IDEAS home Printed from https://ideas.repec.org/p/lan/wpaper/400814269.html
   My bibliography  Save this paper

Testing Models of Complexity Aversion

Author

Listed:
  • Konstantinos Georgalos
  • Nathan Nabil

Abstract

In this paper we aim to investigate how the complexity of a decision-task may change an agents strategic behaviour as a result of increased cognitive fatigue. In this framework, complexity is defined as a function of the number of outcomes in a lottery. Using Bayesian inference techniques, we quantitatively specify and estimate adaptive toolbox models of cognition, which we rigorously test against popular expectation based models; modified to account for complexity aversion. We find that for the majority of the subjects, a toolbox model performs best both in-sample, and with regards to its predictive capacity out-of-sample, suggesting that individuals result to heuristics when the complexity of a task overwhelms their cognitive load.

Suggested Citation

  • Konstantinos Georgalos & Nathan Nabil, 2023. "Testing Models of Complexity Aversion," Working Papers 400814269, Lancaster University Management School, Economics Department.
    • Handle: RePEc:lan:wpaper:400814269
    as

    Download full text from publisher

    File URL: http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lums/economics/working-papers/LancasterWP2023_011.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. B. Douglas Bernheim & Charles Sprenger, 2020. "On the Empirical Validity of Cumulative Prospect Theory: Experimental Evidence of Rank‐Independent Probability Weighting," Econometrica, Econometric Society, vol. 88(4), pages 1363-1409, July.
    2. Kelvin Balcombe & Iain Fraser, 2015. "Parametric preference functionals under risk in the gain domain: A Bayesian analysis," Journal of Risk and Uncertainty, Springer, vol. 50(2), pages 161-187, April.
    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. Stefan Zeisberger, 2022. "Do people care about loss probabilities?," Journal of Risk and Uncertainty, Springer, vol. 65(2), pages 185-213, October.
    5. Aurélien Baillon & Han Bleichrodt & Vitalie Spinu, 2020. "Searching for the Reference Point," Management Science, INFORMS, vol. 66(1), pages 93-112, January.
    6. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
    7. Huck, Steffen & Weizsacker, Georg, 1999. "Risk, complexity, and deviations from expected-value maximization: Results of a lottery choice experiment," Journal of Economic Psychology, Elsevier, vol. 20(6), pages 699-715, December.
    8. Dale O. Stahl, 2018. "An Empirical Evaluation of the Toolbox Model of Lottery Choices," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 528-534, July.
    9. Alina Ferecatu & Ayse Önçüler, 2016. "Heterogeneous risk and time preferences," Journal of Risk and Uncertainty, Springer, vol. 53(1), pages 1-28, August.
    10. Viscusi, W Kip, 1989. "Prospective Reference Theory: Toward an Explanation of the Paradoxes," Journal of Risk and Uncertainty, Springer, vol. 2(3), pages 235-263, September.
    11. Stefania Sitzia & Daniel Zizzo, 2011. "Does product complexity matter for competition in experimental retail markets?," Theory and Decision, Springer, vol. 70(1), pages 65-82, January.
    12. Enrico Diecidue & Moshe Levy & Jeroen Ven, 2015. "No aspiration to win? An experimental test of the aspiration level model," Journal of Risk and Uncertainty, Springer, vol. 51(3), pages 245-266, December.
    13. Giorgio Coricelli & Enrico Diecidue & Francesco D. Zaffuto, 2018. "Evidence for multiple strategies in choice under risk," Journal of Risk and Uncertainty, Springer, vol. 56(2), pages 193-210, April.
    14. 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.
    15. Peter Moffatt & Stefania Sitzia & Daniel Zizzo, 2015. "Heterogeneity in preferences towards complexity," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 147-170, October.
    16. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
    17. Spyros Makridakis & Robert L. Winkler, 1983. "Averages of Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 29(9), pages 987-996, September.
    18. John Payne, 2005. "It is Whether You Win or Lose: The Importance of the Overall Probabilities of Winning or Losing in Risky Choice," Journal of Risk and Uncertainty, Springer, vol. 30(1), pages 5-19, January.
    Full references (including those not matched with items on IDEAS)

