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Getting It Right the First Time: Belief Elicitation with Novice Participants

Author

Listed:
  • Li Hao

    () (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

  • Daniel Houser

    () (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

Abstract

The auction design literature makes clear that theoretically equivalent mechanisms can perform very differently in practice. Though of equal importance, much less is known about the empirical performance of theoretically equivalent mechanisms for belief elicitation. This is especially unfortunate given the increasing interest in eliciting beliefs from (often novice) respondents in large-scale surveys. Using laboratory experiments with novice participants endowed with heterogeneous beliefs, we compare the empirical merit of two belief elicitation mechanisms proposed by Karni (2009), which we denote as ÒdeclarativeÓ and Òclock.Ó These mechanisms are of interest because incentive compatibility does not require strong assumptions such as risk neutrality or expected utility maximization. Our key findings are that under the clock mechanism, (i) subjects are more likely to report their beliefs truthfully; and (ii) the distribution of elicited beliefs more accurately characterizes the true belief distribution. Our findings have substantial practical value to anyone wishing to elicit beliefs from novice respondents, a goal of increasing importance to large-scale survey design.

Suggested Citation

  • Li Hao & Daniel Houser, 2010. "Getting It Right the First Time: Belief Elicitation with Novice Participants," Working Papers 1015, George Mason University, Interdisciplinary Center for Economic Science.
  • Handle: RePEc:gms:wpaper:1015
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    File URL: http://www.gmu.edu/schools/chss/economics/icesworkingpapers.gmu.edu/pdf/1015.pdf
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    Citations

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    Cited by:

    1. Stefan T. Trautmann & Gijs Kuilen, 2015. "Belief Elicitation: A Horse Race among Truth Serums," Economic Journal, Royal Economic Society, vol. 125(589), pages 2116-2135, December.
    2. 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.
    3. David Owens Jr. & Zachary Grossman Jr. & Ryan Fackler Jr., 2014. "The Control Premium: A Preference for Payoff Autonomy," American Economic Journal: Microeconomics, American Economic Association, vol. 6(4), pages 138-161, November.

    More about this item

    Keywords

    probabilistic belief elicitation; declarative mechanism; clock mechanism; proper scoring rules; laboratory experiment;

    JEL classification:

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

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