Collaborative Research: Debt and Insecurity Among Vulnerable Communities During the COVID-19 Crisis
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2048408
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Key facts
Disease
COVID-19Start & end year
20212024Known Financial Commitments (USD)
$66,064Funder
National Science Foundation (NSF)Principal Investigator
Unspecified Jason HouleResearch Location
United States of AmericaLead Research Institution
Trustees Of Dartmouth CollegeResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Social impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
In this project, two questions are investigated: first, how financial difficulties were distributed within low-income communities before and during the COVID-19 pandemic and, second, the extent to which social welfare decisions mitigated or exacerbated debt burdens and which of these decisions were most (or least) successful in protecting low-income families from serious financial difficulties. When faced with economic insecurity, many Americans take on debt. Although access to credit can provide families a resource in times of crisis, debt is often burdensome to repay for low-income families, and can exacerbate, rather than relieve, economic strain and insecurity. With the onset of the COVID-19 crisis, many Americans faced sudden and new sources of economic insecurity, and official responses to the pandemic were diverse. This study contributes to understanding the combined effects of debt and official responses in low-income communities when a crisis strikes. One important goal of this project is to inform decision-makers about low-income debt and economic insecurity during the COVID-19 crisis in order to increase the effectiveness of future interventions. The research questions are addressed through linkages of consumer credit, alternative financial services, and state data sets. Levels of indebtedness in low-income communities are captured with zip-code level quarterly data on consumer credit, such as mortgages and credit cards. Alternative financial service use-e.g., payday and title loans-is obtained from Q1 2019 through Q4 2020. These data are linked to state and zip-level data that include sociodemographic characteristics, COVID-related constraints, and state-level social safety net procedures. Analysis involves, first, description of debt patterns in vulnerable communities in the United States before and after the onset of the COVID-19 pandemic. Second, a variety of statistical models are used to investigate associations between debt problems and official responses to the pandemic in these communities.