Algorithmic Mechanism Design With Investment.

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...

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Published in:Econometrica Vol. 91; no. 6; pp. 1969 - 2004
Main Authors: Akbarpour, Mohammad, Kominers, Scott Duke, Li, Kevin Michael, Li, Shengwu, Milgrom, Paul
Format: Article
Published: Wiley-Blackwell Nov2023
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Nov2023
      vid: 91
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      pub: Wiley-Blackwell
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        174064829
        10.3982/ECTA19559
      ppf: 1969
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      formats:
      tig:
        atl: Algorithmic Mechanism Design With Investment.
      aug:
        au:
          Akbarpour, Mohammad
          Kominers, Scott Duke
          Li, Kevin Michael
          Li, Shengwu
          Milgrom, Paul
        affil:
          Graduate School of Business, Stanford University
          Entrepreneurial Management Unit, Harvard Business School
          Department of Economics, Harvard University
          a16z crypto
          Department of Economics, Stanford University
          Auctionomics
      su:
        Externalities
        Approximation algorithms
        Knapsack problems
        Combinatorial optimization
      sug:
        subj:
          Externalities
          Approximation algorithms
          Knapsack problems
          Combinatorial optimization
      keyword:
        algorithms
        approximation
        auctions
        investment
        Knapsack problem
        algorithms
        approximation
        auctions
        investment
        Knapsack problem
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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