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Team incentives with imperfect mutual inference

机译：相互激励不完善的团队激励

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摘要

I study the optimal team incentive when the agents can coordinate private actions through repeated interaction with imperfect public monitoring. The agents are able to imperfectly infer each other's private actions via the stochastically correlated measurements. Correlation of measurement noise, besides its risk sharing role in the conventional multiple-agent moral hazard problem, is crucial to the accuracy of each agent's inference. The principal's choice of performance pay to provide incentive via inducing competition or coordination among the agents thus exhibits the trade-off between risk sharing and mutual inference between the agents. I characterize the optimal form of performance pay with respect to the correlation of measurement noise. Whether the conventional theoretical prediction holds depends on how the agents form the mutual inference, based on an exogenous standard or formed endogenously.
机译：当代理商可以通过反复互动与不完善的公共监控来协调私人行动时，我研究了最佳团队激励。代理可以通过随机相关的度量完美地推断彼此的私人行动。除了在传统的多主体道德风险问题中承担风险分担作用外，测量噪声的相关性对于每个主体推理的准确性至关重要。委托人选择绩效工资以通过在代理之间进行竞争或协调来提供激励，从而在代理之间的风险分担和相互推断之间表现出权衡。我描述了相对于测量噪声相关性的最佳绩效薪酬形式。常规的理论预测是否成立取决于基于外生标准还是内生形成的相互推论。

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