摘要翻译：
我们研究了信息扰动如何破坏双边匹配市场的稳定。在我们的模型中，代理商分两个阶段到达市场，而第一阶段的代理商不知道后来到达的代理商的类型。市场上已经存在的代理商可能会提前匹配或等待一小群新进入者。尽管缺乏折扣或风险规避，但这种扰动产生了提前匹配和在新代理到来之前离开市场的激励。这些激励因素不会随着市场规模的扩大而消失。此外，我们在这种情况下发现了一个新的不利现象：当市场变大时，\emph{混沌}--现有代理的早期匹配方案对成对偏差没有鲁棒性--的概率接近1。这些结果独立于代理类型的分布，对市场双方之间的不对称具有鲁棒性。因此，我们的发现表明，配对市场对制度细节和不确定性极其敏感。
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英文标题：
《Chaos and Unraveling in Matching Markets》
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作者：
Songzi Du, Yair Livne
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最新提交年份：
2010
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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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：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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英文摘要：
  We study how information perturbations can destabilize two-sided matching markets. In our model, agents arrive on the market over two periods, while agents in the first period do not know the types of those arriving later. Agents already present in the market may match early or wait for the small group of new entrants. Despite the lack of discounting or risk aversion, this perturbation creates incentives to match early and leave the market before the new agents arrive. These incentives do not disappear as the market gets large. Moreover, we identify a new adverse phenomenon in this setting: as markets get large the probability of \emph{chaos} -- where no early matching scheme for existing agents is robust to pairwise deviations -- approaches 1. These results are independent of the distribution of agents' types and robust to asymmetries between the two sides of the market. Our findings thus suggest that matching markets are extremely sensitive to institutional details and uncertainty.
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PDF链接：
https://arxiv.org/pdf/1009.0769