Collaborative Research: Perturbation Methods for Markov-Switching Models

协作研究：马尔可夫切换模型的扰动方法

• 批准号: 1223198
• 负责人: Juan Rubio-Ramirez
• 金额: $ 23.7万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1223198&HistoricalAwards=false
• 关键词: Collaborative; Research; Perturbation; Methods; Markov

AbstractProposal Title: Collaborative Research: Perturbation Methods for Markov-Switching ModelsProposal Number: SES - 1223198 This proposal aims to develop new tools for the computation and estimation of dynamic models in macroeconomics and for the application of those tools to relevant policy questions. Dynamic models have become a standard instrument in modern macroeconomics. Because they are built to analyze how the economy evolves over time, they are used to study growth and business cycles, to design monetary and fiscal policy, or to investigate the aggregate aspects of financial and labor markets, among many other tasks. However, many instruments are still missing in the toolbox of the applied macroeconomic researcher. For instance, economists do not have a good understanding of the effects of changes in policy regimes ?that is, variations in the way in which economic policy is systematically conducted in opposition to changes within one regime- or how the beliefs about future policies affect current behavior by households and firms.The goal of this proposal is to provide some of the required tools for these tasks and show how they can be used to address important questions in the design and evaluation of public policy. Consequently, much of this new research may have positive externalities for other economists within macro and, more generally, for researchers in other fields where dynamic models are also employed. In particular, this proposal focuses on how to use perturbation methods to solve Markov switching rational expectations (MSRE) models starting from first principles, that is, from the set of non-linearized optimality conditions that describe the behavior of the economic agents, rather than from the set of linearized ones, as the literature has previously done. Perturbation methods, commonly used in natural sciences and economics, built approximated solution to models that are analytically intractable. MSRE models allow for different possible policy regimes (for instance, a hawkish central banker and a dovish central banker) that evolve and switch over time (hawkish central bankers are followed, with some probability, by dovish central bankers and so on).The proposal derives the set of algebraic equations to be solved to find the first-order Taylor expansion to the policy functions using a perturbation. Next, it shows how the traditional approach, based on singular value decomposition (SVD) algorithms and used in the constant parameter case, does not work in the case of MSRE models. Instead, the proposal uses a Gröbner basis method. Then, it studies how to check for determinacy and, as an example, it solves a business cycle model with nominal rigidities. Finally, the proposal points out how the perturbation approach also allows us to find higher-order approximations to the solution of MSRE models. Policy-making institutions in the U.S. and abroad can apply the methods presented in this proposal. For instance, the Federal Reserve Board and several regional Federal Reserve Banks, the International Monetary Fund, the European Central Bank, the Bank of England, and the central banks of Austria, Canada, Germany, Italy, Japan, Spain, and Sweden (just to name a few) are actively formulating and estimating dynamic macroeconomic models for policy analysis and forecasting that can benefit from the type of extensions presented in the proposal. Moreover, the economics profession is accumulating evidence of the good forecasting performance of this class of models, even when compared with judgmental predictions from staff economists. The newer and better tools that this proposal outlines are designed explicitly for the purpose of helping the Federal Reserve Board and other policy-making institutions to develop more flexible models that will contribute to the implementation of an effective public policy in the U.S. Finally, the development of new computation techniques has potential applications in other fields of economics (such as international economics, industrial organization, or labor economics), and other social sciences where researchers want to solve and estimate dynamic models using flexible, yet powerful tools.

摘要提案标题：合作研究：该提案旨在开发新的工具，用于计算和估计宏观经济学中的动态模型，并将这些工具应用于相关的政策问题。动态模型已成为现代宏观经济学的标准工具。因为它们是用来分析经济如何随着时间的推移而演变的，所以它们被用来研究增长和商业周期，设计货币和财政政策，或者调查金融和劳动力市场的总体方面，以及许多其他任务。然而，应用宏观经济研究人员的工具箱中仍然缺少许多工具。例如，经济学家对政策制度变化的影响没有很好的理解。也就是说，经济政策的系统性实施方式的变化与一个政权内部的变化相对立，或者对未来政策的信念如何影响家庭和企业的当前行为。本提案的目标是为这些任务提供一些必要的工具，并展示如何使用这些工具来解决公共政策设计和评估中的重要问题。因此，这些新研究的大部分可能对宏观经济学中的其他经济学家，以及更普遍地对其他领域的研究人员具有正外部性，这些领域也采用动态模型。特别是，这个建议的重点是如何使用扰动方法来解决马尔可夫切换理性预期（MSRE）模型从第一原则，也就是说，从一组非线性的最优性条件，描述的行为的经济代理，而不是从一组线性的，如文献先前所做的。摄动法是自然科学和经济学中常用的一种方法，它可以为一些难以解析求解的模型建立近似解。MSRE模型允许不同的可能的政策制度（例如，鹰派央行行长和鸽派央行行长），随着时间的推移而演变和切换（鹰派央行行长之后，有一定的概率，鸽派央行行长等）。接下来，它展示了如何传统的方法，基于奇异值分解（SVD）算法和用于常数参数的情况下，不工作的MSRE模型的情况下。相反，该提案使用Gröbner基方法。然后，研究了确定性检验方法，并以一个具有名义刚性的经济周期模型为例进行了求解。最后，该提案指出如何摄动方法也使我们能够找到高阶近似的MSRE模型的解决方案。美国和国外的决策机构可以应用本提案中提出的方法。例如，联邦储备委员会和几个区域性联邦储备银行、国际货币基金组织、欧洲中央银行、英格兰银行以及奥地利、加拿大、德国、意大利、日本、西班牙、和瑞典（仅举几例）正在积极制定和估计动态宏观经济模型，用于政策分析和预测，这些模型可以受益于提议此外，经济学专业正在积累证据，证明这类模型具有良好的预测性能，即使与经济学家的判断性预测相比也是如此。本提案所概述的更新、更好的工具，其目的是明确地帮助联邦储备委员会和其他决策机构开发更灵活的模型，以有助于在美国实施有效的公共政策。 最后，新计算技术的发展在其他经济学领域（如国际经济学、产业组织或劳动经济学）和其他社会科学中具有潜在的应用，研究人员希望使用灵活而强大的工具来解决和估计动态模型。