Investment Incentives in Near-Optimal Mechanisms
- Shengwu Li, Harvard University
- Time: 2020-06-24 21:00
- Host: Dr. Yuqing Kong
- Venue: Online Talk
In a Vickrey auction, if one bidder can invest to increase his value, the combined mechanism including investments is still fully optimal. By contrast, there exist monotone allocation rules that are arbitrarily close to the 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 of the allocative optimum in the worst case, then that guarantee persists when investment is possible.
This is joint work with Mohammad Akbarpour, Scott Kominers, and Paul Milgrom.
Shengwu Li is an economic theorist, studying behavioral economics and market design. He is an assistant professor of economics at Harvard University.
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