分配稳健性:从定价到拍卖

Nir Bachrach, Inbal Talgam-Cohen
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引用次数: 4

摘要

我们研究了在拍卖中出售单个物品时收益最大化的稳健机制设计,假设只有价值分布的平均值和竞标者对物品的估价的上界是已知的。鲁棒机制设计是贝叶斯机制设计的一个新兴替代方案,它产生的设计不依赖于像完全分布知识这样的假设,而是只依赖于分布的部分知识。我们寻求一种机制,使收益在与已知参数兼容的最坏情况分布上最大化。这种机制产生于卖方和选择分配的对手之间的零和博弈的平衡,因此可以被称为最大-最小机制。Carrasco等人[2018]推导出卖方面对单一竞标者时的最大最小定价。通过研究两个竞标者的典型设置,从最大最小定价到最大最小拍卖,表明最大最小机制是随机预留的二次价格拍卖。我们导出了储备价格分布的封闭解,以及最坏情况值分布,这有简单的经济学直觉。我们还推导了任意数量投标人的最大最小保留价格分布的封闭形式解,并且我们证明了与两个投标人的情况不同,具有随机保留的第二价格拍卖不可能是两个以上投标人的均衡。我们解决零和博弈的技术与Carrasco等人的完全不同——我们关注的是一个简化的零和博弈,卖家只能选择一个随机保留价格(而不是任何机制)的第二价格拍卖的分配。然后,我们分析一个离散版本的设置,以找到平衡将满足的条件。通过细化离散化网格,我们可以得到微分方程,并求解它们得到封闭形式的非离散化分布。卖方和对手的最终分布后来被证明是减少的零和博弈的均衡。对于两个竞标者的情况,我们将结果扩展到原始零和博弈的均衡,其中卖方不限于带保留价的二次拍卖。该论文的完整版本可在https://arxiv.org/abs/2205.09008上获得。
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Distributional Robustness: From Pricing to Auctions
We study robust mechanism design for revenue maximization when selling a single item in an auction, assuming that only the mean of the value distribution and an upper bound on the bidders' valuations for the item are known. Robust mechanism design is a rising alternative to Bayesian mechanism design, which yields designs that do not rely on assumptions like full distributional knowledge, but rather only partial knowledge of the distributions. We seek a 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. We also derive a closed-form solution for the max-min reserve price distribution for any number of bidders, and we show that unlike the case of two bidders, a second-price auction with a randomized reserve cannot be an equilibrium for more than two bidders. Our technique for solving the zero-sum game is quite different than that of Carrasco et al. -- we focus on a reduced zero-sum game, where the seller can only choose a distribution for a second-price auction with a randomized reserve price (rather than any mechanism). We then analyze a discretized version of the setting to find conditions an equilibrium would satisfy. By refining the discretization grid, we are able to achieve differential equations, and solving them yields closed-form non-discretized distributions. The resulting distributions for the seller and the adversary are later shown to be an equilibrium for the reduced zero-sum game. For the two-bidder case, we expand our result to an equilibrium of the original zero-sum game, where the seller is not limited to second price auctions with reserve. The full version of the paper is available at https://arxiv.org/abs/2205.09008.
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