    16. 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.
    17. Maren Baars & Michael Goedde‐Menke, 2022. "Ignorance illusion in decisions under risk: The impact of perceived expertise on probability weighting," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(1), pages 35-62, March.
    18. Johannes G. Jaspersen & Richard Peter & Marc A. Ragin, 2023. "Probability weighting and insurance demand in a unified framework," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 48(1), pages 63-109, March.
    19. Hwang, In Do, 2021. "Prospect theory and insurance demand: Empirical evidence on the role of loss aversion," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 95(C).
    20. Fujii Yoichiro & Inakura Noriko, 2019. "Factors Widening the Gap between Hypothetical and Actual choices—Empirical Evidence from the Japanese Medical Insurance Market—," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 13(2), pages 1-15, July.
    21. Lampe, Immanuel & Würtenberger, Daniel, 2020. "Loss aversion and the demand for index insurance," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 678-693.
    22. Pedro Brandão Graminha & Luís Eduardo Afonso, 2022. "Behavioral Economics and Auto Insurance: The Role of Biases and Heuristics," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(5), pages 200421-2004.
    23. Yichun Chi & Wei Wei, 2020. "Optimal insurance with background risk: An analysis of general dependence structures," Finance and Stochastics, Springer, vol. 24(4), pages 903-937, October.
    24. K. P. M. Winssen & R. C. Kleef & W. P. M. M. Ven, 2016. "Potential determinants of deductible uptake in health insurance: How to increase uptake in The Netherlands?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(9), pages 1059-1072, December.
    25. JaeYoul Shin, 2019. "How Can we Achieve a Sustainable Redistributive Policy? Rethinking the Relationship Between Civic Engagement, Neighborhood Relationship and Labor Market Status," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(1), pages 343-362, February.

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    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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