ICES: Small: Collaborative Research: Interaction, Information and Identification

ICES：小型：协作研究：交互、信息和识别

• 批准号: 1215808
• 负责人: Dirk Bergemann
• 金额: $ 19.99万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1215808&HistoricalAwards=false
• 关键词: ICES; Small; Collaborative; Research; Interaction

Private and widely dispersed information across individuals is pervasive aspect of economic environments. In financial markets, traders possess different information about the value of an asset; in labor markets, employees and employers have different information about the cost of a job. In the interaction of the individual agents, the nature of the private information held by the individuals influences the outcome of the entire economy. In particular, the structure of the interaction - the form of the network - determines the aggregate outcome. Yet from the point of view of an observer, be it as an analyst or a regulator or a legislator, the precise nature of the private information and network structure of the agents is rarely known. The current research develops a method to analyze the behavior and the welfare in an economic environment, online as well as offline, independent of the structure of the private information and network structure of the agents. Concurrently, the investigators will analyze the extent to which the structure of the economic environments (payoffs, preferences) can be identified from the empirical data without knowledge of the exact information and network structure. The methods have epistemic and computational advantages over earlier approaches. The investigators will identify bounds on the statistical moments of the equilibrium distribution. Conversely, the statistical description of the equilibrium outcome allows the investigators to give precise bounds on how much can be learned from the data when the nature of the private information is unknown. This new approach to networks with private information offers techniques to analyze the welfare implications of economic rules and institutions by providing bounds that are independent of the knowledge of the information and network structure. The method allows the investigators to assess the implications of different policies and regulations regarding information disclosure, trading restrictions, and reserve requirements that are independent of the specific information held by the economic agents.

私人和广泛分散在个人之间的信息是经济环境中普遍存在的方面。在金融市场中，交易者掌握着不同的资产价值信息;在劳动力市场中，雇员和雇主掌握着不同的工作成本信息。在个体行为者的相互作用中，个体所拥有的私人信息的性质影响着整个经济的结果。具体而言，互动的结构--网络的形式--决定了总体结果。然而，从观察者的角度来看，无论是分析师、监管者还是立法者，都很少知道代理人的私人信息和网络结构的确切性质。目前的研究开发了一种方法来分析的行为和福利的经济环境中，在线以及离线，独立的私人信息和网络结构的代理。与此同时，研究人员将分析在不了解确切信息和网络结构的情况下，经济环境结构（收益、偏好）可以从经验数据中识别的程度。该方法具有认知和计算的优势，比以前的方法。研究人员将确定平衡分布的统计矩的界限。相反，当私人信息的性质未知时，对均衡结果的统计描述允许研究者给出从数据中可以学到多少的精确界限。 这种新的方法与私人信息的网络提供的技术，分析福利的影响，经济规则和机构提供的界限是独立的知识的信息和网络结构。该方法允许调查人员评估不同的政策和法规的影响，这些政策和法规涉及独立于经济主体所持有的特定信息的信息披露、交易限制和储备要求。