HNDS-R - Collaborative Research: An Integrated Analysis of the COVID-19 Crisis on Labor Market Outcomes and Mortality

HNDS-R - 协作研究：COVID-19 危机对劳动力市场结果和死亡率的综合分析

• 批准号: 2242581
• 负责人: Till von Wachter
• 金额: $ 77.95万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2242581&HistoricalAwards=false
• 关键词: HNDS; Collaborative; Research; Integrated; Analysis

This research tests an important labor market theory by evaluating the economic and health impacts of unemployment insurance (UI) programs on workers across communities before, during, and after the COVID-19 pandemic. The study will assemble a large, detailed, and innovative data set over 20 years from several sources for the empirical part of the project. The first part of the study focuses on take-up rate of UI by various groups, the second part studies the impact of the generosity of UI on labor supply, job stability, and several labor market outcomes before, during and after the pandemic, while the third part studies the effects of UI expansion on CODI-19 mortality rates among different groups. The results of this research will substantially increase our understanding of the effects of the UI program on individual, neighborhood, and state-level actors, and help policymakers better respond to future recessions and pandemics. The results of this research project will make significant contributions to labor economics as well as contribute to better design of unemployment insurance policies, hence help to establish the US as a global leader in UI policies. This research project combines several data sets and merges it with individual-level data for all covered employees in California, over 20 years, that covers periods before, during, and after the COVID-19 pandemic. This data infrastructure will then be used to investigate three fundamental questions about unemployment insurance (UI) program: how does worker, firm, neighborhood characteristics, and worker interaction affect the take-up rate of UI programs by different groups; what is the causal impact of UI on the cost and benefits on several outcomes, especially on labor supply, employment stability, job mobility and earnings; and finally the effects of UI on COVID-19 mortality. By answering these fundamental questions about UI programs, this research project makes significant contributions to labor economics and provides guidance on how to improve unemployment insurance policies to make them more effective. The results could also help improve labor market policies as well as help establish the US a global leader in unemployment insurance innovation. The results of this study will also substantially advance the literature in the fields of economics and statistics, through improved measurement and implementation of new research designs.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.

这项研究通过评估失业保险 (UI) 计划在 COVID-19 大流行之前、期间和之后对各社区工人的经济和健康影响，测试了重要的劳动力市场理论。该研究将从多个来源收集 20 多年来的大量、详细且创新的数据集，用于该项目的实证部分。该研究的第一部分侧重于不同群体的失业保险接受率，第二部分研究慷慨的失业保险对劳动力供应、工作稳定性以及大流行之前、期间和之后的一些劳动力市场结果的影响，而第三部分研究UI扩大对不同群体中CODI-19死亡率的影响。 这项研究的结果将大大增加我们对失业保险计划对个人、社区和州一级行为者影响的理解，并帮助政策制定者更好地应对未来的经济衰退和流行病。 该研究项目的成果将对劳动经济学做出重大贡献，并有助于更好地设计失业保险政策，从而有助于确立美国在失业保险政策方面的全球领先地位。 该研究项目结合了多个数据集，并将其与加州所有受覆盖员工 20 多年来的个人数据合并，涵盖了 COVID-19 大流行之前、期间和之后的时期。 然后，该数据基础设施将用于调查有关失业保险（UI）计划的三个基本问题：工人、公司、社区特征和工人互动如何影响不同群体对失业保险计划的参与率；失业保险对多种结果的成本和收益的因果影响是什么，特别是对劳动力供应、就业稳定性、工作流动性和收入的影响；最后是 UI 对 COVID-19 死亡率的影响。 通过回答有关失业保险计划的这些基本问题，该研究项目对劳动经济学做出了重大贡献，并为如何改进失业保险政策以使其更加有效提供了指导。 研究结果还可能有助于改善劳动力市场政策，并帮助美国成为失业保险创新的全球领导者。这项研究的结果还将通过改进测量和实施新的研究设计，极大地推进经济学和统计学领域的文献发展。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和技术进行评估，被认为值得支持。更广泛的影响审查标准。