Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/78360 
Year of Publication: 
2002
Series/Report no.: 
Diskussionsbeitrag No. 263
Publisher: 
Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Hannover
Abstract: 
This paper examines the learning dynamics of boundedly rational agents, who are asked to voluntarily contribute to a discrete public good. In an incomplete information setting, we discuss contribution games and subscription games, the latter including a money-back guarantee in case of provision failure. The theoretical results on myopic best response dynamics implying striking differences between strategies played in the two games are confirmed by simulations, where the learning process is modeled by an Evolutionary Algorithm. We show that the contribution game even aggravates the selective pressure leading towards the non-contributing equilibrium, thereby supporting results from laboratory experiments. In contrast to this, the subscription game removes the 'fear incentive', implying a higher percentage of successful provisions over time.
Subjects: 
bounded rationality
evolutionary games
evolutionary algorithm
learning
public goods
JEL: 
C6
C73
D83
H41
Document Type: 
Working Paper

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