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Why choice lists increase risk taking

Author

Listed:
  • David J. Freeman

    (Simon Fraser University)

  • Guy Mayraz

    (University of Melbourne)

Abstract

Choice lists with random incentives are widely used for preference elicitation. It is commonly assumed that subjects choose the same option in each question as they would have if it were the only question, but recent findings challenge this assumption. We conduct a large sample experiment varying incentives and presentation independently, and examine choices both near and away from certainty. We consistently find more risk taking when a choice between a safe prize and a risky lottery is embedded in a choice list than when it is presented on its own. This difference remains when we inform subjects of the paid choice in advance, implying that isolation fails not because of the random incentives scheme, but simply because the choice appears in a list together with others. We conjecture that subjects are uncertain about their preferences, reduce this uncertainty through considering the choices that confront them, and make cautious decisions in the interim. Other conditions and non-choice data support this interpretation. Our results open up the possibility that preferences inferred from choice lists offer a better indication of informed preferences than preferences inferred from single choices.

Suggested Citation

  • David J. Freeman & Guy Mayraz, 2019. "Why choice lists increase risk taking," Experimental Economics, Springer;Economic Science Association, vol. 22(1), pages 131-154, March.
    • Handle: RePEc:kap:expeco:v:22:y:2019:i:1:d:10.1007_s10683-018-9586-z
    DOI: 10.1007/s10683-018-9586-z
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    2. Villacis, Alexis H., 2023. "Inconsistent choices over prospect theory lottery games: Evidence from field experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    3. Aurélien Baillon & Yoram Halevy & Chen Li, 2022. "Randomize at Your Own Risk: On the Observability of Ambiguity Aversion," Econometrica, Econometric Society, vol. 90(3), pages 1085-1107, May.
    4. Zhihua Li & Songfa Zhong, 2023. "Reference Dependence in Intertemporal Preference," Management Science, INFORMS, vol. 69(1), pages 475-490, January.
    5. Larry G. Epstein & Yoram Halevy, 2019. "Hard-to-Interpret Signals," Working Papers tecipa-634, University of Toronto, Department of Economics.
    6. Kim, Tami & Martin, Daniel, 2021. "What do consumers learn from regulator ratings? Evidence from restaurant hygiene quality disclosures," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 234-249.
    7. Banerjee, Priyodorshi & Das, Tanmoy, 2019. "Simultaneous decisions under risk: An experimental investigation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 82(C).
    8. Yoram Halevy & Guy Mayraz, 2020. "Identifying Rule-Based Rationality," Working Papers tecipa-677, University of Toronto, Department of Economics.
    9. Ingrid Burfurd & Tom Wilkening, 2022. "Cognitive heterogeneity and complex belief elicitation," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 557-592, April.

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    More about this item

    Keywords

    Choice lists; Random incentive scheme; Discovered preferences; Presentation effect;
    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

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