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Probability Weighting and Cognitive Ability

Author

Listed:
  • Syngjoo Choi

  • Jeongbin Kim

  • Eungik Lee

  • Jungmin Lee

Abstract

Probability weighting is a major concept for accommodating systemic departures from expected utility theory. We examine the relation between probability weighting and cognitive ability by conducting laboratory experiments with a pool of subjects with unusually large variation in cognitive ability; native-born South Koreans and North Korean refugees. We find that cognitive ability is related to two distinct features of probability weighting-likelihood insensitivity and optimism. Particularly, the negative association between likelihood insensitivity and cognitive ability is robust to potential confounders and stronger among lower cognitive-ability subjects. Our findings shed light on the sources of anomalous choices against expected utility theory.

Suggested Citation

  • Syngjoo Choi & Jeongbin Kim & Eungik Lee & Jungmin Lee, 2018. "Probability Weighting and Cognitive Ability," Working Paper Series no121, Institute of Economic Research, Seoul National University.
    • Handle: RePEc:snu:ioerwp:no121
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    Cited by:

    1. Roger, Patrick & D’Hondt, Catherine & Plotkina, Daria & Hoffmann, Arvid, 2022. "Number 19: Another Victim of the COVID‐19 Pandemic?," LIDAM Reprints LFIN 2022012, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Capezzone, Tommaso & Conzo, Pierluigi & Fuochi, Giulia & Zotti, Roberto & Anfossi, Laura & Mosso, Cristina Onesta, 2025. "We care, but delegate: Climate disasters and climate migration trigger concern, normative beliefs, and altruism – but not cooperation," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202511, University of Turin.
    3. Daniel Woods & Mustafa Abdallah & Saurabh Bagchi & Shreyas Sundaram & Timothy Cason, 2022. "Network defense and behavioral biases: an experimental study," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 254-286, February.
    4. Yu Gao & Zhenxing Huang & Ning Liu & Jia Yang, 2024. "Are physicians rational under ambiguity?," Journal of Risk and Uncertainty, Springer, vol. 68(2), pages 183-203, April.
    5. Choi, Syngjoo & Hahn, Kyu Sup & Kim, Byung-Yeon & Lee, Eungik & Lee, Jungmin & Lee, Sokbae, 2024. "North Korean refugees’ implicit bias against South Korea predicts market earnings," Journal of Development Economics, Elsevier, vol. 169(C).
    6. Andrew Caplin & David J. Deming & Søren Leth-Petersen & Ben Weidmann, 2023. "Economic Decision-Making Skill Predicts Income in Two Countries," NBER Working Papers 31674, National Bureau of Economic Research, Inc.
    7. Adam Dominiak & Peter Duersch, 2024. "Choice under uncertainty and cognitive load," Journal of Risk and Uncertainty, Springer, vol. 68(2), pages 133-161, April.
    8. Yui Law & Sinchit Lai & Ning Liu, 2025. "Leniency experiments: an evaluation of external validity," European Journal of Law and Economics, Springer, vol. 59(1), pages 19-76, February.
    9. Masahide Watanabe & Toshio Fujimi, 2024. "Ambiguity attitudes toward natural and artificial sources in gain and loss domains," Journal of Risk and Uncertainty, Springer, vol. 68(1), pages 51-75, February.

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    Keywords

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    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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