Bounded Rationality and Macroeconomic Policy

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，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。理性期望（RE）方法提供了期望形成的基准理论：假设期望是理性的，因为在给定可用信息的情况下，代理不会犯任何系统错误。与可再生资源相关的两个基本问题是可达性，即有界理性主体是否可以通过学习过程达到可再生资源，以及多个可再生资源均衡的可能性。在有限理性方向上对可再生能源的额外现实放宽可能对宏观经济政策产生潜在的重大影响。拟议的研究调查了学习和有限理性对商业周期、资产价格和宏观经济政策的影响。这项研究建立在早期关于学习和模型错误规范的理论工作的基础上。这项研究集中在五个相互关联的研究领域。流动性陷阱、学习和停滞。在适应性学习模式下，经济在遭受严重负面冲击后，有可能陷入通缩螺旋和停滞。该项目研究货币和财政政策的正确组合如何避免通货紧缩和经济停滞。（ii）内源性注意力不集中。本项目考虑在选择最佳信息获取速度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，由于信息获取率的内生变化，可以降低价格和产出方差。参数化不足和内生波动。这一系列研究表明，在错误指定的模型之间动态预测器选择如何导致宏观数据中明显存在的参数漂移和状态切换。（四）近乎理性的繁荣。这个项目表明，在某些条件下，在经济预测中使用判断会导致本来表现良好的模型出现自我实现的波动。研究了避免这种繁荣均衡风险的政策。结构不确定和货币政策。政策所需的关键结构参数的不确定性加剧了学习过程中不确定性或不稳定性的潜在风险。这项研究展示了如何设计将这些风险最小化的最佳政策规则。与这些研究方向相关的技术主题也被探讨，包括替代学习机制、多元模型中的共振频率太阳黑子、教育稳定性、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，也进行了调查。该项目的更广泛目标是告知政策制定者需要考虑私人代理人和政策制定者自己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越来越认识到学习、预期、模型不确定性和货币和财政政策错定性的重要性，近年来克利夫兰和亚特兰大联邦储备银行、德国央行和欧洲央行就这些主题举行的研讨会和会议表明了这一点。一些拟议的项目是与联邦储备系统的研究人员合作的。预期这项研究将在大学、中央银行和高级别会议的讨论会、讲习班和会议上广泛传播。该项目还将支持研究生的研究。过去由PI提供的NSF资助支持了相关主题的研究，并导致了博士论文和研究型大学的学术任命。

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.