Algorithmic Mechanism Design With Investment

被引：0
|
作者：
Akbarpour, Mohammad [1 ]
Kominers, Scott Duke [2 ,3 ]
Li, Kevin Michael [4 ]
Li, Shengwu [5 ]
Milgrom, Paul [6 ]
机构：
[1] Stanford Univ, Grad Sch Business, Stanford, CA 94305 USA
[2] Harvard Univ, Harvard Business Sch, Dept Econ, Entrepreneurial Management Unit, Cambridge, MA USA
[3] A16z crypto, Silicon Valley, CA USA
[4] Stanford Univ, Dept Econ, Stanford, CA USA
[5] Harvard Univ, Dept Econ, Cambridge, MA USA
[6] Stanford Univ & Auct, Dept Econ, Stanford, CA USA
来源：
ECONOMETRICA | 2023年 / 91卷 / 06期
基金：
美国国家科学基金会;
关键词：
Combinatorial optimization; Knapsack problem; investment; auctions; approximation; algorithms; COMBINATORIAL; INCENTIVES;
D O I：
10.3982/ECTA19559
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
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.
引用
收藏
页码：1969 / 2003
页数：35
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