Dynamic Voluntary Contribution to a Public Good:Learning to be a Free Rider
AbstractThis 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 InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 92.
Date of creation: 01 Apr 2001
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Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
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bounded rationality; evolutionary games; experiments; genetic algorithms; learning; public goods;
Other versions of this item:
- Clemens, Christiane & Riechmann, Thomas, 2001. "Dynamic Voluntary Contribution to a Public Good: Learning to be a Free Rider," Diskussionspapiere der Wirtschaftswissenschaftlichen FakultÃ¤t der Leibniz UniversitÃ¤t Hannover dp-240, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
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- Alexis Belianin & Marco Novarese, 2005. "Trust, communication and equlibrium behaviour in public goods," Experimental 0506001, EconWPA.
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