Bounded Rationality and Macroeconomic Policy

有限理性与宏观经济政策

• 批准号: 0617859
• 负责人: George Evans
• 金额: $ 16.44万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0617859&HistoricalAwards=false
• 关键词: Bounded; Rationality; Macroeconomic; Policy

A central feature of modern economic theory is forward-looking decision-making by firms and households. Expectations of economic agents are therefore a key component of macroeconomic theories of consumption, investment, inflation and the business cycle. The rational expectations (RE) approach provides the benchmark theory of expectation formation: expectations are assumed to be rational in the sense that agents do not make any systematic errors, given the available information. Two fundamental issues in connection with RE are attainability, i.e. whether boundedly rational agents can arrive at RE through a learning process, and the possibility of multiple RE equilibria. Additional realistic relaxations of RE in the direction of bounded rationality can have potentially major implications for macroeconomic policy. The proposed research investigates the implications of learning and bounded rationality for business cycles, asset prices and macroeconomic policy. The research builds on earlier theoretical work on learning and model misspecification. The research focuses on five interconnected lines of research. (i) Liquidity traps, learning and stagnation. Under adaptive learning there is the possibility of the economy, after severe negative shocks, slipping into a deflationary spiral and stagnation. The project investigates how the right combination of monetary and fiscal policy can avoid disinflation and stagnation. (ii) Endogenous inattention. This project considers the implications for economic fluctuations when the rate of information acquisition is chosen optimally, weighing costs against benefits. Monetary policies that stabilize the aggregate price path can reduce both price and output variance due to endogenous changes in the information acquisition rate. (iii) Underparameterization and endogenous volatility. This line of research shows how dynamic predictor selection between misspecified models can lead to parameter drift and regime switching of the type apparently present in the macro data. (iv) Near-rational exuberance. This project shows that, under certain conditions, the use of judgment in economic forecasting can lead to self-fulfilling fluctuations in otherwise well-behaved models. Policies to avoid the risk of such exuberance equilibria are studied. (v) Structural uncertainty and monetary policy. Uncertainty about key structural parameters needed for policy compounds the potential risks of indeterminacy or instability under learning. This research shows how to devise optimal policy rules that minimize these risks. Technical topics connected with these lines of research are also pursued, including alternative learning mechanisms, resonant frequency sunspots in multivariate models, eductive stability, anticipated policy changes, heterogeneity and empirical calibration. Other applications, such as exchange rate models and asset price behavior, are also investigated. The broader aim of the project is to inform policymakers of the need to take into account adaptive learning and bounded rationality by private agents and policymakers themselves. The importance of learning, expectations, model uncertainty and misspecification for monetary and fiscal policy is increasingly being recognized by central bank research departments and policymakers, as shown by the workshops and conferences on these topics held in recent years by the Cleveland and Atlanta Federal Reserve Banks, the Bundesbank and the European Central Bank. Some of the proposed project is collaborative with researchers in the Federal Reserve System. The research is expected to be disseminated widely in seminars, workshops and conferences, at universities, central banks and high-level conferences. The project will also support the research of graduate students. Past NSF grants by the PI have supported research on related topics and led to PhD theses and academic appointments at research universities.

现代经济理论的一个核心特征是企业和家庭的前瞻性决策。因此，对经济主体的预期是消费、投资、通货膨胀和商业周期等宏观经济理论的关键组成部分。理性预期（RE）方法提供了预期形成的基准理论：预期被假设为理性的，在这个意义上，代理人不会犯任何系统性错误，给定的信息。与RE有关的两个基本问题是可达性，即有限理性代理是否可以通过学习过程到达RE，以及多个RE平衡的可能性。 在有限理性的方向上对可再生能源的进一步现实放松可能对宏观经济政策产生重大影响。 拟议的研究探讨了学习和有限理性的商业周期，资产价格和宏观经济政策的影响。这项研究建立在早期的学习和模型误指定的理论工作。该研究集中在五个相互关联的研究领域。(i)流动性陷阱、学习和停滞。在适应性学习的情况下，经济有可能在严重的负面冲击后陷入通货紧缩和停滞。该项目研究了货币和财政政策的正确组合如何避免通货紧缩和停滞。(ii)内源性注意力不集中该项目考虑了在最佳选择信息获取率时对经济波动的影响，权衡成本与收益。稳定总价格路径的货币政策可以减少由于信息获取率的内生变化而导致的价格和产出方差。(iii)参数化不足与内生波动。这一系列的研究表明，如何动态预测之间的错误指定的模型选择可能会导致参数漂移和政权切换的类型显然存在于宏观数据。(iv)近理性繁荣。该项目表明，在某些条件下，在经济预测中使用判断可能会导致在其他表现良好的模型中出现自我实现的波动。政策，以避免这种繁荣均衡的风险进行了研究。(v)结构不确定性与货币政策。政策所需关键结构参数的不确定性加剧了学习过程中的不确定性或不稳定性的潜在风险。 这项研究表明，如何设计最佳的政策规则，最大限度地减少这些风险。还研究与这些研究领域相关的技术主题，包括替代学习机制、多元模型中的共振频率太阳黑子、推导稳定性、预期政策变化、异质性和经验校准。其他应用，如汇率模型和资产价格行为，也进行了研究。该项目更广泛的目标是让决策者认识到需要考虑到私人代理人和决策者本身的适应性学习和有限理性。中央银行研究部门和政策制定者日益认识到学习、预期、模型不确定性和错误设定对货币和财政政策的重要性，克利夫兰和亚特兰大联邦储备银行、德国央行和欧洲中央银行近年来就这些主题举办的讲习班和会议就表明了这一点。一些拟议的项目是与联邦储备系统的研究人员合作。预计将在大学、中央银行和高级别会议的研讨会、讲习班和会议上广泛传播这项研究。该项目还将支持研究生的研究。PI过去的NSF拨款支持了相关主题的研究，并导致了研究型大学的博士论文和学术任命。