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Peer‐Confirming Equilibrium

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  • Elliot Lipnowski
  • Evan Sadler

Abstract

We can often predict the behavior of those closest to us more accurately than that of complete strangers, yet we routinely engage in strategic situations with both: our social network impacts our strategic knowledge. Peer‐confirming equilibrium describes the behavioral consequences of this intuition in a noncooperative game. We augment a game with a network to represent strategic information: if two players are linked in the network, they have correct conjectures about each others' strategies. In peer‐confirming equilibrium, there is common belief that players (i) behave rationally and (ii) correctly anticipate neighbors' play. In simultaneous‐move games, adding links to the network always restricts the set of outcomes. In dynamic games, the outcome set may vary non‐monotonically with the network because the actions of well‐connected players help poorly‐connected players coordinate. This solution concept provides a useful language for studying public good provision, highlights a new channel through which central individuals facilitate coordination, and delineates possible sources of miscoordination in protests and coups.

Suggested Citation

  • Elliot Lipnowski & Evan Sadler, 2019. "Peer‐Confirming Equilibrium," Econometrica, Econometric Society, vol. 87(2), pages 567-591, March.
    • Handle: RePEc:wly:emetrp:v:87:y:2019:i:2:p:567-591
    DOI: 10.3982/ECTA15597
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    Cited by:

    1. Foerster, Manuel & Mauleon, Ana & Vannetelbosch, Vincent J., 2021. "Shadow links," Journal of Economic Theory, Elsevier, vol. 197(C).
      • FOERSTER Manuel, & MAULEON Ana, & VANNETELBOSCH Vincent,, 2018. "Shadow links," LIDAM Discussion Papers CORE 2018030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Foerster, Manuel & Mauleon, Ana & Vannetelbosch, Vincent, 2021. "Shadow links," LIDAM Reprints CORE 3171, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Battigalli, Pierpaolo & Panebianco, Fabrizio & Pin, Paolo, 2023. "Learning and selfconfirming equilibria in network games," Journal of Economic Theory, Elsevier, vol. 212(C).
    3. Cerreia-Vioglio, Simone & Maccheroni, Fabio & Schmeidler, David, 2022. "Equilibria of nonatomic anonymous games," Games and Economic Behavior, Elsevier, vol. 135(C), pages 110-131.
    4. Andreas Bjerre-Nielsen & Martin Benedikt Busch, 2022. "Statistical inference in social networks: how sampling bias and uncertainty shape decisions," Papers 2205.13046, arXiv.org.
    5. Zenou, Yves & Bochet, Olivier & Faure, Mathieu & Long, Yan, 2020. "Perceived Competition in Networks," CEPR Discussion Papers 15582, C.E.P.R. Discussion Papers.
    6. Bochet, Olivier & Faure, Mathieu & Long, Yan & Zenou, Yves, 2020. "Perceived Competition in Networks," CEPR Discussion Papers 15582, C.E.P.R. Discussion Papers.

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