Optimal Sequential Screening with Ex Post Participation Constraint

T. Heumann
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引用次数: 4

Abstract

We study a principal-agent model. The parties are symmetrically informed at first; the principal then designs the screening mechanism and, concurrently, the process by which the agent learns his type. Because the agent can opt out of the mechanism ex post, it must leave him with nonnegative rents ex post. We characterize the profit-maximizing mechanism. In that optimal mechanism, learning proceeds in continuous time and, at each moment, the agent learns a lower bound on his type. For each type, there is one of two possible outcomes: the type is allocated the efficient quantity or is left with zero rents ex post.
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具有事后参与约束的最优顺序筛选
我们研究了一个委托代理模型。当事人一开始是对称知情的;然后,委托人设计筛选机制,同时设计代理学习其类型的过程。因为代理可以选择事后退出该机制,所以事后必须给他留下非负租金。我们描述了利润最大化机制。在该最优机制中,学习在连续时间内进行,并且在每个时刻,智能体学习其类型的下界。对于每种类型,都有两种可能的结果之一:该类型被分配到有效数量,或者事后租金为零。
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