Macroeconomics of Labor Market Sorting

劳动力市场分类的宏观经济学

• 批准号: 1357903
• 负责人: Iourii Manovskii
• 金额: $ 30.78万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-15 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1357903&HistoricalAwards=false
• 关键词: Macroeconomics; Labor; Market; Sorting

Suppose one day all workers in the U.S. were randomly reallocated across all existing jobs. Would there be any effect on output? It seems likely that the answer is ``yes''. This suggests that aggregate output and productivity depend on the actual allocation of individual workers to particular jobs. This project extends the state-of-the-art theory of sorting of workers across jobs to include the ability of workers to search for better jobs while employed. It then shows that, using only routinely available matched employer-employee data on wages and labor market transition rates, it is possible to recover the output of any observed employer-employee match and the consequences for output, productivity, and wages of moving any worker to any firm in the economy. The proposed model and measurement method will be used to provide substantive empirical answers to a number of classic but yet unanswered economic questions. The intellectual merit of the project lies in the following. (1) The PI develops an assortative matching model with on-the-job search and proves its nonparametric identification. (2) The PI draws on the recent advances in computer science to develop algorithms to implement the proposed identification strategy in practice given the potential limitations of existent data sets. (3) The PI will provide the theoretical methodology for answering important empirical questions in the context of an equilibrium model. (4) The PI will provide substantive answers to these questions. The project will have a broad impact. (1) It will provide a new model and empirical methodology for studying sorting in the labor market. (2) It will develop and and make publicly available the computational tools that enable this study. (3) New empirical findings obtained using these tools will provide a better understanding of fundamental economic issues and have a potential to substantially impact the design and evaluation of existing public policies. Fundamentally, the PI shows how the US government, using the data it already has access to, can to overcome frictions in the labor market and improve allocation of workers to jobs. This may eventually result in a substantial improvement in economic competitiveness of the United States. The results will also inform optimal design of policies, such as unemployment insurance. (4) It will provide training to graduate and postgraduate students in the development and applications of these tools and methods. (5) The results of this research will be presented at prominent national and international academic and policy conferences and seminars. They are also likely to become a standard entry on the reading lists in advanced courses.

假设有一天，美国的所有工人都被随机重新分配到所有现有的工作岗位上。对输出有影响吗？答案似乎是“是”。这表明总产出和生产率取决于个体工人对特定工作的实际分配。该项目扩展了跨工作分类工人的最先进理论，包括工人在就业期间寻找更好工作的能力。然后，它表明，仅使用常规可用的有关工资和劳动力市场转换率的雇主-雇员匹配数据，就可以恢复任何观察到的雇主-雇员匹配的产出以及将任何工人转移到经济中任何公司对产出、生产率和工资的影响。所提出的模型和测量方法将用于为一些经典但尚未解答的经济问题提供实质性的实证答案。该项目的智力优势如下。 (1) PI开发了一种在职搜索的选型匹配模型，并证明了其非参数识别性。 (2)考虑到现有数据集的潜在局限性，PI利用计算机科学的最新进展来开发算法，以在实践中实施所提出的识别策略。 (3) PI 将提供在均衡模型背景下回答重要实证问题的理论方法。 (4) PI将对这些问题提供实质性答复。该项目将产生广泛的影响。 （1）为研究劳动力市场排序提供新的模型和实证方法。 (2) 它将开发并向公众提供支持本研究的计算工具。 (3) 使用这些工具获得的新实证结果将有助于更好地理解基本经济问题，并有可能对现有公共政策的设计和评估产生重大影响。从根本上说，PI显示了美国政府如何利用其已经获得的数据来克服劳动力市场的摩擦并改善工人的工作分配。这最终可能导致美国经济竞争力的大幅提升。研究结果还将为失业保险等政策的优化设计提供信息。 (4) 将为研究生和研究生提供这些工具和方法的开发和应用的培训。 (5) 本研究的结果将在重要的国内和国际学术和政策会议和研讨会上发表。它们也有可能成为高级课程阅读清单上的标准条目。