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Naive play and the process of choice in guessing games

Author

Listed:
  • Marina Agranov

    (California Institute of Technology and the Center for Experimental Social Science)

  • Andrew Caplin

    (New York University and the Center for Experimental Social Science)

  • Chloe Tergiman

    (University of British Columbia and the Center for Experimental Social Science)

Abstract

There is growing evidence that not all experimental subjects understand their strategic environment. We introduce a “choice process” (CP) protocol that aids in identifying these subjects. This protocol elicits in an incentive compatible manner provisional choices as players internalize their decision making environment. We implement the CP protocol in the modified 2/3 guessing game and use it to pinpoint players that are naive by identifying those who make weakly dominated choices some time into the play. At all time horizons these players average close to 50. This is consistent with the assumption in Level-K theory that the least sophisticated subjects (the naive ones) play uniformly over the [1–100] action space. In contrast, sophisticated players show evidence of increased understanding as time passes. We find that the CP protocol mirrors play in multiple setups with distinct time constraints. Hence it may be worth deploying more broadly to understand the interaction between decision time and choice.

Suggested Citation

  • Marina Agranov & Andrew Caplin & Chloe Tergiman, 2015. "Naive play and the process of choice in guessing games," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(2), pages 146-157, December.
    • Handle: RePEc:spr:jesaex:v:1:y:2015:i:2:d:10.1007_s40881-015-0003-5
    DOI: 10.1007/s40881-015-0003-5
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Experiment; 2/3 Guessing game; Level 0 play;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • 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

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