Models of Dynamic Choice

动态选择模型

• 批准号: 1123729
• 负责人: Tomasz Strzalecki
• 金额: $ 27.29万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1123729&HistoricalAwards=false
• 关键词: Models; Dynamic; Choice

This award funds research in economic decision theory. There are four distinct projects. Each seeks to develop new methods for incorporating aspects of human behavior into formal mathematical models of decision making.The first project builds on previous work by other scholars (Kreps-Porteous and Epstein-Zin) that developed recursive utility models. This project models the premium that an individual with preferences represented by this kind of utility function would pay for the early resolution of uncertainty; in other words, what fraction of his income would the individual be willing to give up in order to learn his future consumption levels? This premium can be used as a criterion for the choice of parameter values in recursive utility models.The second project studies boundedly optimizing decision amkers operating in otherwise standard competitive financial markets with standard preferences. The new theory yields a number of predictions: limited market participation, ex post consumption heterogeneity, and high volatility of asset prices as compared to the fundamentals.Project Three provides a novel axiomatization of quasi-hyperbolic discounting. This model of preferences over time is increasingly widely used in applications of behavioral economics. The proposed axiomatization and the implied method of parameter measurement are useful for experimental work. These methods make it possible to elicit short run discount factors independent of utility functions. The goal is to develop a method that will eliminate experimental confounds that are unavoidable with current methods.Project Four studies a model of individual decisions makers who do not fully recognize the extent to which their future choices disregard their current preferences. The project proposes a method of eliciting such inaccurate beliefs about the future. The goal is to explain such behavior by studying how these failures of learning can persist in the long run.Models of dynamic decisions are key to understanding many economic phenomena, such as savings, investment, taxation, and growth. This research will improve the toolbox available to model these phenomena. The result will be new methods to analyze the effects of economic behavior and economic policy. The methods will be useful not just to economists but also to decision theorists and financial scholars.

该奖项用于经济决策理论的研究。有四个截然不同的项目。每个项目都寻求开发新的方法，将人类行为的各个方面纳入决策的正式数学模型。第一个项目建立在其他学者(Kreps-Porteous和Epstein-Zin)开发递归效用模型的先前工作的基础上。这个项目模拟了具有这种效用函数所代表的偏好的个人为早期解决不确定性而支付的溢价；换句话说，为了了解他未来的消费水平，这个人愿意放弃他收入的多少部分？这一溢价可以作为递归效用模型中参数值选择的标准。第二个项目研究了在具有标准偏好的其他标准竞争金融市场中操作的有界优化决策决策者。新理论产生了一些预测：有限的市场参与，消费后的异质性，以及与基本面相比资产价格的高波动性。项目三提供了准双曲线贴现的新公理化。这种偏好随时间变化的模型越来越广泛地应用于行为经济学。所提出的公理化和隐含的参数测量方法对实验工作是有用的。这些方法使得获得不依赖于效用函数的短期贴现因子成为可能。我们的目标是开发一种方法，以消除当前方法不可避免的实验混淆。项目四研究了一个个体决策者的模型，这些决策者没有完全认识到他们未来的选择在多大程度上忽视了他们目前的偏好。该项目提出了一种方法来引出对未来的这种不准确的信念。其目的是通过研究这些学习失败如何长期存在来解释这种行为。动态决策模型是理解许多经济现象的关键，如储蓄、投资、税收和增长。这项研究将改进可用于模拟这些现象的工具箱。其结果将是分析经济行为和经济政策影响的新方法。这些方法不仅对经济学家有用，而且对决策理论家和金融学者也有用。