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Using Response Times to Measure Strategic Complexity and the Value of Thinking in Games

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  • Gill, David

    () (Purdue University)

  • Prowse, Victoria L.

    () (Purdue University)

Abstract

Response times are a simple low-cost indicator of the process of reasoning in strategic games (Rubinstein, 2007; Rubinstein, 2016). We leverage the dynamic nature of response-time data from repeated strategic interactions to measure the strategic complexity of a situation by how long people think on average when they face that situation (where we define situations according to the characteristics of play in the previous round). We find that strategic complexity varies significantly across situations, and we find considerable heterogeneity in how responsive subjects' thinking times are to complexity. We also study how variation in response times at the individual level across rounds affects strategic behavior and success. We find that 'overthinking' is detrimental to performance: when a subject thinks for longer than she would normally do in a particular situation, she wins less frequently and earns less. The behavioral mechanism that drives the reduction in performance is a tendency to move away from Nash equilibrium behavior.

Suggested Citation

  • Gill, David & Prowse, Victoria L., 2017. "Using Response Times to Measure Strategic Complexity and the Value of Thinking in Games," IZA Discussion Papers 10518, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp10518
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    Cited by:

    1. Larbi Alaoui & Antonio Penta, 2017. "Reasoning about others’ reasoning," Economics Working Papers 1587, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Larbi Alaoui & Antonio Penta, 2017. "Reasoning about Others’ Reasoning," Working Papers 1003, Barcelona Graduate School of Economics.

    More about this item

    Keywords

    response time; decision time; thinking time; strategic complexity; game theory; strategic games; repeated games; beauty contest; cognitive ability; personality;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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