Growth, Business Cycles, and Policy in U.S. States

美国各州的增长、商业周期和政策

• 批准号: 1559385
• 负责人: Noah Williams
• 金额: $ 17.8万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-15 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1559385&HistoricalAwards=false
• 关键词: Growth; Business; Cycles; Policy; U.S.

The project examines the economic performance of individual states in the US over time, taking into account business cycle fluctuations. The goal is to answer research questions about how state-level policies affect state-level economic outcomes. The PI plans to create a data set that includes economic aggregate measures for each US state on a quarterly basis. To do this, he will have to combine existing data sets and will have to use statistical methods to impute quarterly values for several key variables that are only reported annually. The quarterly-level data will be available to other researchers. Once he has constructed this data set, he will use statistical analysis to determine the difference between long-run economic trends and the shorter term effects of business cycle fluctuations. This will allow him to compare across states to see how each state performs on growth, the effects of business cycles, and the impact of economic shocks. Finally, he will develop a model of the economic relationship between states in the US using methods that have been used to model trade between countries in the European Union. He will use the data to estimate parameters of his model, and will then use the model to simulate the effects of different kinds of state-level tax policies. The PI will use a variety of methods (including articles written for a general audience) to make the results of this project accessible to voters and legislators. The results of this project will be important in two different ways. First of all, it will provide new evidence for science-based economic policies at the state level. Second, it will help US policymakers understand which state-level experiments in tax policies are worth considering at the federal level. The first goal of the project is to compile and estimate a data set of quarterly state-level economic aggregates. While some of the macroeconomic variables are available on public databases, several key variables are only available at annual frequencies. But for many questions, data at the quarterly frequency (or higher) are needed. The PI will use annual data on the variables of interest, along with other quarterly economic indicators, to estimate quarterly time series for all key state-level macroeconomic indicators.After constructing the data set, he will begin with a less structured analysis of data, using panel VARs to decompose the state-level variables into long-run growth trends and business cycles. The spatial aspects of the data will allow him to analyze state, regional, and aggregate factors, and to trace how shocks hitting one state or region may diffuse to others. In addition, the states have different dynamics and will respond differently to aggregate shocks. Moreover, the trends, dependencies, and dynamics may have changed over time. Estimating and analyzing time-varying panel VARs will provide useful comparisons across states on the commonalities and differences in growth, business cycles, and the impacts of shocks. While the empirical analysis can describe the dynamics of state economies, to study the impact of state-level economic policy, the PI will develop and estimate structural models of the state-level economies. In particular, he will build on small open economy DSGE models of the Euro area, adapting and applying them to study U.S. states. This will allow him to study the impact of state-level tax policy, including the differential effects of different types of state taxes, and strategies for fiscal consolidation.

该项目考察了美国各州在一段时间内的经济表现，并考虑到商业周期的波动。其目标是回答有关州一级政策如何影响州一级经济成果的研究问题。PI计划创建一个数据集，其中包括美国各州每季度的经济总量指标。为此，他将不得不将联合收割机现有的数据集结合起来，并将不得不使用统计方法为每年报告的几个关键变量估算季度值。季度数据将提供给其他研究人员。一旦他建立了这个数据集，他将使用统计分析来确定长期经济趋势和商业周期波动的短期影响之间的差异。这将使他能够比较各州，看看每个州在经济增长、商业周期的影响以及经济冲击的影响方面的表现。最后，他将使用欧盟国家之间贸易模型的方法，开发美国各州之间经济关系的模型。他将使用这些数据来估计他的模型的参数，然后使用该模型来模拟不同类型的州一级税收政策的影响。PI将使用各种方法（包括为普通读者撰写的文章），使选民和立法者能够了解该项目的结果。该项目的结果将在两个不同方面具有重要意义。首先，它将为国家一级以科学为基础的经济政策提供新的证据。其次，它将帮助美国决策者了解哪些州一级的税收政策实验值得联邦层面考虑。该项目的第一个目标是编制和估算国家级季度经济总量数据集。虽然一些宏观经济变量可以在公共数据库中获得，但一些关键变量仅以年度频率提供。但对于许多问题，需要季度频率（或更高）的数据。PI将使用有关变量的年度数据，沿着其他季度经济指标，估算所有关键州级宏观经济指标的季度时间序列。构建数据集后，他将开始对数据进行结构性较低的分析，使用面板VAR将州级变量分解为长期增长趋势和商业周期。数据的空间方面将使他能够分析国家，区域和总体因素，并跟踪冲击一个国家或地区如何扩散到其他国家或地区。此外，各国有不同的动态，对总体冲击的反应也不同。此外，趋势、依赖性和动态可能随着时间的推移而改变。估计和分析随时间变化的面板VAR将提供有用的比较，在增长，商业周期和冲击的影响的共性和差异。虽然实证分析可以描述国家经济的动态，但为了研究国家一级经济政策的影响，PI将开发和估计国家一级经济的结构模型。特别是，他将建立在欧元区的小型开放经济DSGE模型，调整和应用它们来研究美国各州。这将使他能够研究州一级税收政策的影响，包括不同类型的州税的不同影响，以及财政整顿战略。