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Strategic Complexity and the Value of Thinking

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  • David Gill
  • Victoria Prowse

Abstract

We leverage 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 categorise situations according to 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 affects success: when a subject thinks for longer than she would normally do in a particular situation, she wins less frequently and earns less.

Suggested Citation

  • David Gill & Victoria Prowse, 2023. "Strategic Complexity and the Value of Thinking," The Economic Journal, Royal Economic Society, vol. 133(650), pages 761-786.
    • Handle: RePEc:oup:econjl:v:133:y:2023:i:650:p:761-786.
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    File URL: http://hdl.handle.net/10.1093/ej/ueac070
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    Cited by:

    1. Sebastian J. Goerg & Sebastian Kube & Jonas Radbruch, 2019. "The Effectiveness of Incentive Schemes in the Presence of Implicit Effort Costs," Management Science, INFORMS, vol. 65(9), pages 4063-4078, September.
    2. Strittmatter, Anthony & Sunde, Uwe & Zegners, Dainis, 2022. "Speed, Quality, and the Optimal Timing of Complex Decisions: Field Evidence," Rationality and Competition Discussion Paper Series 317, CRC TRR 190 Rationality and Competition.
    3. Carlos Alós-Ferrer & Johannes Buckenmaier, 2021. "Cognitive sophistication and deliberation times," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 558-592, June.
    4. Larbi Alaoui & Katharina A. Janezic & Antonio Penta, 2022. "Coordination and sophistication," Economics Working Papers 1849, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Grabiszewski, Konrad & Horenstein, Alex, 2020. "Effort is not a monotonic function of skills: Results from a global mobile experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 634-652.
    6. Alaoui, Larbi & Janezic, Katharina A. & Penta, Antonio, 2020. "Reasoning about others' reasoning," Journal of Economic Theory, Elsevier, vol. 189(C).
    7. Larbi Alaoui & Katharina A. Janezic & Antonio Penta, 2022. "Coordination and Sophistication," Working Papers 1372, Barcelona School of Economics.
    8. Alaoui, Larbi & Janezic, Katharina A. & Penta, Antonio, 2022. "Coordination and Sophistication," TSE Working Papers 22-1394, Toulouse School of Economics (TSE).
    9. Castagnetti, Alessandro & Proto, Eugenio & Sofianos, Andis, 2023. "Anger impairs strategic behavior: A Beauty-Contest based analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 128-141.
    10. Cary Frydman & Ian Krajbich, 2022. "Using Response Times to Infer Others’ Private Information: An Application to Information Cascades," Management Science, INFORMS, vol. 68(4), pages 2970-2986, April.
    11. Grabiszewski, Konrad & Horenstein, Alex, 2022. "Measuring tree complexity with response times," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).

    More about this item

    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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