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Targeting the Key Player: An Incentive-Based Approach

Author

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  • Mohamed Belhaj

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Frédéric Deroïan

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

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," Working Papers halshs-01699849, HAL.
    • Handle: RePEc:hal:wpaper:halshs-01699849
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01699849
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    References listed on IDEAS

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    15. Andrea Galeotti & Benjamin Golub & Sanjeev Goyal, 2020. "Targeting Interventions in Networks," Econometrica, Econometric Society, vol. 88(6), pages 2445-2471, November.
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    Cited by:

    1. Marc Claveria-Mayol, 2024. "Moral Hazard with Network Effects," Papers 2406.11660, arXiv.org.
    2. Belhaj, Mohamed & Deroïan, Frédéric & Safi, Shahir, 2023. "Targeting in networks under costly agreements," Games and Economic Behavior, Elsevier, vol. 140(C), pages 154-172.
    3. Sun, Yang & Zhao, Wei, 2024. "Relative performance evaluation in spillover networks," Games and Economic Behavior, Elsevier, vol. 145(C), pages 285-311.
    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. Mohamed Belhaj & Frédéric Deroïan & Shahir Safi, 2020. "Costly agreement-based transfers and targeting on networks with synergies," AMSE Working Papers 2015, Aix-Marseille School of Economics, France.
    6. Li, Jian & Zhou, Junjie & Chen, Ying-Ju, 2022. "The limit of targeting in networks," Journal of Economic Theory, Elsevier, vol. 201(C).

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    More about this item

    Keywords

    key player; network; linear interaction; incentives; contract; limited budget;
    All these keywords.

    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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