IDEAS home Printed from https://ideas.repec.org/a/kap/jrisku/v49y2014i2p141-166.html
   My bibliography  Save this article

To bet or not to bet? Decision-making under risk in non-human primates

Author

Listed:
  • M. Pelé
  • M. Broihanne
  • B. Thierry
  • J. Call
  • V. Dufour

Abstract

Animals deal with predictable and unpredictable events on a daily basis. Yet our knowledge of the cognitive processes involved in decisions remains limited. We tested capuchins, macaques and orang-utans in a food-gambling task to investigate whether or not individuals estimate the chances of different outcomes. Results highlighted that gambling decisions were negatively induced by the probability of losing and the frequency of previous losses, and positively induced by the probability of gaining. Actual decisions were consistent with first order stochastic dominance. The study of second order stochastic dominance revealed that macaques were risk-prone whereas capuchins and orang-utans were risk-adverse. We detected responses comparable to the hot-hand effect, a bias found in humans. Capuchins and orang-utans exhibited probability distortion and loss aversion, which were not systematically found in macaques. Given the heterogeneity among individuals, we implemented mixture models and showed that attitudes towards risk and probabilities play complementary and different roles in the three species. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • M. Pelé & M. Broihanne & B. Thierry & J. Call & V. Dufour, 2014. "To bet or not to bet? Decision-making under risk in non-human primates," Journal of Risk and Uncertainty, Springer, vol. 49(2), pages 141-166, October.
    • Handle: RePEc:kap:jrisku:v:49:y:2014:i:2:p:141-166
    DOI: 10.1007/s11166-014-9202-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11166-014-9202-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11166-014-9202-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Louis Lévy-Garboua & Hela Maafi & David Masclet & Antoine Terracol, 2012. "Risk aversion and framing effects," Experimental Economics, Springer;Economic Science Association, vol. 15(1), pages 128-144, March.
    2. Rachel Croson & James Sundali, 2005. "The Gambler’s Fallacy and the Hot Hand: Empirical Data from Casinos," Journal of Risk and Uncertainty, Springer, vol. 30(3), pages 195-209, May.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    5. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    6. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    7. Camerer, Colin F & Ho, Teck-Hua, 1994. "Violations of the Betweenness Axiom and Nonlinearity in Probability," Journal of Risk and Uncertainty, Springer, vol. 8(2), pages 167-196, March.
    8. 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..
    9. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    10. Chateauneuf, Alain & Cohen, Michele, 1994. "Risk Seeking with Diminishing Marginal Utility in a Non-expected Utility Model," Journal of Risk and Uncertainty, Springer, vol. 9(1), pages 77-91, July.
    11. M. Keith Chen & Venkat Lakshminarayanan & Laurie R. Santos, 2006. "How Basic Are Behavioral Biases? Evidence from Capuchin Monkey Trading Behavior," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 517-537, June.
    12. Anna Conte & John D. Hey & Peter G. Moffatt, 2018. "Mixture models of choice under risk," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 1, pages 3-12, World Scientific Publishing Co. Pte. Ltd..
    13. Richard H. Thaler & Eric J. Johnson, 1990. "Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice," Management Science, INFORMS, vol. 36(6), pages 643-660, June.
    14. Lattimore, Pamela K. & Baker, Joanna R. & Witte, Ann D., 1992. "The influence of probability on risky choice: A parametric examination," Journal of Economic Behavior & Organization, Elsevier, vol. 17(3), pages 377-400, May.
    15. Glenn Harrison & E. Rutström, 2009. "Expected utility theory and prospect theory: one wedding and a decent funeral," Experimental Economics, Springer;Economic Science Association, vol. 12(2), pages 133-158, June.
    16. George Wu & Richard Gonzalez, 1996. "Curvature of the Probability Weighting Function," Management Science, INFORMS, vol. 42(12), pages 1676-1690, December.
    17. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    18. Kessler, Eric H. & Ford, Cameron M. & Bailey, James R., 1996. "Object valence as a moderator of the framing effect on risk preference," Journal of Economic Behavior & Organization, Elsevier, vol. 30(2), pages 241-256, August.
