IDEAS home Printed from https://ideas.repec.org/a/inm/ormoor/v46y2021i3p835-855.html

From Monetary to Nonmonetary Mechanism Design via Artificial Currencies

Author

Listed:
  • Artur Gorokh

    (Center for Applied Mathematics, Cornell University, Ithaca, New York 14850)

  • Siddhartha Banerjee

    (Operations Research and Information Engineering, Cornell University, Ithaca, New York 14850)

  • Krishnamurthy Iyer

    (Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

Abstract

Nonmonetary mechanisms for repeated allocation and decision making are gaining widespread use in many real-world settings. Our aim in this work is to study the performance and incentive properties of simple mechanisms based on artificial currencies in such settings. To this end, we make the following contributions: For a general allocation setting, we provide two black-box approaches to convert any one-shot monetary mechanism to a dynamic nonmonetary mechanism using an artificial currency that simultaneously guarantees vanishing gains from nontruthful reporting over time and vanishing losses in performance. The two mechanisms trade off between their applicability and their computational and informational requirements. Furthermore, for settings with two agents, we show that a particular artificial currency mechanism also results in a vanishing price of anarchy.

Suggested Citation

  • Artur Gorokh & Siddhartha Banerjee & Krishnamurthy Iyer, 2021. "From Monetary to Nonmonetary Mechanism Design via Artificial Currencies," Mathematics of Operations Research, INFORMS, vol. 46(3), pages 835-855, August.
    • Handle: RePEc:inm:ormoor:v:46:y:2021:i:3:p:835-855
    DOI: 10.1287/moor.2020.1098
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/moor.2020.1098
    Download Restriction: no
    File URL: https://libkey.io/10.1287/moor.2020.1098?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Milgrom,Paul, 2004. "Putting Auction Theory to Work," Cambridge Books, Cambridge University Press, number 9780521536721.
    2. Eduardo M Azevedo & Eric Budish, 2019. "Strategy-proofness in the Large," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 81-116.
    3. Alex Gershkov & Benny Moldovanu, 2009. "Dynamic Revenue Maximization with Heterogeneous Objects: A Mechanism Design Approach," American Economic Journal: Microeconomics, American Economic Association, vol. 1(2), pages 168-198, August.
    4. Santiago R. Balseiro & Huseyin Gurkan & Peng Sun, 2019. "Multiagent Mechanism Design Without Money," Operations Research, INFORMS, vol. 67(5), pages 1417-1436, September.
    5. Krishnamurthy Iyer & Ramesh Johari & Mukund Sundararajan, 2014. "Mean Field Equilibria of Dynamic Auctions with Learning," Management Science, INFORMS, vol. 60(12), pages 2949-2970, December.
    6. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2015. "Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design," Management Science, INFORMS, vol. 61(4), pages 864-884, April.
    7. Dirk Bergemann & Juuso V‰lim‰ki, 2010. "The Dynamic Pivot Mechanism," Econometrica, Econometric Society, vol. 78(2), pages 771-789, March.
    8. Eric Budish, 2011. "The Combinatorial Assignment Problem: Approximate Competitive Equilibrium from Equal Incomes," Journal of Political Economy, University of Chicago Press, vol. 119(6), pages 1061-1103.
    9. Matthew O Jackson & Hugo F Sonnenschein, 2007. "Overcoming Incentive Constraints by Linking Decisions -super-1," Econometrica, Econometric Society, vol. 75(1), pages 241-257, January.
    10. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    11. Santiago R. Balseiro & Yonatan Gur, 2019. "Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium," Management Science, INFORMS, vol. 65(9), pages 3952-3968, September.
    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. Gerdus Benadè & Daniel Halpern & Alexandros Psomas, 2025. "Dynamic Fair Division with Partial Information," Operations Research, INFORMS, vol. 73(4), pages 1876-1896, July.
    2. Shivam Gupta & Saurabh Bansal & Milind Dawande & Ganesh Janakiraman, 2024. "Trust-and-Evaluate: A Dynamic Nonmonetary Mechanism for Internal Capital Allocation," Management Science, INFORMS, vol. 70(11), pages 7811-7828, November.
    3. Moise Blanchard & Patrick Jaillet, 2024. "Near-Optimal Mechanisms for Resource Allocation Without Monetary Transfers," Papers 2408.10066, arXiv.org.
    4. Santiago R. Balseiro & Omar Besbes & Francisco Castro, 2024. "Mechanism Design Under Approximate Incentive Compatibility," Operations Research, INFORMS, vol. 72(1), pages 355-372, January.
    5. Kevin Riehl & Anastasios Kouvelas & Michail Makridis, 2024. "Fair Money -- Public Good Value Pricing With Karma Economies," Papers 2407.05132, arXiv.org.
    6. Vahideh Manshadi & Rad Niazadeh & Scott Rodilitz, 2023. "Fair Dynamic Rationing," Management Science, INFORMS, vol. 69(11), pages 6818-6836, November.
    7. 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.
    8. 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.
    9. MohammadHossein Bateni & Yiwei Chen & Dragos Florin Ciocan & Vahab Mirrokni, 2022. "Fair Resource Allocation in a Volatile Marketplace," Operations Research, INFORMS, vol. 70(1), pages 288-308, January.
    10. Ezzat Elokda & Saverio Bolognani & Andrea Censi & Florian Dörfler & Emilio Frazzoli, 2024. "A Self-Contained Karma Economy for the Dynamic Allocation of Common Resources," Dynamic Games and Applications, Springer, vol. 14(3), pages 578-610, July.
    11. Th`anh Nguyen & Alexander Teytelboym & Shai Vardi, 2023. "Dynamic Combinatorial Assignment," Papers 2303.13967, arXiv.org.

