Algorithmic Mechanism Design with Investment

45 Pages Posted: 13 Apr 2020 Last revised: 8 Nov 2022

See all articles by Mohammad Akbarpour

Mohammad Akbarpour

Stanford University

Scott Duke Kominers

Harvard University; a16z crypto

Kevin Michael Li

affiliation not provided to SSRN

Shengwu Li

Harvard University - Society of Fellows

Paul R. Milgrom

Stanford University

Date Written: November 6, 2022

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, but have only a zero guarantee when one bidder can invest before participating. An algorithm's worst-case allocative and investment guarantees coincide if and only if that algorithm's "confirming negative externalities" are sufficiently small. We introduce new fast approximation algorithms for the knapsack problem that have no confirming negative externalities, with guarantees close to 100% both with and without investments.

Keywords: Combinatorial optimization, Knapsack problem, Investment, Auctions, Approximation, Algorithms

JEL Classification: D44, D47, D82

Suggested Citation

Akbarpour, Mohammad and Kominers, Scott Duke and Li, Kevin Michael and Li, Shengwu and Milgrom, Paul R., Algorithmic Mechanism Design with Investment (November 6, 2022). Available at SSRN: https://ssrn.com/abstract=3544100 or http://dx.doi.org/10.2139/ssrn.3544100

Mohammad Akbarpour

Stanford University ( email )

Scott Duke Kominers

Harvard University ( email )

Rock Center
Harvard Business School
Boston, MA 02163
United States

HOME PAGE: http://www.scottkom.com/

a16z crypto ( email )

Kevin Michael Li

affiliation not provided to SSRN

Shengwu Li (Contact Author)

Harvard University - Society of Fellows ( email )

Cambridge, MA
United States

Paul R. Milgrom

Stanford University ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
+1-650-723-3397 (Phone)
+1-419-791-8545 (Fax)

HOME PAGE: www.milgrom.net

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