IDEAS home Printed from https://ideas.repec.org/p/mag/wpaper/09014.html
   My bibliography  Save this paper

Different methods to define utility functions yield different results and engage different neural processes

Author

Listed:
  • Heldmann, Marcus

    (Otto-von-Guericke University Magdeburg)

  • Vogt, Bodo

    (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)

  • Heinze, Hans-Jochen

    (Otto-von-Guericke University Magdeburg)

  • Münte, Thomas

    (Otto-von-Guericke University Magdeburg)

Abstract

Although the concept of utility is fundamental to many economic theories, up to now a generally accepted method determining a subject’s utility function is not available. We investigated two methods that are used in economic sciences for describing utility functions by using response-locked event-related potentials in order to assess their neural underpinnings. For defining the certainty equivalent (CE), we used a lottery game with probabilities of 0.5, for identifying the subjects’ utility functions directly a standard bisection task was applied. Although the lottery tasks’ payoffs were only hypothetical, a pronounced negativity was observed resembling the error related negativity (ERN) previously described in action monitoring research, but this occurred only for choices far away from the indifference point between money and lottery. By contrast, the bisection task failed to evoke an ERN irrespective of the responses’ correctness. Based on these findings we are reasoning that only decisions made in the lottery task achieved a level of subjective relevance that activates cognitive-emotional monitoring. In terms of economic sciences, our findings support the view that the bisection method is unaffected by any kind of probability valuation or other parameters related to risk and in combination with the lottery task can, therefore, be used to differentiate between payoff and probability valuation.

Suggested Citation

  • Heldmann, Marcus & Vogt, Bodo & Heinze, Hans-Jochen & Münte, Thomas, 2009. "Different methods to define utility functions yield different results and engage different neural processes," FEMM Working Papers 09014, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
  • Handle: RePEc:mag:wpaper:09014
    as

    Download full text from publisher

    File URL: http://www.ww.uni-magdeburg.de/fwwdeka/femm/a2009_Dateien/2009_14.pdf
    File Function: First version, 2009
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-824, December.
    3. Albers Wulf & Pope Robin & Vogt Bodo & Selten Reinhard, 2000. "Experimental Evidence for Attractions to Chance," German Economic Review, De Gruyter, vol. 1(2), pages 113-130, May.
    4. 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..
    5. David E. Bell, 1985. "Disappointment in Decision Making Under Uncertainty," Operations Research, INFORMS, vol. 33(1), pages 1-27, February.
    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. Dolgikh, Sofiia, 2019. "The influence of subjective beliefs in luck on the decision-making under risk: TV show analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 74-98.

    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. Pope, Robin & Leitner, Johannes & Leopold-Wildburger, Ulrike, 2009. "Expected utility versus the changes in knowledge ahead," European Journal of Operational Research, Elsevier, vol. 199(3), pages 892-901, December.
    2. Enrico G. De Giorgi & Thierry Post, 2011. "Loss Aversion with a State-Dependent Reference Point," Management Science, INFORMS, vol. 57(6), pages 1094-1110, June.
    3. Ronald Bosman & Frans Van Winden, 2010. "Global Risk, Investment and Emotions," Economica, London School of Economics and Political Science, vol. 77(307), pages 451-471, July.
    4. Ivan Barreda-Tarrazona & Ainhoa Jaramillo-Gutierrez & Daniel Navarro-Martinez & Gerardo Sabater-Grande, 2014. "The role of forgone opportunities in decision making under risk," Journal of Risk and Uncertainty, Springer, vol. 49(2), pages 167-188, October.
    5. Wang, Di, 2021. "Attention-driven probability weighting," Economics Letters, Elsevier, vol. 203(C).
    6. Servaas van Bilsen & Roger J. A. Laeven & Theo E. Nijman, 2020. "Consumption and Portfolio Choice Under Loss Aversion and Endogenous Updating of the Reference Level," Management Science, INFORMS, vol. 66(9), pages 3927-3955, September.
    7. Astrid Hopfensitz & Frans Winden, 2008. "Dynamic Choice, Independence and Emotions," Theory and Decision, Springer, vol. 64(2), pages 249-300, March.
    8. Zhenzhen Ma & Jianjun Zhu & Shitao Zhang, 2021. "Probabilistic-based expressions in behavioral multi-attribute decision making considering pre-evaluation," Fuzzy Optimization and Decision Making, Springer, vol. 20(1), pages 145-173, March.
    9. repec:cup:judgdm:v:16:y:2021:i:6:p:1324-1369 is not listed on IDEAS
    10. Jiakun Zheng, 2020. "Optimal insurance design under narrow framing," Post-Print hal-04227370, HAL.
    11. Zheng, Jiakun, 2020. "Optimal insurance design under narrow framing," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 596-607.
    12. Lieder, Falk & Griffiths, Tom & Hsu, Ming, 2016. "Over-representation of extreme events in decision-making reflects rational use of cognitive resources," OSF Preprints kxxag, Center for Open Science.
    13. Alessandra Cillo & Marco Bonetti & Giovanni Burro & Clelia Di Serio & Roberta De Filippis & Riccardo Maria Martoni, 2019. "Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-16, February.
    14. Zhihua Li & Songfa Zhong, 2023. "Reference Dependence in Intertemporal Preference," Management Science, INFORMS, vol. 69(1), pages 475-490, January.
    15. Graham Loomes & Ganna Pogrebna, 2014. "Testing for independence while allowing for probabilistic choice," Journal of Risk and Uncertainty, Springer, vol. 49(3), pages 189-211, December.
    16. Weber, Bethany J. & Chapman, Gretchen B., 2005. "Playing for peanuts: Why is risk seeking more common for low-stakes gambles?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 97(1), pages 31-46, May.
    17. Herweg, Fabian & Müller, Daniel, 2021. "A comparison of regret theory and salience theory for decisions under risk," Journal of Economic Theory, Elsevier, vol. 193(C).
    18. Pavlo Blavatskyy, 2018. "A second-generation disappointment aversion theory of decision making under risk," Theory and Decision, Springer, vol. 84(1), pages 29-60, January.
    19. Toritseju Begho & Kelvin Balcombe, 2023. "Attitudes to Risk and Uncertainty: New Insights From an Experiment Using Interval Prospects," SAGE Open, , vol. 13(3), pages 21582440231, July.
    20. Doron Sonsino, 2008. "Disappointment Aversion in internet Bidding-Decisions," Theory and Decision, Springer, vol. 64(2), pages 363-393, March.
    21. Sudeep Bhatia & Graham Loomes & Daniel Read, 2021. "Establishing the laws of preferential choice behavior," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(6), pages 1324-1369, November.

    More about this item

    Keywords

    Utility function; neuroeconomics; error-related negativity; executive functions; cognitive electrophysiology; lottery; bisection;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:mag:wpaper:09014. 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: Guido Henkel (email available below). General contact details of provider: https://edirc.repec.org/data/fwmagde.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.