We consider a principal-agent problem where the agent may privately choose to acquire relevant information prior to taking a hidden action. This model generalizes two special cases: a classic moral hazard setting, and a more recently studied problem of incentivizing information acquisition (IA). We show that all of these problems can be reduced to the design of a proper scoring rule. Under a limited liability condition, we consider the special cases separately and then the general problem. We give novel results for the special case of IA, giving a closed form "pointed polyhedral cone" solution for the general multidimensional problem. We also describe a geometric, scoring-rules based solution to the case of the classic contracts problem. Finally, we give an efficient algorithm for the general problem of Contracts with Information Acquisition.
翻译:我们考虑的是主要代理人可能私下选择在采取隐藏行动之前获得相关信息的问题。这个模型概括了两个特殊案例:典型的道德风险环境,以及最近研究的激励信息获取的问题。我们表明所有这些问题都可以简化为适当的评分规则的设计。在有限责任条件下,我们分别考虑特殊情况,然后考虑一般问题。我们给IA的特殊情况提供新的结果,为一般的多层面问题提供一种封闭形式“指向聚体锥体”的解决办法。我们还描述了典型合同问题的几何、评分规则解决办法。最后,我们为信息获取合同的一般问题提供了一种有效的算法。