Collaborative Research: Cognitively costly decision making by economic agents: micro and macro implications

合作研究：经济主体的认知成本决策：微观和宏观影响

• 批准号: 1824405
• 负责人: Rosen Valchev
• 金额: $ 24.87万
• 依托单位: Boston College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1824405&HistoricalAwards=false
• 关键词: Collaborative; Research; Cognitively; costly; decision

This award funds research in macroeconomics. The team starts with the observation that many and possibly most economic decisions require time, attention, and careful reasoning. In other words, economic decisions require a specific kind of work called cognitive effort. However, most standard approaches used in macroeconomics assume that people can make their economic decisions instantaneously, with no effort. The research team will develop and analyze a new and tractable model of an entire economy where people, firms, and institutions find that reasoning requires costly cognitive effort. The model allows for the possibility that individuals, businesses, and policymakers may make economic decisions that are not in their long-run best interest simply because determining the best action takes too much time and effort. This is consistent with results from behavioral science. The new model may give us new tools to predict the effects of economic policies, and therefore could contribute to U.S. economic growth as well as advancing fundamental knowledge in economic science.The cognitive limitations studied in this project are not about agents imperfectly observing the relevant state variables such as interest rates, prices, and tax rates. Instead, the focus here is on agents imperfectly computing actions such as hours worked and how much to spend and save. The standard approach in macroeconomics focuses on issues created by imperfect observation and assumes a mapping derived under full rationality. The approach taken in this research is consistent with experimental evidence. Formally, the research starts with the assumption that agents observe the objective states but do not know their optimal policy function. They therefore make rational decisions about how to expend costly cognitive resources to learn about the policy function. The team will first develop a tractable static framework of individual behavior. The key emerging property is that as information accumulates about the unknown policy function, the optimal reasoning choice makes agents' effective actions state and history dependent, leading to non-linearity, endogenous persistence, and volatility clustering. The non-linearity generates both inertia to small shocks, and a salience like effect for large shocks. The second project extends the theoretical analysis to a dynamic setting where agents fully anticipate how current reasoning choices impact future utility and choices. The third project sets the mechanism in a representative agent macro model and studies its aggregate implications, where the non-linear features of the micro behavior are likely to re-surface in aggregate outcomes. There the cognitive limitations that affect individual decision rules as well as the preception of general equilibrium effects are jointly analyzed. The fourth project introduces heterogeneity and incomplete markets.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.

该奖项资助宏观经济学研究。该团队首先观察到，许多（可能是大多数）经济决策需要时间、注意力和仔细的推理。换句话说，经济决策需要一种特定的工作，称为认知努力。然而，宏观经济学中使用的大多数标准方法都假设人们可以毫不费力地立即做出经济决策。该研究团队将开发和分析一个新的和易于处理的整个经济模型，其中人们，公司和机构发现推理需要昂贵的认知努力。该模型考虑到个人、企业和政策制定者可能会做出不符合其长期最佳利益的经济决策，因为确定最佳行动需要花费太多时间和精力。这与行为科学的结果是一致的。新模型可能为我们提供新的工具来预测经济政策的效果，因此可能有助于美国的经济增长以及推进经济科学的基础知识。本项目中研究的认知局限性并不是关于代理人不完美地观察相关的状态变量，如利率，价格和税率。相反，这里的重点是代理不完美地计算动作，如工作时间和花费和节省多少。宏观经济学的标准方法关注的是不完美的观察所产生的问题，并假设在完全理性的情况下得出的映射。本研究中采用的方法与实验证据一致。形式上，该研究从代理观察目标状态但不知道其最优策略函数的假设开始。因此，他们会理性地决定如何花费昂贵的认知资源来了解政策功能。该团队将首先开发一个易于处理的个人行为静态框架。关键的新兴属性是，随着有关未知政策函数的信息积累，最佳推理选择使代理人的有效行动依赖于状态和历史，从而导致非线性、内生持续性和波动性聚集。非线性产生小冲击的惯性和大冲击的显著性效应。第二个项目将理论分析扩展到一个动态环境，在这个环境中，代理商充分预测当前的推理选择如何影响未来的效用和选择。第三个项目将该机制设置在一个代表性的代理宏观模型中，并研究其总体影响，其中微观行为的非线性特征可能会在总体结果中重新出现。在那里，影响个人决策规则的认知局限性，以及一般均衡效应的概念共同分析。第四个项目介绍了异质性和不完全市场。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Economic Agents as Imperfect Problem Solvers

经济主体作为不完美的问题解决者

• DOI: 10.1093/qje/qjac027
• 发表时间: 2022
• 期刊: The Quarterly Journal of Economics
• 作者: Ilut, Cosmin;Valchev, Rosen
• 通讯作者: Valchev, Rosen