HNDS-R - Collaborative Research: An Integrated Analysis of the COVID-19 Crisis on Labor Market Outcomes and Mortality
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2242472
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Key facts
Disease
COVID-19Start & end year
20232026Known Financial Commitments (USD)
$32,413Funder
National Science Foundation (NSF)Principal Investigator
Hannes SchwandtResearch Location
United States of AmericaLead Research Institution
Northwestern UniversityResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Economic impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Adults (18 and older)
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
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.