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Targeting the Key Player: An Incentive-Based Approach

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Abstract

We consider a network game with local complementarities. A policymaker, aiming at minimizing or maximizing aggregate effort, contracts with a single agent on the network to trade effort change against transfer. The policymaker has to find the best agent and the optimal contract to offer. Our study shows that for all utilities with linear best-responses, it only takes two statistics about the position of each agent on the network to identify the key player: the Bonacich centrality and a weighted measure of the number of closed walks originating from the agent. We also characterize key players under linear quadratic utilities for various contractual arrangements.

Suggested Citation

  • Mohamed Belhaj & Frédéric Deroïan, 2018. "Targeting the Key Player: An Incentive-Based Approach," AMSE Working Papers 1804, Aix-Marseille School of Economics, France.
    • Handle: RePEc:aim:wpaimx:1804
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    Cited by:

    1. Marc Claveria-Mayol, 2024. "Moral Hazard with Network Effects," Papers 2406.11660, arXiv.org.
    2. Michel Grabisch & Elena Parilina & Agnieszka Rusinowska & Georges Zaccour, 2025. "Dynamic Network Formation with Farsighted Players and Limited Capacities," Documents de travail du Centre d'Economie de la Sorbonne 25019, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Mohamed Belhaj & Frédéric Deroïan & Shahir Safi, 2020. "Costly agreement-based transfers and targeting on networks with synergies," Working Papers halshs-02558397, HAL.
    4. Li, Jian & Zhou, Junjie & Chen, Ying-Ju, 2021. "The Limit of Targeting in Networks," ISU General Staff Papers 202112081957590000, Iowa State University, Department of Economics.
    5. Belhaj, Mohamed & Deroïan, Frédéric & Safi, Shahir, 2023. "Targeting in networks under costly agreements," Games and Economic Behavior, Elsevier, vol. 140(C), pages 154-172.
    6. Yifan Xiong & Youze Lang & Ziyan Li, 2024. "Cost intervention in delinquent networks," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 62(2), pages 321-344, March.
    7. Li, Jian & Zhou, Junjie & Chen, Ying-Ju, 2022. "The limit of targeting in networks," Journal of Economic Theory, Elsevier, vol. 201(C).
    8. Sun, Yang & Zhao, Wei, 2024. "Relative performance evaluation in spillover networks," Games and Economic Behavior, Elsevier, vol. 145(C), pages 285-311.
    9. Frédéric Deroïan & Philippine Escudie, 2025. "Addiction in networks," AMSE Working Papers 2506, Aix-Marseille School of Economics, France.

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    Keywords

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    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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