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Network formation with NIMBY constraints

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  • Block, Lukas

Abstract

The expansion of power networks is often hampered by local protests against certain power lines (’not-in-my-backyard’). For that matter, we study the structure of these networks with an application of a network formation game in order to determine the emergence of such a protest. We examine the existence of Nash-stable networks and their characteristics, when no player wants to make an alteration. Stability within this game is only reached if each player is sufficiently connected to a power source but is not linked to more players than necessary. In addition, we introduce the Nash-stable network algorithm which constructs a Nash-stable network with heterogeneous players.

Suggested Citation

  • Block, Lukas, 2023. "Network formation with NIMBY constraints," Energy Economics, Elsevier, vol. 119(C).
  • Handle: RePEc:eee:eneeco:v:119:y:2023:i:c:s0140988322005990
    DOI: 10.1016/j.eneco.2022.106470
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    References listed on IDEAS

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    1. Britta Hoyer & Kris De Jaegher, 2016. "Strategic Network Disruption and Defense," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(5), pages 802-830, October.
    2. Haller, Hans & Sarangi, Sudipta, 2005. "Nash networks with heterogeneous links," Mathematical Social Sciences, Elsevier, vol. 50(2), pages 181-201, September.
    3. Paul L. Joskow, 2014. "Incentive Regulation in Theory and Practice: Electricity Distribution and Transmission Networks," NBER Chapters, in: Economic Regulation and Its Reform: What Have We Learned?, pages 291-344, National Bureau of Economic Research, Inc.
    4. Joskow Paul L., 2008. "Incentive Regulation and Its Application to Electricity Networks," Review of Network Economics, De Gruyter, vol. 7(4), pages 1-14, December.
    5. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    6. Bloch, Francis & Jackson, Matthew O., 2007. "The formation of networks with transfers among players," Journal of Economic Theory, Elsevier, vol. 133(1), pages 83-110, March.
    7. Rious Vincent & Perez Yannick & Glachant Jean-Michel, 2011. "Power Transmission Network Investment as an Anticipation Problem," Review of Network Economics, De Gruyter, vol. 10(4), pages 1-23, December.
    8. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    9. Jayanth R. Banavar & Amos Maritan & Andrea Rinaldo, 1999. "Size and form in efficient transportation networks," Nature, Nature, vol. 399(6732), pages 130-132, May.
    10. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
    11. Francis Bloch & Matthew Jackson, 2006. "Definitions of equilibrium in network formation games," International Journal of Game Theory, Springer;Game Theory Society, vol. 34(3), pages 305-318, October.
    12. Watts, Alison, 2001. "A Dynamic Model of Network Formation," Games and Economic Behavior, Elsevier, vol. 34(2), pages 331-341, February.
    13. Sütterlin, Bernadette & Siegrist, Michael, 2017. "Public acceptance of renewable energy technologies from an abstract versus concrete perspective and the positive imagery of solar power," Energy Policy, Elsevier, vol. 106(C), pages 356-366.
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    More about this item

    Keywords

    Network formation; NIMBY; Power networks; Nash stability;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • H54 - Public Economics - - National Government Expenditures and Related Policies - - - Infrastructures
    • L52 - Industrial Organization - - Regulation and Industrial Policy - - - Industrial Policy; Sectoral Planning Methods

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