摘要翻译：
我们利用先验独立的简单机制来考虑双边市场中的福利最大化问题。Myerson-Satterthwaite不可能定理表明，即使对于双边贸易，也不存在一个可行的（IR,真实的，预算平衡的）机制，它的福利达到最优但不可行的VCG机制，即获得最大福利但出现赤字。另一方面，最优可行机制需要仔细定制贝叶斯先验，并且极其复杂，难以精确描述。我们提出了Bulow-Klemperer式的结果，以规避双重拍卖市场中的这些障碍。我们建议使用买方交易减少(BTR)机制，这是McAfee机制的一种变体，它既可行又简单（特别是确定性、真实性、先验独立性、匿名性）。首先，在买家和卖家的价值被I.I.D.抽样的情况下。从同一分布出发，我们证明了对于任何规模的此类市场，具有一个额外买方且其价值取自同一分布的BTR的期望福利至少与原始市场的最优值一样高。然后我们转向一个更一般的设置，其中买方的价值从一个分布中取样，卖方的价值从另一个分布中取样，重点讨论买方的一阶分布随机支配卖方的情况。我们给出了购买人数的界限，当增加时，保证BTR在扩大市场中的福利至少与原始市场中的最优值一样高。我们的下限扩展到一大类机制，我们所有的结果都扩展到增加卖方而不是买方。此外，在上述两种情形下，我们给出了关于在双边市场中福利最大化的样本定价有用性的实证结果，据我们所知，这是在此背景下的第一次抽样结果。
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英文标题：
《Bulow-Klemperer-Style Results for Welfare Maximization in Two-Sided
  Markets》
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作者：
Moshe Babaioff, Kira Goldner, Yannai A. Gonczarowski
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最新提交年份：
2019
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computer Science and Game Theory        计算机科学与博弈论
分类描述：Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
涵盖计算机科学和博弈论交叉的所有理论和应用方面，包括机制设计的工作，游戏中的学习（可能与学习重叠），游戏中的agent建模的基础（可能与多agent系统重叠），非合作计算环境的协调、规范和形式化方法。该领域还涉及博弈论在电子商务等领域的应用。
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一级分类：Economics        经济学
二级分类：Theoretical Economics        理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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英文摘要：
  We consider the problem of welfare maximization in two-sided markets using simple mechanisms that are prior-independent. The Myerson-Satterthwaite impossibility theorem shows that even for bilateral trade, there is no feasible (IR, truthful, budget balanced) mechanism that has welfare as high as the optimal-yet-infeasible VCG mechanism, which attains maximal welfare but runs a deficit. On the other hand, the optimal feasible mechanism needs to be carefully tailored to the Bayesian prior, and is extremely complex, eluding a precise description.   We present Bulow-Klemperer-style results to circumvent these hurdles in double-auction markets. We suggest using the Buyer Trade Reduction (BTR) mechanism, a variant of McAfee's mechanism, which is feasible and simple (in particular, deterministic, truthful, prior-independent, anonymous). First, in the setting where buyers' and sellers' values are sampled i.i.d. from the same distribution, we show that for any such market of any size, BTR with one additional buyer whose value is sampled from the same distribution has expected welfare at least as high as the optimal in the original market.   We then move to a more general setting where buyers' values are sampled from one distribution and sellers' from another, focusing on the case where the buyers' distribution first-order stochastically dominates the sellers'. We present bounds on the number of buyers that, when added, guarantees that BTR in the augmented market have welfare at least as high as the optimal in the original market. Our lower bounds extend to a large class of mechanisms, and all of our results extend to adding sellers instead of buyers. In addition, we present positive results about the usefulness of pricing at a sample for welfare maximization in two-sided markets under the above two settings, which to the best of our knowledge are the first sampling results in this context.
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PDF链接：
https://arxiv.org/pdf/1903.06696