    19. Pamela K. Lattimore & Joanna R. Baker & A. Dryden Witte, 1992. "The Influence Of Probability on Risky Choice: A parametric Examination," NBER Technical Working Papers 0081, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Simone Ferrari-Toniolo & Leo Chi U. Seak & Wolfram Schultz, 2022. "Risky choice: Probability weighting explains independence axiom violations in monkeys," Journal of Risk and Uncertainty, Springer, vol. 65(3), pages 319-351, December.
    2. Francesca de Petrillo & Alexandra Rosati, 2021. "Variation in primate decision-making under uncertainty and the roots of human economic behaviour," Post-Print hal-03151858, HAL.
    3. Steven R. Beckman & Gregory DeAngelo & W. James Smith & Ning Wang, 2016. "Is social choice gender-neutral? Reference dependence and sexual selection in decisions toward risk and inequality," Journal of Risk and Uncertainty, Springer, vol. 52(3), pages 191-211, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Galarza, Francisco, 2009. "Choices under Risk in Rural Peru," MPRA Paper 17708, University Library of Munich, Germany.
    2. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    3. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    4. George Wu & Alex B. Markle, 2008. "An Empirical Test of Gain-Loss Separability in Prospect Theory," Management Science, INFORMS, vol. 54(7), pages 1322-1335, July.
    5. José Lara Resende & George Wu, 2010. "Competence effects for choices involving gains and losses," Journal of Risk and Uncertainty, Springer, vol. 40(2), pages 109-132, April.
    6. Ariane Charpin, 2018. "Tests des modèles de décision en situation de risque. Le cas des parieurs hippiques en France," Revue économique, Presses de Sciences-Po, vol. 69(5), pages 779-803.
    7. Luís Santos-Pinto & Adrian Bruhin & José Mata & Thomas Åstebro, 2015. "Detecting heterogeneous risk attitudes with mixed gambles," Theory and Decision, Springer, vol. 79(4), pages 573-600, December.
    8. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    9. Eyal Baharad & Doron Kliger, 2013. "Market failure in light of non-expected utility," Theory and Decision, Springer, vol. 75(4), pages 599-619, October.
    10. Vincent Laferrière & David Staubli & Christian Thöni, 2023. "Explaining Excess Entry in Winner-Take-All Markets," Management Science, INFORMS, vol. 69(2), pages 1050-1069, February.
    11. Daniel Cavagnaro & Mark Pitt & Richard Gonzalez & Jay Myung, 2013. "Discriminating among probability weighting functions using adaptive design optimization," Journal of Risk and Uncertainty, Springer, vol. 47(3), pages 255-289, December.
    12. Gigi Foster & Paul Frijters & Markus Schaffner & Benno Torgler, 2013. "Expectation Formation in an Evolving Game of Uncertainty: Theory and New Experimental Evidence," CREMA Working Paper Series 2013-19, Center for Research in Economics, Management and the Arts (CREMA).
    13. Jonathan Ingersoll, 2007. "Non-Monotonicity of the Tversky-Kahneman Probability-Weighting Function: A Cautionary Note," Yale School of Management Working Papers amz2432, Yale School of Management, revised 01 Nov 2007.
    14. Martina Nardon & Paolo Pianca, 2019. "Behavioral premium principles," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 229-257, June.
    15. Martina Nardon & Paolo Pianca, 2019. "European option pricing under cumulative prospect theory with constant relative sensitivity probability weighting functions," Computational Management Science, Springer, vol. 16(1), pages 249-274, February.
    16. Kliger, Doron & Levy, Ori, 2009. "Theories of choice under risk: Insights from financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 330-346, August.
    17. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
    18. Foster, Gigi & Frijters, Paul & Schaffner, Markus & Torgler, Benno, 2018. "Expectation formation in an evolving game of uncertainty: New experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 379-405.
    19. Thomas Epper & Helga Fehr-Duda & Adrian Bruhin, 2011. "Viewing the future through a warped lens: Why uncertainty generates hyperbolic discounting," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 169-203, December.
    20. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Consumer Choice," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 803-843.

    More about this item

    Keywords

    Risk; Decision-making; First order and second order stochastic dominance; Expected utility theory; Cumulative prospect theory; Rank dependent expected utility theory; Mixture models; Non-human primates; D81; C91; C51; C12;
    All these 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

    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:kap:jrisku:v:49:y:2014:i:2:p:141-166. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.