Predicting Cooperation with Learning Models
American Economic Journal: Microeconomics
vol. 16,
no. 1, February 2024
(pp. 1-32)
Abstract
We use simulations of a simple learning model to predict cooperation rates in the experimental play of the indefinitely repeated prisoner's dilemma. We suppose that learning and the game parameters only influence play in the initial round of each supergame, and that after these rounds, play depends only on the outcome of the previous round. We find that our model predicts out-of-sample cooperation at least as well as models with more parameters and harder-to-interpret machine learning algorithms. Our results let us predict the effect of session length and help explain past findings on the role of strategic uncertainty.Citation
Fudenberg, Drew, and Gustav Karreskog Rehbinder. 2024. "Predicting Cooperation with Learning Models." American Economic Journal: Microeconomics, 16 (1): 1-32. DOI: 10.1257/mic.20220148Additional Materials
JEL Classification
- C57 Econometrics of Games and Auctions
- C72 Noncooperative Games
- C73 Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- D91 Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
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