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A Computational Approach to the Collective Action Problem: Assessment of Alternative Learning Rules

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Abstract

We sketch here the basis of a behavioral theory of non-market decision making or collective action. Departing from the basic social problem, the coordination of individual actions when individual rationality is opposed to collective rationality, we model a population of agents choosing their level of individual cooperation. The social dilemma that emerges may be solved in a bounded rationality evolutionary context. We find that the efficiency embodied in the solutions is dependent on the type of learning individuals adopt. Additional returns to the individual from collective contributions and discounting the future play key roles in the determination of the solution. We conclude that the emergent properties of the social cooperation agree with the findings in the experimental literature: cooperation, although not optimal, is a fact, and institutional settings affect the outcomes in a significant way.

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Authors and Affiliations

  1. Departamento de Economía Aplicada, Universitat de València, Av. Naranjos s/n, E-46022, València, Spain

    Juan D. Montoro-Pons & Francisco Garcia-Sobrecases

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  1. Juan D. Montoro-Pons
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  2. Francisco Garcia-Sobrecases
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Montoro-Pons, J.D., Garcia-Sobrecases, F. A Computational Approach to the Collective Action Problem: Assessment of Alternative Learning Rules. Computational Economics 21, 137–151 (2003). https://doi.org/10.1023/A:1022211603767

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