    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. Konstantinos Georgalos & Nathan Nabil, 2023. "Heuristics Unveiled," Working Papers 400814162, Lancaster University Management School, Economics Department.
    2. Lisheng He & Pantelis P. Analytis & Sudeep Bhatia, 2022. "The Wisdom of Model Crowds," Management Science, INFORMS, vol. 68(5), pages 3635-3659, May.
    3. Wakker, Peter P., 2023. "A criticism of Bernheim & Sprenger's (2020) tests of rank dependence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    4. Oberholzer, Yvonne & Olschewski, Sebastian & Scheibehenne, Benjamin, 2024. "Complexity aversion in risky choices and valuations: Moderators and possible causes," Journal of Economic Psychology, Elsevier, vol. 100(C).
    5. Konstantinos Georgalos & Ivan Paya & David Peel, 2023. "Higher order risk attitudes: new model insights and heterogeneity of preferences," Experimental Economics, Springer;Economic Science Association, vol. 26(1), pages 145-192, March.
    6. 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.
    7. Arts, Sara & Ong, Qiyan & Qiu, Jianying, 2020. "Measuring subjective decision confidence," MPRA Paper 117907, University Library of Munich, Germany.
    8. Larbi Alaoui & Antonio Penta, 2022. "Attitudes towards success and failure," Economics Working Papers 1831, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Levy, Moshe, 2022. "An inter-temporal CAPM based on First order Stochastic Dominance," European Journal of Operational Research, Elsevier, vol. 298(2), pages 734-739.
    10. Giorgio Coricelli & Enrico Diecidue & Francesco D. Zaffuto, 2018. "Evidence for multiple strategies in choice under risk," Journal of Risk and Uncertainty, Springer, vol. 56(2), pages 193-210, April.
    11. Stefan Zeisberger, 2022. "Do people care about loss probabilities?," Journal of Risk and Uncertainty, Springer, vol. 65(2), pages 185-213, October.
    12. Arts, Sara & Ong, Qiyan & Qiu, Jianying, 2020. "Measuring subjective decision confidence," MPRA Paper 106811, University Library of Munich, Germany.
    13. Larbi Alaoui & Antonio Penta, 2022. "Attitudes Towards Success and Failure," Working Papers 1336, Barcelona School of Economics.
    14. Ori Plonsky & Yefim Roth & Ido Erev, 2021. "Underweighting of rare events in social interactions and its implications to the design of voluntary health applications," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(2), pages 267-289, March.
    15. Peter Moffatt & Stefania Sitzia & Daniel Zizzo, 2015. "Heterogeneity in preferences towards complexity," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 147-170, October.
    16. Alex Markle & George Wu & Rebecca White & Aaron Sackett, 2018. "Goals as reference points in marathon running: A novel test of reference dependence," Journal of Risk and Uncertainty, Springer, vol. 56(1), pages 19-50, February.
    17. Brice Corgnet & Roberto Hernán González, 2023. "On The Appeal Of Complexity," Working Papers 2312, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    18. Han Bleichrodt & Olivier L’haridon, 2023. "Prospect theory’s loss aversion is robust to stake size," Post-Print hal-04126663, HAL.
    19. repec:cup:judgdm:v:16:y:2021:i:2:p:267-289 is not listed on IDEAS
    20. repec:cup:judgdm:v:8:y:2013:i:3:p:214-235 is not listed on IDEAS
    21. Birnbaum, Michael H., 2007. "Tests of branch splitting and branch-splitting independence in Allais paradoxes with positive and mixed consequences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(2), pages 154-173, March.
    22. Eyal Ert & Ido Erev, 2013. "On the descriptive value of loss aversion in decisions under risk: Six clarifications," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(3), pages 214-235, May.

    More about this item

    Keywords

    Complexity aversion; Toolbox models; Heuristics; Risky choice; Bayesian modelling;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    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:lan:wpaper:400814269. 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: Giorgio Motta (email available below). General contact details of provider: https://edirc.repec.org/data/delanuk.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.