    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. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.
    2. Kaplan, Todd R. & Zamir, Shmuel, 2015. "Advances in Auctions," Handbook of Game Theory with Economic Applications,, Elsevier.
    3. Dragos Florin Ciocan & Krishnamurthy Iyer, 2021. "Tractable Equilibria in Sponsored Search with Endogenous Budgets," Operations Research, INFORMS, vol. 69(1), pages 227-244, January.
    4. Santiago R. Balseiro & Vahab Mirrokni & Renato Paes Leme & Song Zuo, 2022. "Dynamic Double Auctions: Toward First Best," Operations Research, INFORMS, vol. 70(4), pages 2299-2317, July.
    5. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2019. "Dynamic Mechanism Design with Budget-Constrained Buyers Under Limited Commitment," Operations Research, INFORMS, vol. 67(3), pages 711-730, May.
    6. Tao Zhang & Quanyan Zhu, 2022. "On Incentive Compatibility in Dynamic Mechanism Design With Exit Option in a Markovian Environment," Dynamic Games and Applications, Springer, vol. 12(2), pages 701-745, June.
    7. Moise Blanchard & Patrick Jaillet, 2024. "Near-Optimal Mechanisms for Resource Allocation Without Monetary Transfers," Papers 2408.10066, arXiv.org.
    8. Frank Kelly & Peter Key & Neil Walton, 2016. "Efficient Advert Assignment," Operations Research, INFORMS, vol. 64(4), pages 822-837, August.
    9. 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.
    10. Luofeng Liao & Christian Kroer, 2024. "Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions," Papers 2406.15522, arXiv.org, revised Mar 2025.
    11. Said, Maher, 2012. "Auctions with dynamic populations: Efficiency and revenue maximization," Journal of Economic Theory, Elsevier, vol. 147(6), pages 2419-2438.
    12. Philippe Jehiel & Laurent Lamy, 2020. "On the Benefits of Set-Asides," Journal of the European Economic Association, European Economic Association, vol. 18(4), pages 1655-1696.
    13. Condorelli, Daniele, 2013. "Market and non-market mechanisms for the optimal allocation of scarce resources," Games and Economic Behavior, Elsevier, vol. 82(C), pages 582-591.
    14. Mierendorff, Konrad, 2016. "Optimal dynamic mechanism design with deadlines," Journal of Economic Theory, Elsevier, vol. 161(C), pages 190-222.
    15. Eric Budish & Judd B. Kessler, 2022. "Can Market Participants Report Their Preferences Accurately (Enough)?," Management Science, INFORMS, vol. 68(2), pages 1107-1130, February.
    16. W. Jason Choi & Amin Sayedi, 2019. "Learning in Online Advertising," Marketing Science, INFORMS, vol. 38(4), pages 584-608, July.
    17. Yash Kanoria & Hamid Nazerzadeh, 2020. "Dynamic Reserve Prices for Repeated Auctions: Learning from Bids," Papers 2002.07331, arXiv.org.
    18. Estrella Alonso & Joaquín Sánchez-Soriano & Juan Tejada, 2020. "Mixed Mechanisms for Auctioning Ranked Items," Mathematics, MDPI, vol. 8(12), pages 1-26, December.
    19. Vincent Conitzer & Christian Kroer & Debmalya Panigrahi & Okke Schrijvers & Nicolas E. Stier-Moses & Eric Sodomka & Christopher A. Wilkens, 2022. "Pacing Equilibrium in First Price Auction Markets," Management Science, INFORMS, vol. 68(12), pages 8515-8535, December.
    20. Ezzat Elokda & Saverio Bolognani & Andrea Censi & Florian Dörfler & Emilio Frazzoli, 2024. "A Self-Contained Karma Economy for the Dynamic Allocation of Common Resources," Dynamic Games and Applications, Springer, vol. 14(3), pages 578-610, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    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:inm:ormoor:v:46:y:2021:i:3:p:835-855. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.