IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2302.05831.html
   My bibliography  Save this paper

On the Difficulty of Characterizing Network Formation with Endogenous Behavior

Author

Listed:
  • Benjamin Golub
  • Yu-Chi Hsieh
  • Evan Sadler

Abstract

Bolletta (2021, Math. Soc. Sci. 114:1-10) studies a model in which a network is strategically formed and then agents play a linear best-response investment game in it. The model is motivated by an application in which people choose both their study partners and their levels of educational effort. Agents have different one-dimensional types $\unicode{x2013}$ private returns to effort. A main result claims that pairwise Nash stable networks have a locally complete structure consisting of possibly overlapping cliques: if two agents are linked, they are part of a clique composed of all agents with types between theirs. We offer a counterexample showing that the claimed characterization is incorrect, highlight where the analysis errs, and discuss implications for network formation models.

Suggested Citation

  • Benjamin Golub & Yu-Chi Hsieh & Evan Sadler, 2023. "On the Difficulty of Characterizing Network Formation with Endogenous Behavior," Papers 2302.05831, arXiv.org, revised Feb 2023.
    • Handle: RePEc:arx:papers:2302.05831
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2302.05831
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. , D. & Tessone, Claudio J. & ,, 2014. "Nestedness in networks: A theoretical model and some applications," Theoretical Economics, Econometric Society, vol. 9(3), September.
    2. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2014. "Endogenous peer effects: local aggregate or local average?," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 39-59.
    3. Watts, Alison, 2001. "A Dynamic Model of Network Formation," Games and Economic Behavior, Elsevier, vol. 34(2), pages 331-341, February.
    4. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    5. Scott E. Carrell & Bruce I. Sacerdote & James E. West, 2013. "From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation," Econometrica, Econometric Society, vol. 81(3), pages 855-882, May.
    6. Anton Badev, 2021. "Nash Equilibria on (Un)Stable Networks," Econometrica, Econometric Society, vol. 89(3), pages 1179-1206, May.
    7. Hiller, Timo, 2017. "Peer effects in endogenous networks," Games and Economic Behavior, Elsevier, vol. 105(C), pages 349-367.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anton Badev, 2021. "Nash Equilibria on (Un)Stable Networks," Econometrica, Econometric Society, vol. 89(3), pages 1179-1206, May.
    2. Ushchev, Philip & Zenou, Yves, 2020. "Social norms in networks," Journal of Economic Theory, Elsevier, vol. 185(C).
    3. Topa, Giorgio & Zenou, Yves, 2015. "Neighborhood and Network Effects," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 561-624, Elsevier.
    4. Zenou, Yves, 2014. "Key Players," CEPR Discussion Papers 10277, C.E.P.R. Discussion Papers.
    5. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    6. Nora, Vladyslav & Winter, Eyal, 2024. "Exploiting social influence in networks," Theoretical Economics, Econometric Society, vol. 19(1), January.
    7. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Working Papers hal-03459820, HAL.
    8. Bolletta, Ugo, 2021. "A model of peer effects in school," Mathematical Social Sciences, Elsevier, vol. 114(C), pages 1-10.
    9. repec:hal:spmain:info:hdl:2441/78vacv4udu92eq3fec89svm9uv is not listed on IDEAS
    10. Hahn, Youjin & Islam, Asadul & Patacchini, Eleonora & Zenou, Yves, 2015. "Network Structure and Education Outcomes: Evidence from a Field Experiment in Bangladesh," IZA Discussion Papers 8872, Institute of Labor Economics (IZA).
    11. Matthew O. Jackson & Brian W. Rogers & Yves Zenou, 2017. "The Economic Consequences of Social-Network Structure," Journal of Economic Literature, American Economic Association, vol. 55(1), pages 49-95, March.
    12. Cohen-Cole, Ethan & Patacchini, Eleonora & Zenou, Yves, 2015. "Static and dynamic networks in interbank markets," Network Science, Cambridge University Press, vol. 3(1), pages 98-123, March.
    13. Zenou, Yves & Patacchini, Eleonora & Islam, Asad, 2015. "Teams, Organization and Education Outcomes: Evidence from a field experiment in Bangladesh," CEPR Discussion Papers 10631, C.E.P.R. Discussion Papers.
    14. Zenou, Yves & Lindquist, Matthew & Sauermann, Jan, 2015. "Network Effects on Worker Productivity," CEPR Discussion Papers 10928, C.E.P.R. Discussion Papers.
    15. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Working Papers hal-03459820, HAL.
    16. Simpson Zhang & Mihaela van der Schaar, 2018. "Reputational Dynamics in Financial Networks During a Crisis," Working Papers 18-03, Office of Financial Research, US Department of the Treasury.
    17. Markus Kinateder & Luca Paolo Merlino, 2021. "The Evolution of Networks and Local Public Good Provision: A Potential Approach," Games, MDPI, vol. 12(3), pages 1-12, July.
    18. Péter Bayer & Ani Guerdjikova, 2020. "Optimism leads to optimality: Ambiguity in network formation," Working Papers hal-03005107, HAL.
    19. Chen, Ying-Ju & Zenou, Yves & Zhou, Junjie, 2022. "The impact of network topology and market structure on pricing," Journal of Economic Theory, Elsevier, vol. 204(C).
    20. Michael D. König & Xiaodong Liu & Yves Zenou, 2019. "R&D Networks: Theory, Empirics, and Policy Implications," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 476-491, July.
    21. Harkins, Andrew, 2020. "Network Comparative Statics," The Warwick Economics Research Paper Series (TWERPS) 1306, University of Warwick, Department of Economics.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2302.05831. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.