Advancing Methods for Analyzing Coordination: New Developments in Global Game Theory.

改进协调分析方法：全球博弈论的新发展。

• 批准号: 2001208
• 负责人: Stephen Morris
• 金额: $ 11.39万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2001208&HistoricalAwards=false
• 关键词: Advancing; Methods; Analyzing; Coordination; New

This award funds research in economic theory, with a focus on coordination games. This theory can be used to analyze a wide variety of economic problems, including financial crises and business cycles. While the standard coordination game approach offers insight into these settings, it allows multiple equilibria and thus does not offer a complete theory in the absence of a theory of equilibrium selection. In response, a global games approach has been widely used in applied economics. By assuming noisy information about payoffs, one can remove the multiplicity of equilibria and develop a wide variety of predictions that can then be tested against data. However, there are a number of important limitations to the global games approach. The four components of this research proposal address four different limitations. The components are relevant for all global game applications, but are developed in the context of applications in macroeconomics, political economy and finance. The project therefore contributes to developing new theories and methods that can help individuals, businesses, and policymakers at all levels of government make better decisions. Global game analysis has made extreme informational assumptions: there is common knowledge of payoffs and multiple equilibria, or small noise and globally unique equilibria. The project has four components, each designed to address one aspect of these assumptions. The first component examines richer classes of information structures to develop novel predictions about when global game predictions arise. Global game analysis has been primarily static. The second component examines dynamic environments with learning to develop predictions about when global game predictions occur. Global game analysis has focused on binary action games. The third component analyzes a political economy application where feasible set of available actions is itself a choice variable, and characterizes when the action set is or is not binary. Global game analysis has mostly relied on simple analytic solutions to deliver qualitative insights. The fourth component develops a finance application with a rich set of heterogeneous players in order to develop quantitative framework that that can be used in empirical work.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项为经济理论的研究提供了资金，重点是协调游戏。该理论可用于分析各种经济问题，包括金融危机和商业周期。尽管标准的协调游戏方法提供了对这些设置的见解，但它允许多个平衡，因此在没有平衡选择理论的情况下没有提供完整的理论。作为回应，全球游戏方法已被广泛用于应用经济学。通过假设有关收益的嘈杂信息，可以消除平衡的多样性并产生各种各样的预测，然后可以根据数据进行测试。但是，全球游戏方法有许多重要的局限性。该研究建议的四个组成部分解决了四个不同的局限性。这些组件与所有全球游戏应用都相关，但是在宏观经济，政治经济学和金融中应用的背景下开发的。 因此，该项目有助于开发新的理论和方法，这些理论和方法可以帮助各个层面的个人，企业和政策制定者做出更好的决定。全球游戏分析提出了极端的信息假设：收益和多重均衡存在常识，或者是噪音小，全球独特的平衡知识。该项目有四个组件，每个组件旨在解决这些假设的一个方面。第一个组件研究了更丰富的信息结构，以开发有关何时出现全球游戏预测的新颖预测。全球游戏分析主要是静态的。第二个组件通过学习来开发有关何时进行全局游戏预测的预测来研究动态环境。全球游戏分析集中在二元动作游戏上。第三个组成部分分析了一种政治经济学应用，其中可行的可用行动本身就是一个选择变量，并且表征了何时或不是二元的动作。全球游戏分析主要依靠简单的分析解决方案来提供定性见解。第四个组件开发了具有丰富异质玩家的财务应用程序，以开发可用于经验工作的定量框架。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准通过评估来进行评估的。