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Tradeoffs for Downside Risk-Averse Decision-Makers and the Self-Protection Decision

Author

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  • Michel M Denuit

    (Institut de Sciences Actuarielles and Institut de Statistique, Université Catholique de Louvain, Louvain-la-Neuve B-1348, Belgium.)

  • Louis Eeckhoudt

    (IESEG School of Management, LEM, Lille, France.
    CORE, Université Catholique de Louvain, Louvain-la-Neuve, Belgium)

  • Liqun Liu

    (Private Enterprise Research Center, Texas A&M University, College Station, TX 77843, U.S.A.)

  • Jack Meyer

    (Department of Economics, Michigan State University, East Lansing, MI 48824, U.S.A.)

Abstract

In addition to risk aversion, decision-makers tend to be also downside risk averse. Besides the usual size for risk trade-off, this allows several other trade-offs to be considered. The decision to increase the level of self-protection generates five trade-offs each involving an unfavourable downside risk increase and an accompanying beneficial change. Five stochastic orders that correspond to these trade-offs are defined, characterised and used to prove comparative static theorems that provide information concerning the self-protection decision. The five stochastic orders are general in nature and can be applied in any decision model where downside risk aversion is assumed.

Suggested Citation

  • Michel M Denuit & Louis Eeckhoudt & Liqun Liu & Jack Meyer, 2016. "Tradeoffs for Downside Risk-Averse Decision-Makers and the Self-Protection Decision," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(1), pages 19-47, March.
    • Handle: RePEc:pal:genrir:v:41:y:2016:i:1:p:19-47
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    Cited by:

    1. Keenan, Donald C. & Snow, Arthur, 2017. "Greater parametric downside risk aversion," Journal of Mathematical Economics, Elsevier, vol. 71(C), pages 119-128.
    2. Richard Peter, 2024. "The economics of self-protection," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 6-35, March.
    3. Light, Bar & Perlroth, Andres, 2021. "The Family of Alpha,[a,b] Stochastic Orders: Risk vs. Expected Value," Journal of Mathematical Economics, Elsevier, vol. 96(C).
    4. Timo R. Lambregts & Paul Bruggen & Han Bleichrodt, 2021. "Insurance decisions under nonperformance risk and ambiguity," Journal of Risk and Uncertainty, Springer, vol. 63(3), pages 229-253, December.
    5. Liqun Liu & Nicolas Treich, 2021. "Optimality of winner-take-all contests: the role of attitudes toward risk," Journal of Risk and Uncertainty, Springer, vol. 63(1), pages 1-25, August.
    6. Richard Peter, 2021. "Who should exert more effort? Risk aversion, downside risk aversion and optimal prevention," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(4), pages 1259-1281, June.
    7. Liqun Liu & Jack Meyer & Andrew J. Rettenmaier & Thomas R. Saving, 2018. "Risk and risk aversion effects in contests with contingent payments," Journal of Risk and Uncertainty, Springer, vol. 56(3), pages 289-305, June.
    8. Liqun Liu & William S. Neilson, 2019. "Alternative Approaches to Comparative n th-Degree Risk Aversion," Management Science, INFORMS, vol. 65(8), pages 3824-3834, August.
    9. Peter, Richard, 2017. "Optimal self-protection in two periods: On the role of endogenous saving," Journal of Economic Behavior & Organization, Elsevier, vol. 137(C), pages 19-36.
    10. Dertwinkel-Kalt, Markus & Ebert, Sebastian & Köster, Mats, 2023. "On correlated lotteries in economic applications," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 292-306.
    11. Mario Menegatti, 2018. "Prudence and Different Kinds of Prevention," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 44(2), pages 273-285, April.

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