Mechanism Design via Optimal Transport

TL;DR

This paper introduces a novel framework using optimal transport and duality theory to design revenue-maximizing mechanisms in complex multi-item auction settings, especially where traditional explicit methods do not apply.

Contribution

It develops a new approach for optimal mechanism design in implicit valuation models, providing conditions for simple pricing and characterizing mechanisms in two-item cases.

Findings

Grand bundle pricing is optimal under certain conditions.

Closed-form solutions for two-item optimal mechanisms.

A continuum of lotteries may be necessary for revenue maximization.

Abstract

Optimal mechanisms have been provided in quite general multi-item settings, as long as each bidder's type distribution is given explicitly by listing every type in the support along with its associated probability. In the implicit setting, e.g. when the bidders have additive valuations with independent and/or continuous values for the items, these results do not apply, and it was recently shown that exact revenue optimization is intractable, even when there is only one bidder. Even for item distributions with special structure, optimal mechanisms have been surprisingly rare and the problem is challenging even in the two-item case. In this paper, we provide a framework for designing optimal mechanisms using optimal transport theory and duality theory. We instantiate our framework to obtain conditions under which only pricing the grand bundle is optimal in multi-item settings (complementing the work of [Manelli and Vincent 2006], as well as to characterize optimal two-item mechanisms. We use our results to derive closed-form descriptions of the optimal mechanism in several two-item settings, exhibiting also a setting where a continuum of lotteries is necessary for revenue optimization but a closed-form representation of the mechanism can still be found efficiently using our framework.