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

该奖项资助经济理论研究，重点是协调博弈。这一理论可以用来分析各种各样的经济问题，包括金融危机和商业周期。虽然标准的协调博弈方法提供了对这些设置的洞察，但它允许多个均衡，因此在缺乏均衡选择理论的情况下不能提供完整的理论。作为回应，全球博弈方法在应用经济学中得到了广泛应用。通过假设关于收益的噪声信息，一个人可以消除均衡的多重性，并开发出各种预测，然后可以针对数据进行测试。然而，全球游戏的方法有许多重要的限制。这项研究提案的四个组成部分解决了四个不同的限制。这些组件与所有全球游戏应用程序相关，但都是在宏观经济、政治经济学和金融应用程序的背景下开发的。因此，该项目有助于开发新的理论和方法，帮助个人、企业和各级政府的政策制定者做出更好的决策。全球博弈分析做出了极端的信息性假设：存在关于收益和多重均衡的常识，或者关于小噪声和全球唯一均衡的常识。该项目有四个组成部分，每个组成部分都旨在解决这些假设的一个方面。第一个部分考察了更丰富的信息结构类别，以开发关于全球比赛预测何时出现的新预测。全球博弈分析主要是静态的。第二个组件检查动态环境，学习如何制定关于全球比赛预测何时发生的预测。全球游戏分析的重点是二元动作游戏。第三部分分析政治经济学应用，其中可用动作的可行集合本身是选择变量，并且表征动作集合何时是或不是二进制的。全球博弈分析主要依靠简单的分析解决方案来提供定性的见解。第四个组成部分开发了一个具有丰富的不同参与者集合的财务应用程序，以开发可用于实证工作的量化框架。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.