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A degree-distance-based connections model with negative and positive externalities

Author

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  • Philipp Möhlmeier

    (Universität Bielefeld = Bielefeld University)

  • Agnieszka Rusinowska

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Emily Tanimura

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

We develop a modification of the connections model by Jackson and Wolinsky (1996) that takes into account negative externalities arising from the connectivity of direct and indirect neighbors, thus combining aspects of the connections model and the co-author model. We consider a general functional form for agents' utility that incorporates both the effects of distance and of neighbors' degree. Consequently, we introduce a framework that can be seen as a degree-distance-based connections model with both negative and positive externalities. Our analysis shows how the introduction of negative externalities modifies certain results about stability and efficiency compared to the original connections model. In particular, we see the emergence of new stable structures, such as a star with links between peripheral nodes. We also identify structures, for example, certain disconnected networks, that are efficient in our model but which could not be efficient in the original connections model. While our results are proved for the general utility function, some of them are illustrated by using a specific functional form of the degree-distance-based utility.

Suggested Citation

  • Philipp Möhlmeier & Agnieszka Rusinowska & Emily Tanimura, 2013. "A degree-distance-based connections model with negative and positive externalities," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00825266, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00825266
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00825266
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    References listed on IDEAS

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    Cited by:

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    3. Hellmann, Tim & Staudigl, Mathias, 2014. "Evolution of social networks," European Journal of Operational Research, Elsevier, vol. 234(3), pages 583-596.
    4. László Á. Kóczy, 2022. "Core-stability over networks with widespread externalities," Annals of Operations Research, Springer, vol. 318(2), pages 1001-1027, November.
    5. Möhlmeier, Philipp & Rusinowska, Agnieszka & Tanimura, Emily, 2018. "Competition for the access to and use of information in networks," Mathematical Social Sciences, Elsevier, vol. 92(C), pages 48-63.
    6. 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).
    7. Chenghong Luo & Ana Mauleon & Vincent Vannetelbosch, 2021. "Network formation with myopic and farsighted players," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(4), pages 1283-1317, June.
    8. Ping Sun & Elena Parilina, 2024. "Networks with nonordered partitioning of players: stability and efficiency with neighborhood-influenced cost topology," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 99(3), pages 271-305, June.
    9. Pramod C. Mane & Nagarajan Krishnamurthy & Kapil Ahuja, 2019. "Formation of Stable and Efficient Social Storage Cloud," Games, MDPI, vol. 10(4), pages 1-17, November.
    10. Jan-Peter Siedlarek, 2023. "Making friends meet: network formation with introductions," International Journal of Game Theory, Springer;Game Theory Society, vol. 52(4), pages 1037-1076, December.
    11. 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.
    12. Pramod C. Mane & Nagarajan Krishnamurthy & Kapil Ahuja, 2023. "Resource availability in the social cloud: An economics perspective," Bulletin of Economic Research, Wiley Blackwell, vol. 75(2), pages 541-566, April.
    13. Adriani, Fabrizio & Ladley, Dan, 2021. "Social distance, speed of containment and crowding in/out in a network model of contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 597-625.

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    More about this item

    Keywords

    Connections model; degree; distance; negative externalities; positive externalities; pairwise stability; efficiency; Modèle des connexions; degré; externalités négatives; externalités positives; stabilité; efficacité;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General

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