错误代理的稳定匹配

Georgy Artemov, Yeon-Koo Che, YingHua He
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引用次数: 3

摘要

由于越来越多的证据表明智能体在策略简单的环境中会犯错误,我们提出了一个解决方案概念——稳健均衡——它只需要一个渐近最优行为。我们用它来研究由申请人提出延期接受操作的大型随机匹配市场。尽管说真话是一种优势策略,但在稳健均衡中,几乎所有申请者都可能不诚实;然而,结果必须任意接近稳定匹配。我们的研究结果表明,人们可以假设真实的代理人理论或反事实地研究延迟接受结果。然而,为了估计错误行为者的偏好,人们应该假设稳定的匹配,而不是说实话。
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Stable Matching with Mistaken Agents
Motivated by growing evidence of agents’ mistakes in strategically simple environments, we propose a solution concept—robust equilibrium—that requires only an asymptotically optimal behavior. We use it to study large random matching markets operated by applicant-proposing deferred acceptance. Although truth telling is a dominant strategy, almost all applicants may be nontruthful in robust equilibrium; however, the outcome must be arbitrarily close to the stable matching. Our results imply that one can assume truthful agents to study deferred acceptance outcomes theoretically or counterfactually. However, to estimate the preferences of mistaken agents, one should assume stable matching but not truth telling.
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