When are efficient conventions selected in networks?

Carlos Alós-Ferrer, Johannes Buckenmaier, Federica Farolfi

Research output: Contribution to journalArticlepeer-review

Abstract

We study the determinants of convergence to efficient conventions in coordination games played on networks, when agents focus on past performance (imitative play). Previous theoretical results provide an incomplete picture and suggest potentially-complex interactions between the features of dynamics and behavior. We conducted an extensive simulation study (with approximately 1.12 million simulations) varying network size, interaction and information radius, the probability of actual interaction, the probability of mistakes, tie-breaking rules, and the process governing revision opportunities. Our main result is that “more interactions,” be it in the form of larger interaction neighborhoods or of a higher interaction probability, lead to less coordination on efficient conventions. A second observation, confirming previous but partial theoretical results, is that a large network size relative to the size of neighborhoods (a “large world”) facilitates convergence to efficient conventions. Third, a larger information neighborhood helps efficiency because it increases visibility of efficient payoffs across the network. Last, technical details of the dynamic specification as tie-breaking or inertia, while often relevant for specific theoretical results, appear to be of little empirical relevance in the larger space of dynamics.

Original languageEnglish (US)
Article number104074
JournalJournal of Economic Dynamics and Control
Volume124
DOIs
StatePublished - Mar 2021

Keywords

  • Agent-based models
  • Coordination games
  • Learning
  • Local interactions
  • Networks

ASJC Scopus subject areas

  • Economics and Econometrics
  • Control and Optimization
  • Applied Mathematics

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