Distributional Robustness: From Pricing to Auctions

Abstract

Robust mechanism design is a rising alternative to Bayesian mechanism design, which yields designs that do not rely on assumptions like full distributional knowledge. We apply this approach to mechanisms for selling a single item, assuming that only the mean of the value distribution and an upper bound on the bidder values are known. We seek the mechanism that maximizes revenue over the worst-case distribution compatible with the known parameters. Such a mechanism arises as an equilibrium of a zero-sum game between the seller and an adversary who chooses the distribution, and so can be referred to as the max-min mechanism.Carrasco et al. [2018] derive the max-min pricing when the seller faces a single bidder for the item. We go from max-min pricing to max-min auctions by studying the canonical setting of two i.i.d. bidders, and show the max-min mechanism is the second-price auction with a randomized reserve. We derive a closed-form solution for the distribution over reserve prices, as well as the worst-case value distribution, for which there is simple economic intuition. In fact we derive a closed-form solution for the reserve price distribution for any number of bidders.Our technique for solving the zero-sum game is quite different than that of Carrasco et al.it involves analyzing a discretized version of the setting, then refining the discretization grid and deriving a closed-form solution for the non-discretized, original setting. Our results establish a difference between the case of two bidders and that of n ≥ 3 bidders.

Prior-Independent Auctions for Heterogeneous Bidders

“…[Deng et al, 2019, Braverman et al, 2021). Another approach towards robust auction design is that of distributionally-robust auctions which assumes that the auctioneer has knowledge of some summary statistics of the distribution such as the mean and the upper limit of the support, and characterizes the max-min performance, i.e., under the worst case distribution (see [Bachrach andTalgam-Cohen, 2022, Che, 2019]. A very recent work of Anunrojwong, Balseiro, and Besbes [2022] also tackles the question of designing optimal mechanisms for prior-independent distributions but considers the benchmark of regret.…”