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Cognitive Imprecision and Small-Stakes Risk Aversion
[Linear Mapping of Numbers onto Space Requires Attention]

Author

Listed:
  • Mel Win Khaw
  • Ziang Li
  • Michael Woodford

Abstract

Observed choices between risky lotteries are difficult to reconcile with expected utility maximization, both because subjects appear to be too risk averse with regard to small gambles for this to be explained by diminishing marginal utility of wealth, as stressed by Rabin (2000), and because subjects’ responses involve a random element. We propose a unified explanation for both anomalies, similar to the explanation given for related phenomena in the case of perceptual judgments: they result from judgments based on imprecise (and noisy) mental representations of the decision situation. In this model, risk aversion results from a sort of perceptual bias—but one that represents an optimal decision rule, given the limitations of the mental representation of the situation. We propose a quantitative model of the noisy mental representation of simple lotteries, based on other evidence regarding numerical cognition, and test its ability to explain the choice frequencies that we observe in a laboratory experiment.

Suggested Citation

  • Mel Win Khaw & Ziang Li & Michael Woodford, 2021. "Cognitive Imprecision and Small-Stakes Risk Aversion [Linear Mapping of Numbers onto Space Requires Attention]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1979-2013.
  • Handle: RePEc:oup:restud:v:88:y:2021:i:4:p:1979-2013.
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    File URL: http://hdl.handle.net/10.1093/restud/rdaa044
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    References listed on IDEAS

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    3. Duffy, Sean & Gussman, Steven & Smith, John, 2021. "Visual judgments of length in the economics laboratory: Are there brains in stochastic choice?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
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    6. Ball, Sheryl & Katz, Benjamin & Li, Flora & Smith, Alec, 2023. "The effect of cognitive load on economic decision-making: a replication attempt," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 226-242.
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    8. Zachary Breig & Paul Feldman, 2024. "Revealing risky mistakes through revisions," Journal of Risk and Uncertainty, Springer, vol. 68(3), pages 227-254, June.
    9. Benjamin Enke & Cassidy Shubatt, 2023. "Quantifying Lottery Choice Complexity," CESifo Working Paper Series 10644, CESifo.
    10. Fakir, Adnan M.S., 2021. "Schooling and small stakes risk aversion: Insights from a rural-poor community," Economics Letters, Elsevier, vol. 207(C).
    11. Pedro Bordalo & John Conlon & Nicola Gennaioli & Spencer Kwon & Andrei Shleifer, 2023. "How People Use Statistics," Working Papers 699, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    12. Chew, Soo Hong & Miao, Bin & Shen, Qiang & Zhong, Songfa, 2022. "Multiple-switching behavior in choice-list elicitation of risk preference," Journal of Economic Theory, Elsevier, vol. 204(C).
    13. Filip-Mihai Toma & Cosmin-Octavian Cepoi & Matei Nicolae Kubinschi & Makoto Miyakoshi, 2023. "Gazing through the bubble: an experimental investigation into financial risk-taking using eye-tracking," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    14. Alós-Ferrer, Carlos & Garagnani, Michele, 2022. "The gradual nature of economic errors," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 55-66.
    15. Pedro Bordalo & Giovanni Burro & Katherine Coffman & Nicola Gennaioli & Andrei Shleifer, 2023. "Imagining the Future: Memory, Simulation and Beliefs," Working Papers 701, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    16. 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.

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