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Non-optimal Mechanism Design

Author

Listed:
  • Jason D. Hartline
  • Brendan Lucier

Abstract

The optimal allocation of resources in complex environments—like allocation of dynamic wireless spectrum, cloud computing services, and Internet advertising—is computationally challenging even given the true preferences of the participants. In the theory and practice of optimization in complex environments, a wide variety of special and general purpose algorithms have been developed; these algorithms produce outcomes that are satisfactory but not generally optimal or incentive compatible. This paper develops a very simple approach for converting any, potentially non-optimal, algorithm for optimization given the true participant preferences, into a Bayesian incentive compatible mechanism that weakly improves social welfare and revenue. (JEL D82, H82, L82)

Suggested Citation

  • Jason D. Hartline & Brendan Lucier, 2015. "Non-optimal Mechanism Design," American Economic Review, American Economic Association, vol. 105(10), pages 3102-3124, October.
    • Handle: RePEc:aea:aecrev:v:105:y:2015:i:10:p:3102-24
    Note: DOI: 10.1257/aer.20130712
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    References listed on IDEAS

    as
    1. Christopher A. Pissarides, 2009. "The Unemployment Volatility Puzzle: Is Wage Stickiness the Answer?," Econometrica, Econometric Society, vol. 77(5), pages 1339-1369, September.
    2. Steven J. Davis & R. Jason Faberman & John C. Haltiwanger & Ian Rucker, 2010. "Adjusted Estimates of Worker Flows and Job Openings in JOLTS," NBER Chapters, in: Labor in the New Economy, pages 187-216, National Bureau of Economic Research, Inc.
    3. Marcus Hagedorn & Iourii Manovskii, 2008. "The Cyclical Behavior of Equilibrium Unemployment and Vacancies Revisited," American Economic Review, American Economic Association, vol. 98(4), pages 1692-1706, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Hu Fu & Tao Lin, 2020. "Learning Utilities and Equilibria in Non-Truthful Auctions," Papers 2007.01722, arXiv.org, revised Oct 2022.
    2. Alon Eden & Michal Feldman & Ophir Friedler & Inbal Talgam-Cohen & S. Matthew Weinberg, 2021. "A Simple and Approximately Optimal Mechanism for a Buyer with Complements," Operations Research, INFORMS, vol. 69(1), pages 188-206, January.
    3. Dirk Bergemann & Tan Gan & Yingkai Li, 2023. "Managing Persuasion Robustly: The Optimality of Quota Rules," Papers 2310.10024, arXiv.org, revised Dec 2025.
    4. Louis Golowich & Shengwu Li, 2021. "On the Computational Properties of Obviously Strategy-Proof Mechanisms," Papers 2101.05149, arXiv.org, revised Oct 2022.
    5. Tim Roughgarden & Inbal Talgam-Cohen, 2018. "Approximately Optimal Mechanism Design," Papers 1812.11896, arXiv.org, revised Aug 2020.
    6. Shao, Ran & Zhou, Lin, 2016. "Optimal allocation of an indivisible good," Games and Economic Behavior, Elsevier, vol. 100(C), pages 95-112.
    7. Yiding Feng & Wei Tang, 2025. "Persuasive Calibration," Papers 2504.03211, arXiv.org.

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    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • H82 - Public Economics - - Miscellaneous Issues - - - Governmental Property
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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