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Algorithmic Mechanism Design With Investment

Author

Listed:
  • Mohammad Akbarpour
  • Scott Duke Kominers
  • Kevin Michael Li
  • Shengwu Li
  • Paul Milgrom

Abstract

We study the investment incentives created by truthful mechanisms that allocate resources using approximation algorithms. Some approximation algorithms guarantee nearly 100% of the optimal welfare in the allocation problem but guarantee nothing when accounting for investment incentives. An algorithm's allocative and investment guarantees coincide if and only if its confirming negative externalities are sufficiently small. We introduce fast approximation algorithms for the knapsack problem that have no confirming negative externalities and guarantees close to 100% for both allocation and investment.

Suggested Citation

  • Mohammad Akbarpour & Scott Duke Kominers & Kevin Michael Li & Shengwu Li & Paul Milgrom, 2023. "Algorithmic Mechanism Design With Investment," Econometrica, Econometric Society, vol. 91(6), pages 1969-2003, November.
    • Handle: RePEc:wly:emetrp:v:91:y:2023:i:6:p:1969-2003
    DOI: 10.3982/ECTA19559
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    References listed on IDEAS

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    5. Tomoeda, Kentaro, 2019. "Efficient investments in the implementation problem," Journal of Economic Theory, Elsevier, vol. 182(C), pages 247-278.
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    Cited by:

    1. Ce Li & Qianfan Zhang & Weiqiang Zheng, 2025. "From Best Responses to Learning: Investment Efficiency in Dynamic Environment," Papers 2511.01157, arXiv.org.

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