减少二维筛选中的激励约束

Braulio Calagua
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引用次数: 0

摘要

本文研究的是具有准线性偏好的筛选问题,即代理人的私人信息是二维的,而分配工具是一维的。我们定义了一个前序,根据类型对工具的边际估值对其进行比较,这有助于减少必须检查的激励相容约束。通过这种方法,离散化问题在计算上变得简单易行。作为应用,我们用数值方法解决了 Lewis & Sappington(1988)提出的一个问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reducing incentive constraints in bidimensional screening
This paper studies screening problems with quasilinear preferences, where agents' private information is two-dimensional and the allocation instrument is one-dimensional. We define a preorder to compare types based on their marginal valuation to the instrument, which facilitates the reduction of incentive compatibility constraints that must be checked. With this approach, the discretized problem becomes computationally tractable. As an application, we numerically solve a problem introduced by Lewis & Sappington (1988)
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