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

在这个项目中，调查了两个问题：第一，在新冠肺炎大流行之前和期间，经济困难在低收入社区中是如何分配的；第二，社会福利决定在多大程度上减轻或加剧了债务负担，以及在保护低收入家庭免受严重经济困难方面，哪些决定最成功(或最不成功)。当面临经济不安全时，许多美国人背负着债务。虽然获得信贷可以在危机时期为家庭提供资源，但债务往往是低收入家庭偿还债务的沉重负担，而且可能加剧而不是缓解经济压力和不安全。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因素，官方对这场流行病的反应也是多种多样的。这项研究有助于理解低收入社区在危机来袭时债务和官方应对措施的综合影响。该项目的一个重要目标是向决策者通报新冠肺炎危机期间的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。研究问题通过消费者信贷、另类金融服务和国家数据集之间的联系来解决。低收入社区的负债水平是通过消费信贷的邮政编码级别的季度数据来反映的，例如抵押贷款和信用卡。替代金融服务用途-例如发薪日和所有权贷款-从2019年第一季度到2020年第四季度获得。这些数据与州和邮政编码级别的数据相关联，这些数据包括社会人口特征、与COVID相关的限制和州级别的社会安全网程序。首先，分析涉及对美国易受伤害社区在新冠肺炎大流行爆发前后的债务模式的描述。其次，各种统计模型被用来调查债务问题与官方在这些社区对疫情的反应之间的联系。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.