Imitation, network size, and efficiency

Carlos Alós-Ferrer, Johannes Buckenmaier, Federica Farolfi

Research output: Contribution to journalArticlepeer-review

Abstract

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) Economics Letters, 93, 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.

Original languageEnglish (US)
JournalNetwork Science
DOIs
StateAccepted/In press - 2020

Keywords

  • agent-based models
  • imitation
  • networks
  • pareto efficiency
  • risk dominance
  • stochastic stability

ASJC Scopus subject areas

  • Social Psychology
  • Communication
  • Sociology and Political Science

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