IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2411.08026.html

Incentive Design with Spillovers

Author

Listed:
  • Krishna Dasaratha
  • Benjamin Golub
  • Anant Shah

Abstract

A principal uses payments conditioned on stochastic outcomes of a team project to elicit costly effort from the team members. We develop a multi-agent generalization of a classic first-order approach to contract optimization by leveraging methods from network games. The main results characterize the optimal allocation of incentive pay across agents and outcomes. Incentive optimality requires equalizing, across agents, a product of (i) individual productivity (ii) organizational centrality and (iii) responsiveness to monetary incentives. We specialize the model to explore several applied questions, including whether compensation should reward individual ability or collaborativeness and how the strength of complementarities shapes pay dispersion.

Suggested Citation

  • Krishna Dasaratha & Benjamin Golub & Anant Shah, 2024. "Incentive Design with Spillovers," Papers 2411.08026, arXiv.org, revised Jul 2026.
    • Handle: RePEc:arx:papers:2411.08026
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2411.08026
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ozan Candogan & Kostas Bimpikis & Asuman Ozdaglar, 2012. "Optimal Pricing in Networks with Externalities," Operations Research, INFORMS, vol. 60(4), pages 883-905, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gillian K. Hadfield & Andrew Koh, 2025. "An Economy of AI Agents," Papers 2509.01063, arXiv.org.
    2. Chengqing Li & Junjie Zhou, 2025. "Price Regulation and Network Spillovers," Papers 2508.17301, arXiv.org, revised Mar 2026.

    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. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    2. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.
    3. Jingjing Zhao & Yongli Li & Yunlong Ding & Chao Liu, 2019. "The value of leading customers in a crowdfunding-based marketing pattern," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
    4. Ostrizek, Franz & Sartori, Elia, 2023. "Screening while controlling an externality," Games and Economic Behavior, Elsevier, vol. 139(C), pages 26-55.
    5. Nora, Vladyslav & Winter, Eyal, 2024. "Exploiting social influence in networks," Theoretical Economics, Econometric Society, vol. 19(1), January.
    6. Elias Carroni & Paolo Pin & Simone Righi, 2020. "Bring a Friend! Privately or Publicly?," Management Science, INFORMS, vol. 66(5), pages 2269-2290, May.
    7. Alexandre Belloni & Changrong Deng & Saša Pekeč, 2017. "Mechanism and Network Design with Private Negative Externalities," Operations Research, INFORMS, vol. 65(3), pages 577-594, June.
    8. Colombo, Luca & Labrecciosa, Paola & Rusinowska, Agnieszka, 2025. "A dynamic analysis of criminal networks," Journal of Economic Theory, Elsevier, vol. 223(C).
    9. 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).
    10. Jadbabaie, Ali & Kakhbod, Ali, 2019. "Optimal contracting in networks," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1094-1153.
    11. Beknazar-Yuzbashev, George & Jimenez-Duran, Rafael & Simonov, Andrey & Mateusz Stalinsk, Mateusz, 2026. "Social Media Advertising Loads as Prices," The Warwick Economics Research Paper Series (TWERPS) 1602, University of Warwick, Department of Economics.
    12. Ruxian Wang & Zizhuo Wang, 2017. "Consumer Choice Models with Endogenous Network Effects," Management Science, INFORMS, vol. 63(11), pages 3944-3960, November.
    13. Andrea Galeotti & Benjamin Golub & Sanjeev Goyal, 2020. "Targeting Interventions in Networks," Econometrica, Econometric Society, vol. 88(6), pages 2445-2471, November.
    14. Yiangos Papanastasiou, 2020. "Fake News Propagation and Detection: A Sequential Model," Management Science, INFORMS, vol. 66(5), pages 1826-1846, May.
    15. Harkins, Andrew, 2020. "Network Comparative Statics," The Warwick Economics Research Paper Series (TWERPS) 1306, University of Warwick, Department of Economics.
    16. Baris Ata & Alexandre Belloni & Ozan Candogan, 2024. "Latent Agents in Networks: Estimation and Targeting," Operations Research, INFORMS, vol. 72(2), pages 549-569, March.
    17. 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.
    18. Chenhao Du & William L. Cooper & Zizhuo Wang, 2016. "Optimal Pricing for a Multinomial Logit Choice Model with Network Effects," Operations Research, INFORMS, vol. 64(2), pages 441-455, April.
    19. Rui Zheng & Biying Shou & Yingju Chen, 2023. "Differential pricing in social networks with strategic consumers," Production and Operations Management, Production and Operations Management Society, vol. 32(8), pages 2638-2655, August.
    20. Kun Jin & Yevgeniy Vorobeychik & Mingyan Liu, 2021. "Multi-Scale Games: Representing and Solving Games on Networks with Group Structure," Papers 2101.08314, arXiv.org.

    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:2411.08026. 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: https://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.