Collaborative Research: Dynamic Rational Inattention: Theory and Applications

合作研究：动态理性注意力不集中：理论与应用

• 批准号: 1461469
• 负责人: David Dillenberger
• 金额: $ 15.09万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1461469&HistoricalAwards=false
• 关键词: Collaborative; Research; Dynamic; Rational; Inattention

Models of rational inattention have proved to be useful in understanding many economic phenomena, such as price and investment stickiness, asymmetric response of consumption to income shocks, and coordination failure. The proposed research will provide a new tool to analyze and interpret these - as well as other issues that pertain to economic agents' limitations on the ability to process information - via a new class of dynamic rational inattention models that have a recursive form. The key component in these models is an Infinite Horizon Attention Constraint (IHAC), which captures the intertemporal trade-off in acquiring information. An IHAC specifies what type of information is affordable today, and how the choice of what to learn today affects the possible choices of information tomorrow and in the future. The IHAC is universal in a well-defined sense and yet it - as well as all the other parameters of the model, such as state dependent utilities and the anticipated evolution of beliefs over states - can be uniquely identified from choice behavior.First, the proposed research will characterize axiomatically the types of behavior that can be described by the model. Second, it will develop applications of the model that generate new theoretical predictions, both in the realm of individual decision making and in the context of strategic interactions, and in different areas, ranging from macro-economic phenomena to the explanation of evidence collected by psychologists and economists in laboratory experiments. For example, the model can capture notions such as expertise and fatigue in acquiring information and gives rise to new behavioral phenomena such as familiarity bias. It will also generate new insights about policies that might ameliorate inefficient attention choices. The relevance of this issue is underscored by the current debate about the role exhausted attention seems to play in trapping people in poverty (see Mani et. al. 2013 and Mullainathan and Shafir, 2013).

事实证明，理性忽视模型有助于理解许多经济现象，如价格和投资粘性、消费对收入冲击的不对称反应以及协调失败。这项拟议的研究将提供一种新的工具，通过一类具有递归形式的动态理性注意力不集中模型来分析和解释这些问题以及其他与经济主体处理信息的能力限制有关的问题。这些模型中的关键部分是无限视界注意约束(IHAC)，它捕捉到了在获取信息时的跨期权衡。IHAC规定了今天什么类型的信息是负担得起的，以及今天学习什么的选择如何影响明天和未来可能的信息选择。IHAC在定义明确的意义上是普遍的，但它以及该模型的所有其他参数，如状态依赖效用和信念在状态上的预期演变，可以唯一地与选择行为区分开来。首先，拟议的研究将公理地表征该模型可以描述的行为类型。其次，它将开发该模型的应用，在个人决策领域和战略互动的背景下，以及从宏观经济现象到心理学家和经济学家在实验室实验中收集的证据的解释等不同领域，产生新的理论预测。例如，该模型可以捕捉到获取信息时的专业知识和疲劳等概念，并产生新的行为现象，如熟悉偏差。它还将产生有关政策的新见解，这些政策可能会改善低效的注意力选择。当前关于注意力耗尽似乎在使人们陷入贫困的过程中所起作用的辩论突出了这一问题的相关性(见Mani et。艾尔2013年和穆莱纳坦和沙菲尔，2013年)。