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Dynamic Voluntary Contribution to a Public Good:Learning to be a Free Rider

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  • Christiane Clemens and Thomas Riechmann

Abstract

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We find that the contribution level converges towards the Nash equilibrium although exact free rider-behavior is never observed. The latter result corresponds to findings from experiments on voluntary contribution to a public good. Crucial determinants of the learning process are the population size and the propensity to experiment.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 92.

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Date of creation: 01 Apr 2001
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Handle: RePEc:sce:scecf1:92

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Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
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Related research

Keywords: bounded rationality; evolutionary games; experiments; genetic algorithms; learning; public goods;

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Cited by:
  1. Alexis Belianin & Marco Novarese, 2005. "Trust, communication and equlibrium behaviour in public goods," Experimental 0506001, EconWPA.

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