IDEAS home Printed from https://ideas.repec.org/p/exc/wpaper/2020-06.html

Do People Maximize Quantiles?

Author

Listed:
  • Luciano de Castroy
  • Antonio F. Galvao
  • Charles N. Noussair
  • Liang Qiao

Abstract

Quantiles have been used for decision making in banking and investment (in the form of Value at Risk) and in the mining, oil and gas industries (in the form of \\probabilities of exceeding\" a certain level of production). However, it is unknown how common quantile-based decision making actually is among individual decision makers. This paper describes an experiment that aims to (1) compare how common quantile decision making is relative to expected utility maximization, and (2) estimate risk attitude parameters under the assumption of quantile preferences. The experiment has two parts. In the first part, individuals make pairwise choices between risky lotteries, and the competing models are fitted to the choice data. In the second part, we directly elicit a decision rule from a menu of alternatives. The results show that the quantile preference model outperforms expected utility for a considerable minority, 30%-50%, of participants, depending on the metric. The majority of individuals are risk averse, and women are more risk averse than men, under both models.

Suggested Citation

  • Luciano de Castroy & Antonio F. Galvao & Charles N. Noussair & Liang Qiao, 2020. "Do People Maximize Quantiles?," Experimental Economics Center Working Paper Series 2020-06, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
    • Handle: RePEc:exc:wpaper:2020-06
    as

    Download full text from publisher

    File URL: http://excen.gsu.edu/workingpapers/GSU_EXCEN_WP_2020-06.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    3. Peng Liu & Tiantian Mao & Ruodu Wang, 2024. "Quantiles under ambiguity and risk sharing," Papers 2412.19546, arXiv.org.
    4. de Castro, Luciano & Galvao, Antonio F. & Muchon, Andre, 2023. "Numerical Solution of Dynamic Quantile Models," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    5. de Castro, Luciano & Galvao, Antonio F. & Ota, Hirofumi, 2026. "Quantile approach to intertemporal consumption with multiple assets," Journal of Econometrics, Elsevier, vol. 253(C).
    6. Jose Blanchet & Henry Lam & Yang Liu & Ruodu Wang, 2025. "Convolution Bounds on Quantile Aggregation," Operations Research, INFORMS, vol. 73(5), pages 2761-2781, September.
    7. Luciano de Castro & Antonio F. Galvao & Gabriel Montes-Rojas & Jose Olmo, 2022. "Portfolio selection in quantile decision models," Annals of Finance, Springer, vol. 18(2), pages 133-181, June.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:exc:wpaper:2020-06. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: J. Todd Swarthout (email available below). General contact details of provider: https://edirc.repec.org/data/exgsuus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.