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Optimal prize allocation in contests: The role of negative prizes

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  • Liu, Bin
  • Lu, Jingfeng
  • Wang, Ruqu
  • Zhang, Jun

Abstract

In this paper, we analyze the role of negative prizes in contest design with a fixed budget, risk-neutral contestants, and independent private abilities. The effort-maximizing prize allocation rule features a threshold. When the highest effort is above the threshold, all contestants with lower efforts receive negative prizes. These negative prizes are used to augment the prize to the contestant with the highest effort, which better incentivizes contestants with higher abilities. When no contestant's effort exceeds the threshold, all contestants equally split the initial budget (or a portion of it) to ensure their participation. We find that allowing negative prizes can increase the expected total effort dramatically. In particular, if no bound is imposed on negative prizes, the expected total effort can be arbitrarily close to the highest possible effort inducible when all contestants have the maximum ability with certainty. The above contest is shown to be the optimal mechanism for a more general class of mechanisms.

Suggested Citation

  • Liu, Bin & Lu, Jingfeng & Wang, Ruqu & Zhang, Jun, 2018. "Optimal prize allocation in contests: The role of negative prizes," Journal of Economic Theory, Elsevier, vol. 175(C), pages 291-317.
  • Handle: RePEc:eee:jetheo:v:175:y:2018:i:c:p:291-317
    DOI: 10.1016/j.jet.2018.01.016
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Letina, Igor & Liu, Shuo & Netzer, Nick, 2023. "Optimal contest design: Tuning the heat," Journal of Economic Theory, Elsevier, vol. 213(C).
    2. Olszewski, Wojciech & Siegel, Ron, 2020. "Performance-maximizing large contests," Theoretical Economics, Econometric Society, vol. 15(1), January.
    3. Paul Pecorino, 2020. "Bridge burning and escape routes," Public Choice, Springer, vol. 184(3), pages 399-414, September.
    4. Name Correa, Alvaro J. & Yildirim, Huseyin, 2024. "Multiple prizes in tournaments with career concerns," Journal of Economic Theory, Elsevier, vol. 215(C).
    5. Fu, Qiang & Wang, Xiruo & Wu, Zenan, 2021. "Multi-prize contests with risk-averse players," Games and Economic Behavior, Elsevier, vol. 129(C), pages 513-535.
    6. Liu, Bin & Lu, Jingfeng, 2023. "Optimal orchestration of rewards and punishments in rank-order contests," Journal of Economic Theory, Elsevier, vol. 208(C).
    7. Boyarchenko, Svetlana, 2021. "Inefficiency of sponsored research," Journal of Mathematical Economics, Elsevier, vol. 95(C).
    8. Mengxi Zhang, 2023. "Optimal Contests with Incomplete Information and Convex Effort Costs," CRC TR 224 Discussion Paper Series crctr224_2023_156v2, University of Bonn and University of Mannheim, Germany.
    9. Feng, Xin & Jiao, Qian & Kuang, Zhonghong & Lu, Jingfeng, 2024. "Optimal prize design in team contests with pairwise battles," Journal of Economic Theory, Elsevier, vol. 215(C).
    10. Xiao, Jun, 2023. "Ability grouping in contests," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    11. Liu, Bin & Lu, Jingfeng, 2019. "The optimal allocation of prizes in contests with costly entry," International Journal of Industrial Organization, Elsevier, vol. 66(C), pages 137-161.
    12. Aner Sela & Yizhaq Minchuk, 2024. "Carrots and sticks: collaboration of taxation and subsidies in contests," Working Papers 2407, Ben-Gurion University of the Negev, Department of Economics.
    13. Ginzburg, Boris, 2019. "A Simple Model of Competitive Testing," MPRA Paper 99463, University Library of Munich, Germany.

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    More about this item

    Keywords

    Optimal contest; Mechanism design; Negative prize; Incomplete information; Cross transfer; Leverage;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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