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Modelling the effect of learning and evolving rules on the use of common-pool resources

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  • Alexander Smajgl

Abstract

The extend to which common-pool resources are used and managed sustainably depends highly on incentives. Incentives influence the behaviour of individuals with respect to natural resource management and are determined by institutional arrangements comprising of formal and informal rules and markets. Changes in institutional arrangements will affect individual incentives and will therefore have an impact on resource use. In order to model the connections between institutional arrangements and the sustainable use of common-pool resources we must take into consideration the behaviour of individuals. Game-theoretical models appear to be an adequate modelling technique with which to assess the behaviour of individuals as well as the development of institutions with regards to common-pool resource regimes. The implementation of a game-theoretical framework in the form of an agent-based model appears to be a particularly appropriate tool with which to assess common-pool resource use regimes as such models enable the behaviour of different agents to be modelled as strategies. Traditionally with agent-based models, the strategies that agents pursue are given, with their expression endogenously determined by the set of rules which govern their behaviour. In this paper I focus on the implementation of mechanisms that also allow for rules to adapt endogenously. Such an approach will be applied to common-pool resource use in order to analyse the effect of rule changes.

Suggested Citation

  • Alexander Smajgl, 2004. "Modelling the effect of learning and evolving rules on the use of common-pool resources," Computing in Economics and Finance 2004 178, Society for Computational Economics.
    • Handle: RePEc:sce:scecf4:178
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    More about this item

    Keywords

    Institutional arrangements; agent-based modelling; learning; evolving rules;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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