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Understanding the Two Components of Risk Attitudes: An Experimental Analysis

Author

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  • Jianying Qiu

    (Department of Economics, University of Innsbruck)

  • Eva-Maria Steiger

    (Stratigic Interaction Group, Max Planck Institute of Economics, Jena)

Abstract

Economics and management science share the tradition of ordering risk aversion by ï¬ tting the best expected utility (EU) model with a certain utility function to individual data, and then using the utility curvature for each individual as the sole index of risk attitude. (Cumulative) Prospect theory (CPT) has demonstrated various empirical deï¬ ciencies of EU and introduced the weighting of probabilities as an additional component to capture risk attitude. However, if utility curvature and probability weighting were strongly correlated, the utility curvature in EU alone, while not properly describing risky behavior in general, would still capture most of the variance regarding degrees of risk aversion. This study shows, however, that such a strong correlation does not exist. Though, most individuals exhibit concave utility and convex probability weighting, the two components show no correlation. Thus neglecting one component entails a loss.

Suggested Citation

  • Jianying Qiu & Eva-Maria Steiger, 2009. "Understanding the Two Components of Risk Attitudes: An Experimental Analysis," Jena Economics Research Papers 2009-088, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2009-088
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    References listed on IDEAS

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    Cited by:

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    2. Herold, Florian & Netzer, Nick, 2023. "Second-best probability weighting," Games and Economic Behavior, Elsevier, vol. 138(C), pages 112-125.
    3. Renata S Suter & Thorsten Pachur & Ralph Hertwig & Tor Endestad & Guido Biele, 2015. "The Neural Basis of Risky Choice with Affective Outcomes," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-22, April.
    4. Matthew D. Rablen, 2023. "Loss Aversion, Risk Aversion, and the Shape of the Probability Weighting Function," Working Papers 2023013, The University of Sheffield, Department of Economics.
    5. Ilke Aydogan & Yu Gao, 2020. "Experience and rationality under risk: re-examining the impact of sampling experience," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1100-1128, December.
    6. Qiu, Jianying & Ong, Qiyan, 2017. "Indifference or indecisiveness: a strict discrimination," MPRA Paper 81790, University Library of Munich, Germany, revised 18 Sep 2017.
    7. Alam, Jessica & Georgalos, Konstantinos & Rolls, Harrison, 2022. "Risk preferences, gender effects and Bayesian econometrics," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 168-183.
    8. Qiu, Jianying & Weitzel, Utz, 2013. "Experimental Evidence on Valuation and Learning with Multiple Priors," MPRA Paper 43974, University Library of Munich, Germany.
    9. Gijs van de Kuilen & Peter P. Wakker, 2011. "The Midweight Method to Measure Attitudes Toward Risk and Ambiguity," Management Science, INFORMS, vol. 57(3), pages 582-598, March.
    10. Olivier Toubia & Eric Johnson & Theodoros Evgeniou & Philippe Delquié, 2013. "Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters," Management Science, INFORMS, vol. 59(3), pages 613-640, June.
    11. Festjens, Anouk & Bruyneel, Sabrina & Diecidue, Enrico & Dewitte, Siegfried, 2015. "Time-based versus money-based decision making under risk: An experimental investigation," Journal of Economic Psychology, Elsevier, vol. 50(C), pages 52-72.
    12. Rablen, Matthew D., 2019. "Foundations of the Rank-Dependent Probability Weighting Function," IZA Discussion Papers 12701, Institute of Labor Economics (IZA).
    13. Özalp Özer & Yanchong Zheng, 2016. "Markdown or Everyday Low Price? The Role of Behavioral Motives," Management Science, INFORMS, vol. 62(2), pages 326-346, February.
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    16. Michał Krawczyk, 2014. "Probability weighting in different domains: the role of stakes, fungibility, and affect," Working Papers 2014-15, Faculty of Economic Sciences, University of Warsaw.

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    More about this item

    Keywords

    risk attitudes; cumulative prospect theory; experimental study;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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