Investment Incentives in Near-Optimal Mechanisms

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See all articles by Mohammad Akbarpour

Mohammad Akbarpour

Stanford University

Scott Duke Kominers

Harvard University

Shengwu Li

Harvard University - Society of Fellows

Paul R. Milgrom

Stanford University

Date Written: February 25, 2020

Abstract

In a Vickrey auction, if one bidder can invest to increase his value, the combined mechanism including investments is still fully optimal. By contrast, for any β < 1, there exist monotone allocation rules that guarantee a fraction β of the allocative optimum in the worst case, but such that the associated mechanism with investments by one bidder can lead to arbitrarily small fractions of the full optimum being achieved. We show that if a monotone allocation rule “excludes bossy negative externalities” and guarantees a fraction β in the worst case, then that guarantee persists when investment is possible.

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

JEL Classification: D44, D47, D82

Suggested Citation

Akbarpour, Mohammad and Kominers, Scott Duke and Li, Shengwu and Milgrom, Paul R., Investment Incentives in Near-Optimal Mechanisms (February 25, 2020). Available at SSRN: https://ssrn.com/abstract=

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/

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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