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The Ratio Bias Phenomenon : Fact or Artifact ?

Author

Listed:
  • Mathieu Lefebvre

    (University of Liège, CREPP; Boulevard du Rectorat, 7 Bâtiment 31, boîte 39, 4000 Liège, Belgium)

  • Ferdinand Vieider

    (University Lyon 2, Lyon, F-69007, France; CNRS, GATE, 93, Chemin de Mouilles Ecully, F- 69130, France, and DIW, Berlin, Germany)

  • Marie-Claire Villeval

    (University Lyon 2, Lyon, F-69007, France; CNRS, GATE, 93, Chemin de Mouilles Ecully, F- 69130, France, IZA, Bonn, Germany, and CCP, Aarhus, Denmark)

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.

Suggested Citation

  • Mathieu Lefebvre & Ferdinand Vieider & Marie-Claire Villeval, 2009. "The Ratio Bias Phenomenon : Fact or Artifact ?," Working Papers 0925, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    • Handle: RePEc:gat:wpaper:0925
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    Cited by:

    1. Filiz-Ozbay, Emel & Gulen, Huseyin & Masatlioglu, Yusufcan & Ozbay, Erkut Y., 2022. "Comparing ambiguous urns with different sizes," Journal of Economic Theory, Elsevier, vol. 199(C).
    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. 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).
    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. 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.
    6. Lee, Yong-Ju & Cho, Hyunkuk, 2021. "Students’ preference for grading rules: The role of ratio bias," Journal of Economic Psychology, Elsevier, vol. 87(C).
    7. 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.
    8. 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.
    9. 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.

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    Keywords

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    JEL classification:

    • 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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