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Multiagent Mechanism Design Without Money

Author

Listed:
  • Santiago R. Balseiro

    (Graduate School of Business, Columbia University, New York, New York 10027)

  • Huseyin Gurkan

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Peng Sun

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

Abstract

We consider a principal repeatedly allocating a single resource in each period to one of multiple agents, whose values are private, without relying on monetary payments over an infinite horizon with discounting. We design a dynamic mechanism that induces agents to report their values truthfully in each period via promises/threats of future favorable/unfavorable allocations. We show that our mechanism asymptotically achieves the first-best efficient allocation (the welfare-maximizing allocation as if values are public) as agents become more patient and provide sharp characterizations of convergence rates to first best as a function of the discount factor. In particular, in the case of two agents we prove that the convergence rate of our mechanism is optimal—that is, no other mechanism can converge faster to first best.

Suggested Citation

  • Santiago R. Balseiro & Huseyin Gurkan & Peng Sun, 2019. "Multiagent Mechanism Design Without Money," Operations Research, INFORMS, vol. 67(5), pages 1417-1436, September.
    • Handle: RePEc:inm:oropre:v:67:y:2019:i:5:p:1417-1436
    DOI: opre.2018.1820
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    References listed on IDEAS

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    2. Julien Combe & Vladyslav Nora & Olivier Tercieux, 2021. "Dynamic assignment without money: Optimality of spot mechanisms," Working Papers 2021-11, Center for Research in Economics and Statistics.
    3. Liang, Yong & Sun, Peng & Tang, Runyu & Zhang, Chong, 2023. "Efficient resource allocation contracts to reduce adverse events," Other publications TiSEM 0bcf44d9-d0ac-4231-beaf-8, Tilburg University, School of Economics and Management.
    4. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
    5. K. Drakopoulos & R. S. Randhawa, 2021. "Why Perfect Tests May Not Be Worth Waiting For: Information as a Commodity," Management Science, INFORMS, vol. 67(11), pages 6678-6693, November.
    6. Shivam Gupta & Wei Chen & Milind Dawande & Ganesh Janakiraman, 2023. "Three Years, Two Papers, One Course Off: Optimal Nonmonetary Reward Policies," Management Science, INFORMS, vol. 69(5), pages 2852-2869, May.
    7. Ezzat Elokda & Saverio Bolognani & Andrea Censi & Florian Dorfler & Emilio Frazzoli, 2022. "A self-contained karma economy for the dynamic allocation of common resources," Papers 2207.00495, arXiv.org, revised May 2023.
    8. Th`anh Nguyen & Alexander Teytelboym & Shai Vardi, 2023. "Dynamic Combinatorial Assignment," Papers 2303.13967, arXiv.org.

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