The collective wisdom of behavioral game theory

Shu Huang () and Russell Golman ()
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Shu Huang: Carnegie Mellon University
Russell Golman: Carnegie Mellon University

Economic Theory, 2025, vol. 79, issue 1, No 10, 356 pages

Abstract: Abstract We apply an algorithm from the wisdom-of-crowds literature to optimally combine behavioral game theory models to more accurately predict strategic choice in one-shot, simultaneous-move games. We find that the optimal weighted average of seven behavioral game theory models predicts out-of-sample choice behavior significantly better than any of the individual models. The crowd of behavioral game theory models is wiser than any single one of them. Different strategic choice models complement each other by capturing distinct patterns of behavior. The field of behavioral game theory is enriched by having this diversity of models.

Keywords: Dual accumulator model; Level-k reasoning; Model aggregation; Noisy introspection; Strategic decision making (search for similar items in EconPapers)
JEL-codes: C72 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00199-024-01571-y

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