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Common ratio and common consequence effects arise from true preferences

Author

Listed:
  • Carlos Alós-Ferrer
  • Ernst Fehr
  • Helga Fehr-Duda
  • Michele Garagnani

Abstract

Recent contributions suggest that the empirical evidence for the common ratio effect could be explained as noise instead of underlying preferences under “common assumptions.” We revisit this argument using a more general method which allows to unambiguously dis- tinguish noise from preferences nonparametrically and with less stringent assumptions. The results are independent of the assumed behavioral model or how noise affects choices. Ap- plying this method to new experimental data we show that there is a systematic preference for the common ratio and the common consequence effects which cannot be explained by noise.

Suggested Citation

  • Carlos Alós-Ferrer & Ernst Fehr & Helga Fehr-Duda & Michele Garagnani, 2024. "Common ratio and common consequence effects arise from true preferences," ECON - Working Papers 459, Department of Economics - University of Zurich.
    • Handle: RePEc:zur:econwp:459
    as

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    File URL: https://www.zora.uzh.ch/id/eprint/264661/1/econwp459.pdf
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    References listed on IDEAS

    as
    1. Jose Apesteguia & Miguel A. Ballester, 2018. "Monotone Stochastic Choice Models: The Case of Risk and Time Preferences," Journal of Political Economy, University of Chicago Press, vol. 126(1), pages 74-106.
    2. Carlos Alós-Ferrer & Ernst Fehr & Nick Netzer, 2021. "Time Will Tell: Recovering Preferences When Choices Are Noisy," Journal of Political Economy, University of Chicago Press, vol. 129(6), pages 1828-1877.
    3. Carlos Alós-Ferrer & Michele Garagnani, 2024. "Improving Risky-Choice Predictions Using Response Times," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 2(2), pages 335-354.
    4. Marina Agranov & Pietro Ortoleva, 2017. "Stochastic Choice and Preferences for Randomization," Journal of Political Economy, University of Chicago Press, vol. 125(1), pages 40-68.
    5. Ian Bateman & Brett Day & Graham Loomes & Robert Sugden, 2007. "Can ranking techniques elicit robust values?," Journal of Risk and Uncertainty, Springer, vol. 34(1), pages 49-66, February.
    6. Carlo Baldassi & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Marco Pirazzini, 2020. "A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure," Management Science, INFORMS, vol. 66(11), pages 5075-5093, November.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • 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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