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The Ratio Bias Phenomenon : Fact or Artifact ?

Author

Listed:
  • Mathieu Lefebvre

    (CREPP - Center of Research in Public Economics and Population Economics - Université de Liège)

  • Ferdinand Vieider

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

  • Marie Claire Villeval

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The ratio bias – according to which individuals prefer to bet on probabilities expressed as a ratio of large numbers to normatively equivalent or superior probabilities expressed as a ratio of small numbers – has recently gained momentum, with researchers especially in health economics emphasizing the policy importance of the phenomenon. Although the bias has been replicated several times, some doubts remain about its economic significance. Our two experiments show that the bias disappears once order effects are excluded, and once salient and dominant incentives are provided. This holds true for both choice and valuation tasks. Also, adding context to the decision problem does not change this outcome. No ratio bias could be found in between-subject tests either, which leads us to the conclusion that the policy relevance of the phenomenon is doubtful at best.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Mathieu Lefebvre & Ferdinand Vieider & Marie Claire Villeval, 2009. "The Ratio Bias Phenomenon : Fact or Artifact ?," Post-Print halshs-00948485, HAL.
    • Handle: RePEc:hal:journl:halshs-00948485
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    2. Chen Li & Zhihua Li & Peter Wakker, 2014. "If nudge cannot be applied: a litmus test of the readers’ stance on paternalism," Theory and Decision, Springer, vol. 76(3), pages 297-315, March.
    3. Johannes G. Jaspersen, 2016. "Hypothetical Surveys And Experimental Studies Of Insurance Demand: A Review," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 217-255, January.
    4. Lefebvre, Mathieu & Vieider, Ferdinand M. & Villeval, Marie Claire, 2010. "Incentive effects on risk attitude in small probability prospects," Economics Letters, Elsevier, vol. 109(2), pages 115-120, November.
    5. Fecher, André & Robbert, Thomas & Roth, Stefan, 2019. "Same price, different perception: Measurement-unit effects on price-level perceptions and purchase intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 129-142.
    6. Yang, Bi & Li, Shanshi & Chen, Zhenyu & Mattila, Anna S., 2023. "Consumer responses to time-based sales messages," Annals of Tourism Research, Elsevier, vol. 99(C).
    7. David Bourdin & Rudolf Vetschera, 2018. "Factors influencing the ratio bias," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 321-342, November.
    8. Christian König-Kersting & Monique Pollmann & Jan Potters & Stefan T. Trautmann, 2021. "Good decision vs. good results: Outcome bias in the evaluation of financial agents," Theory and Decision, Springer, vol. 90(1), pages 31-61, February.
    9. Lee, Yong-Ju & Cho, Hyunkuk, 2021. "Students’ preference for grading rules: The role of ratio bias," Journal of Economic Psychology, Elsevier, vol. 87(C).

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    More about this item

    Keywords

    ratio bias; financial incentives; error rates; experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I19 - Health, Education, and Welfare - - Health - - - Other

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