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Lossed in translation: an off-the-shelf method to recover probabilistic beliefs from loss-averse agents

Author

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  • Theo Offerman

    () (CREED, University of Amsterdam)

  • Asa B. Palley

    () (Duke University)

Abstract

Abstract Strictly proper scoring rules are designed to truthfully elicit subjective probabilistic beliefs from risk neutral agents. Previous experimental studies have identified two problems with this method: (i) risk aversion causes agents to bias their reports toward the probability of $$1/2$$ 1 / 2 , and (ii) for moderate beliefs agents simply report $$1/2$$ 1 / 2 . Applying a prospect theory model of risk preferences, we show that loss aversion can explain both of these behavioral phenomena. Using the insights of this model, we develop a simple off-the-shelf probability assessment mechanism that encourages loss-averse agents to report true beliefs. In an experiment, we demonstrate the effectiveness of this modification in both eliminating uninformative reports and eliciting true probabilistic beliefs.

Suggested Citation

  • Theo Offerman & Asa B. Palley, 2016. "Lossed in translation: an off-the-shelf method to recover probabilistic beliefs from loss-averse agents," Experimental Economics, Springer;Economic Science Association, vol. 19(1), pages 1-30, March.
  • Handle: RePEc:kap:expeco:v:19:y:2016:i:1:d:10.1007_s10683-015-9429-0
    DOI: 10.1007/s10683-015-9429-0
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    References listed on IDEAS

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    More about this item

    Keywords

    Scoring rule; Subjective probability assessment; Loss aversion; Prospect theory;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • 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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