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Dynamic network formation with foresighted agents

Author

Listed:
  • Yangbo Song

    (The Chinese University of Hong Kong (Shenzhen))

  • Mihaela Schaar

    (University of Oxford)

Abstract

What networks can form and persist when agents are self-interested? Can such networks be efficient? A substantial theoretical literature predicts that various networks emerge randomly and efficiency is unlikely to be sustained, but these predictions are in stark contrast to empirical findings. In this paper, we present a new model of network formation. In contrast to the existing literature, we assume that agents are foresighted (rather than myopic) and have some but not necessarily all information about the history. We provide a tight characterization of the sustainable networks; in particular, efficient networks can form and persist if they provide every agent a strictly positive payoff. Our results are robust to model variations, while evidence from empirical networks suggests a modest improvement in prediction by our model compared with models with agent myopia.

Suggested Citation

  • Yangbo Song & Mihaela Schaar, 2020. "Dynamic network formation with foresighted agents," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(2), pages 345-384, June.
  • Handle: RePEc:spr:jogath:v:49:y:2020:i:2:d:10.1007_s00182-020-00714-4
    DOI: 10.1007/s00182-020-00714-4
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    More about this item

    Keywords

    Network formation; Foresight; Efficiency;
    All these keywords.

    JEL classification:

    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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