A Granular Framework for Assessing the Incidence of Local Economic Shocks

评估当地经济冲击发生率的细粒度框架

• 批准号: 2018609
• 负责人: Felix Tintelnot
• 金额: $ 42.3万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018609&HistoricalAwards=false
• 关键词: Granular; Framework; Assessing; Incidence; Local

AbstractUrban economy models are challenged by a growing body of increasingly fine spatial data. This project develops a framework for the analysis of urban policies that accounts for geographically fine data. The project assembles data of new plant and office openings and combines them with commuting and land price information to analyze the predictions of quantitative spatial models. The project will provide new directions for the development of urban economy models. These models are useful for policy makers in their forecasts and evaluation of the effects of changes to the economic environment.Conventional quantitative spatial models assume a continuum of agents. Therefore, conventional estimation procedures may over-fit granular outcomes due to sampling noise. This project develops a granular spatial-equilibrium model that features the optimizing decisions of a finite number of individuals, as well as land and labor market clearing, leading to endogenous prices for land and labor. The project empirically implements the model and illustrates advances over prior econometric approaches. Furthermore, by collecting and utilizing data on plant and office openings and commuting and land price responses, the project evaluates predictions of spatial economic models. These models have become increasingly popular in economic analysis and evaluating their predictions will increase the confidence in their predictions and lead to future research on these frameworks.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.

摘要城市经济模型受到越来越多的精细空间数据的挑战。该项目开发了一个分析城市政策的框架，该框架考虑到地理上的精细数据。该项目收集新工厂和办公室开业的数据，并将其与通勤和土地价格信息相结合，以分析定量空间模型的预测。该项目将为城市经济模式的发展提供新的方向。这些模型对于政策制定者预测和评估经济环境变化的影响是有用的。传统的定量空间模型假设了一个连续体的代理人。因此，传统的估计过程可能由于采样噪声而过拟合粒度结果。该项目开发了一个粒度空间均衡模型，该模型的特点是有限数量的个人的优化决策，以及土地和劳动力市场的出清，导致土地和劳动力的内生价格。该项目实证实施的模型，并说明了先进的计量经济学方法。此外，通过收集和利用有关工厂和办公室开放以及通勤和土地价格反应的数据，该项目评估了空间经济模型的预测。这些模型在经济分析中越来越受欢迎，评估它们的预测将增加预测的信心，并导致未来对这些框架的研究。该奖项反映了NSF的法定使命，并被认为值得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来支持。