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Controlling for the Compromise Effect Debiases Estimates of Risk Preference Parameters

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  • Jonathan P. Beauchamp
  • Daniel J. Benjamin
  • Christopher F. Chabris
  • David I. Laibson

Abstract

The compromise effect arises when options near the "middle" of a choice set are more appealing. The compromise effect poses conceptual and practical problems for economic research: by influencing choices, it distorts revealed preferences, biasing researchers' inferences about deep (i.e., domain general) preferences. We propose and estimate an econometric model that disentangles and identifies both deep preferences and the context-dependent compromise effect. We demonstrate our method using data from an experiment with 550 participants who made choices over lotteries from multiple price lists. Following prior work, we manipulate the compromise effect by varying the middle options of each multiple price list and then estimate risk preferences without modelling the compromise effect. These naïve parameter estimates are not robust: they change as the compromise effect is manipulated. To eliminate this bias, we incorporate the compromise effect directly into our econometric model. We show that this method generates robust estimates of risk preference parameters that are no longer sensitive to compromise-effect manipulations. This method can be applied to other settings that exhibit the compromise effect.

Suggested Citation

  • Jonathan P. Beauchamp & Daniel J. Benjamin & Christopher F. Chabris & David I. Laibson, 2015. "Controlling for the Compromise Effect Debiases Estimates of Risk Preference Parameters," NBER Working Papers 21792, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21792
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    Cited by:

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    2. 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.
    3. James Andreoni & Michael Callen & Karrar Hussain & Muhammad Yasir Khan & Charles Sprenger, 2023. "Using Preference Estimates to Customize Incentives: An Application to Polio Vaccination Drives in Pakistan," Journal of the European Economic Association, European Economic Association, vol. 21(4), pages 1428-1477.
    4. Hunt Allcott & Judd B. Kessler, 2015. "The Welfare Effects of Nudges: A Case Study of Energy Use Social Comparisons," NBER Working Papers 21671, National Bureau of Economic Research, Inc.
    5. Ambuehl, Sandro & Li, Shengwu, 2018. "Belief updating and the demand for information," Games and Economic Behavior, Elsevier, vol. 109(C), pages 21-39.

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    More about this item

    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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