Collaborative Research: Debt and Insecurity Among Vulnerable Communities During the COVID-19 Crisis

在本项目中，研究了两个问题：第一，在2019冠状病毒病大流行之前和期间，低收入社区的财政困难是如何分配的；第二，社会福利决策在多大程度上减轻或加剧了债务负担，以及哪些决策在保护低收入家庭免受严重财政困难方面最成功（或最不成功）。当面临经济不安全时，许多美国人会负债。虽然获得信贷可以在危机时期为家庭提供资源，但对于低收入家庭来说，偿还债务往往是沉重的负担，而且可能加剧而不是缓解经济紧张和不安全。随着新冠肺炎危机的爆发，许多美国人面临着突如其来的新的经济不安全感，官方对疫情的反应也各不相同。这项研究有助于理解危机来袭时低收入社区的债务和官方反应的综合影响。该项目的一个重要目标是向决策者通报2019冠状病毒病危机期间低收入债务和经济不安全状况，以提高未来干预措施的有效性。通过消费者信贷、替代金融服务和国家数据集的联系来解决研究问题。通过邮政编码级别的消费信贷（如抵押贷款和信用卡）季度数据，可以捕捉到低收入社区的债务水平。替代金融服务用途-例如：从2019年第一季度到2020年第四季度，获得了发薪日和产权贷款。这些数据与州和邮政级数据相关联，其中包括社会人口特征、与covid相关的限制以及州一级的社会安全网程序。首先，分析涉及对2019冠状病毒病大流行爆发前后美国脆弱社区债务模式的描述。其次，使用各种统计模型来调查这些社区的债务问题与官方对流行病的反应之间的关系。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

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.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.