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Incentives to Cooperate in Network Formation

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Author Info
Haydée Lugo () (Cómputo Científico y Estadística Universidad Simón Bolívar)

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Abstract

We propose a mechanism based on taxes and subsidies that enhances high cooperation in evolutionary networks. The interactions among agents are based on a Prisoners' Dilemma game in which each agent plays the same strategy with its local neighbors, collects an aggregate payoff and imitates the strategy of its best neighbor. The network can be adaptive if agents are able to change their local neighborhood according to their satisfaction level and the strategy played. The condition, in order to obtain highly cooperative non-taxed networks in the long-run time, is that the initial fraction of cooperators has to be sufficiently high. Focussing on this restriction, the implementation of our mechanism produces successful results, a highly cooperative network is reached. Additionally, we observe that the mechanism slightly affects the macrostructure of networks once they have reached a sufficiently high fraction of cooperative agents, this suggests that the mechanism could be implemented only for a short finite period of time.

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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 181.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:181

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Related research
Keywords: Prisoners' Dilemma; Adaptive Network; Taxes-subsidies Scheme;

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Find related papers by JEL classification:
H2 - Public Economics - - Taxation, Subsidies, and Revenue
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
D6 - Microeconomics - - Welfare Economics

References listed on IDEAS
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  1. Nicolaas J. Vriend, 2005. "ACE Models of Endogenous Interactions," Working Papers 542, Queen Mary, University of London, Department of Economics. [Downloadable!]
    Other versions:
  2. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, EconWPA, revised 15 Aug 2002. [Downloadable!]
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This page was last updated on 2009-11-27.


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