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Type | Journal Article |
Scope | Discipline-based scholarship |
Title | Imitation, network size, and efficiency |
Organization Unit | |
Authors |
|
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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Journal Title | Network Science |
Publisher | Cambridge University Press |
Geographical Reach | international |
ISSN | 2050-1242 |
Volume | 9 |
Number | 1 |
Page Range | 123 - 133 |
Date | 2021 |
Abstract Text | A number of theoretical results have provided sufficient conditions for the selection of payoff-efficient equilibria in games played on networks when agents imitate successful neighbors and make occasional mistakes (stochastic stability). However, those results only guarantee full convergence in the long-run, which might be too restrictive in reality. Here, we employ a more gradual approach relying on agent-based simulations avoiding the double limit underlying these analytical results. We focus on the circular-city model, for which a sufficient condition on the population size relative to the neighborhood size was identified by Alós-Ferrer & Weidenholzer [(2006) <jats:italic>Economics Letters</jats:italic>, <jats:italic>93</jats:italic>, 163–168]. Using more than 100,000 agent-based simulations, we find that selection of the efficient equilibrium prevails also for a large set of parameters violating the previously identified condition. Interestingly, the extent to which efficiency obtains decreases gradually as one moves away from the boundary of this condition. |
Digital Object Identifier | 10.1017/nws.2020.43 |
Other Identification Number | merlin-id:20113 |
PDF File | Download from ZORA |
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Keywords | Sociology and Political Science, Communication, Social Psychology, agent-based models, pareto efficiency, risk dominance, imitation, networks, stochastic stability |