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Measuring and controlling for the compromise effect when estimating risk preference parameters

Author

Listed:
  • Jonathan P. Beauchamp

    (George Mason University)

  • Daniel J. Benjamin

    (University of Southern California
    NBER)

  • David I. Laibson

    (NBER
    Harvard University)

  • Christopher F. Chabris

    (Geisinger Health Systems)

Abstract

The compromise effect arises when being close to the “middle” of a choice set makes an option more appealing. The compromise effect poses conceptual and practical problems for economic research: by influencing choices, it can bias researchers’ inferences about preference parameters. To study this bias, we conduct an experiment with 550 participants who made choices over lotteries from multiple price lists (MPLs). Following prior work, we manipulate the compromise effect to influence choices by varying the middle options of each MPL. We then estimate risk preferences using a discrete-choice model without a compromise effect embedded in the model. As anticipated, the resulting risk preference parameter estimates are not robust, changing as the compromise effect is manipulated. To disentangle risk preference parameters from the compromise effect and to measure the strength of the compromise effect, we augment our discrete-choice model with additional parameters that represent a rising penalty for expressing an indifference point further from the middle of the ordered MPL. Using this method, we estimate an economically significant magnitude for the compromise effect and generate robust estimates of risk preference parameters that are no longer sensitive to compromise-effect manipulations.

Suggested Citation

  • Jonathan P. Beauchamp & Daniel J. Benjamin & David I. Laibson & Christopher F. Chabris, 2020. "Measuring and controlling for the compromise effect when estimating risk preference parameters," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1069-1099, December.
  • Handle: RePEc:kap:expeco:v:23:y:2020:i:4:d:10.1007_s10683-019-09640-z
    DOI: 10.1007/s10683-019-09640-z
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    Cited by:

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    2. Zhihua Li & Songfa Zhong, 2023. "Reference Dependence in Intertemporal Preference," Management Science, INFORMS, vol. 69(1), pages 475-490, January.
    3. Yuta Kittaka & Ryo Mikami & Natsumi Shimada, 2021. "Passive or Active? Behavioral changes in different designs of search experiments," ISER Discussion Paper 1148, Institute of Social and Economic Research, Osaka University.
    4. 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.
    5. Changkuk Im, 2023. "Accurate Quality Elicitation in a Multi-Attribute Choice Setting," Papers 2309.00114, arXiv.org, revised Dec 2023.
    6. Yuta Kittaka & Ryo Mikami & Natsumi Shimada, 2021. "Behavioral changes in different designs of search experiments," ISER Discussion Paper 1148r, Institute of Social and Economic Research, Osaka University, revised Jun 2022.

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    More about this item

    Keywords

    Compromise effect; Cumulative prospect theory; Loss aversion; Risk preferences;
    All these keywords.

    JEL classification:

    • B49 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Other
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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