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Bargaining dynamics in exchange networks

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  • Bayati, Mohsen
  • Borgs, Christian
  • Chayes, Jennifer
  • Kanoria, Yash
  • Montanari, Andrea

Abstract

We consider a one-sided assignment market or exchange network with transferable utility and the dynamics of bargaining in such a market. Our dynamical model is local, involving iterative updates of ‘offers’ based on estimated best alternative matches, in the spirit of pairwise Nash bargaining. Agents are not strategic in our model. We establish that when a balanced outcome (a generalization of the pairwise Nash bargaining solution to networks) exists, our dynamics converges rapidly to such an outcome.

Suggested Citation

  • Bayati, Mohsen & Borgs, Christian & Chayes, Jennifer & Kanoria, Yash & Montanari, Andrea, 2015. "Bargaining dynamics in exchange networks," Journal of Economic Theory, Elsevier, vol. 156(C), pages 417-454.
    • Handle: RePEc:eee:jetheo:v:156:y:2015:i:c:p:417-454
    DOI: 10.1016/j.jet.2014.02.007
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    References listed on IDEAS

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    Cited by:

    1. Yuqing Zhu & Ruidong Yan & Deying Li, 2019. "Minimum cost stability in exchange networks," Journal of Combinatorial Optimization, Springer, vol. 38(4), pages 987-1004, November.
    2. Alison Watts, 2016. "Auctions Versus Private Negotiations in Buyer-Seller Networks," Games, MDPI, vol. 7(3), pages 1-14, August.
    3. Mohsen Mosleh & Peter Ludlow & Babak Heydari, 2016. "Distributed Resource Management in Systems of Systems: An Architecture Perspective," Systems Engineering, John Wiley & Sons, vol. 19(4), pages 362-374, July.
    4. Bary S. R. Pradelski & Heinrich H. Nax, 2020. "Market sentiments and convergence dynamics in decentralized assignment economies," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(1), pages 275-298, March.
    5. Leshno, Jacob D. & Pradelski, Bary S.R., 2021. "The importance of memory for price discovery in decentralized markets," Games and Economic Behavior, Elsevier, vol. 125(C), pages 62-78.
    6. Heinrich H. Nax & Bary S. R. Pradelski, 2016. "Core Stability and Core Selection in a Decentralized Labor Matching Market," Games, MDPI, vol. 7(2), pages 1-16, March.
    7. János Kramár & Tom Eccles & Ian Gemp & Andrea Tacchetti & Kevin R. McKee & Mateusz Malinowski & Thore Graepel & Yoram Bachrach, 2022. "Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    8. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    9. Blume, Lawrence & Easley, David & Kleinberg, Jon & Kleinberg, Robert & Tardos, Éva, 2015. "Introduction to computer science and economic theory," Journal of Economic Theory, Elsevier, vol. 156(C), pages 1-13.
    10. Agranov, M. & Elliott, M., 2017. "Commitment and (In)Efficiency: A Bargaining Experiment," Cambridge Working Papers in Economics 1743, Faculty of Economics, University of Cambridge.
    11. Arnaud Zlatko Dragicevic, 2022. "Exchange Networks with Stochastic Matching," Games, MDPI, vol. 14(1), pages 1-18, December.
    12. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.

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    More about this item

    Keywords

    Nash bargaining; Network; Dynamics; Convergence; Matching; Assignment;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory

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