Information and Monitoring in Repeated Agency of PartnershipProblems

重复代理合作问题的信息和监测

• 批准号: 8921840
• 负责人: Ennio Stacchetti
• 金额: $ 9.57万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-01-15 至 1992-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8921840&HistoricalAwards=false
• 关键词: Information; Monitoring; Repeated; Agency; PartnershipProblems

The past two decades have seen the development of a large and vital literature on repeated games with discounting. Research in this area has been stimulated both by a succession of theoretical breakthroughs and by a rich variety of economic applications that have emerged, notably in industrial organization, macroeconomics and international trade. Until recently, the models under study shared the feature of "perfect monitoring": in each period, a player in the repeated game knows precisely what actions were taken by other players in all previous periods. Researchers investigating applied problems in different fields became increasingly dissatisfied with the realism of the perfect monitoring assumption and developed models with special kinds of imperfect monitoring. The contribution of this project consists of developing more general and powerful models of imperfect monitoring and confronting the methodological problems that occur in these more realistic models. Traditional agency theory assumes that the principal has no more information about the agent's actions than the enforcement authorities have. This project explores various agency supergames that modify this standard informational structure. In one such model the principal, but not the enforcement agency, can observe the agent's actions. Results obtained by assuming that the principal can only write one-period contracts are extended to allow the principal at any time to freely write long-term contracts, which offer the agent a salary in every future period depending on the publicly observed outcomes. The contracts can be renegotiated at the end of every period. This work provides the basis for extending agency theory to a dynamic setting. Such a theory requires the analyst to solve problems of loss of recursive structure and the negotiation of disequilibrium agreements.

在过去的二十年里，出现了大量关于折扣重复游戏的重要文献。 这一领域的研究受到一系列理论突破和已出现的丰富多样的经济应用的刺激，特别是在产业组织、宏观经济学和国际贸易方面。 直到最近，正在研究的模型都具有“完美监控”的特征：在每个时期，重复博弈中的玩家准确地知道其他玩家在之前所有时期采取了哪些行动。 研究不同领域应用问题的研究人员对完美监测假设的现实性越来越不满意，并开发了具有特殊类型的不完美监测的模型。 该项目的贡献包括开发更通用和更强大的不完善监测模型，并解决这些更现实的模型中出现的方法问题。 传统的代理理论假设委托人并不比执法机构拥有更多关于代理人行为的信息。 该项目探索了修改此标准信息结构的各种机构超级游戏。 在这样的模型中，委托人（而非执行机构）可以观察代理人的行为。 假设委托人只能签订一期合同所得到的结果被扩展为允许委托人在任何时候自由地签订长期合同，根据公开观察到的结果为代理人在未来的每个时期提供薪水。 合同可以在每个周期结束时重新协商。 这项工作为将代理理论扩展到动态环境提供了基础。 这样的理论要求分析者解决递归结构的丢失和不平衡协议的协商问题。