Improving Data Collection of Debt and Financial Strain to Assess Health Impacts of Economic Insecurity

改进债务和金融紧张的数据收集，以评估经济不安全对健康的影响

• 批准号: 10416007
• 负责人: Lawrence M Berger
• 金额: $ 67.09万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10416007
• 关键词: Adult; Behavior; Benchmarking; COVID-19 impact; COVID-19 pandemic; Characteristics; Child; Child Support; Cognitive; Data; Data Analyses; Data Collection; Data Reporting; Demographic Analyses; Development; Disadvantaged; Economics; Education; Employment; Equipment and supply inventories; Family; Financial Hardship; Friends; Goals; Gold; Health; Heterogeneity; Household; Income; Individual; Inequality; Intervention; Interview; Knowledge; Legal; Link; Low Income Population; Low income; Mainstreaming; Measures; Middle Class Populations; Modeling; Patient Self-Report; Performance; Personal Satisfaction; Persons; Pilot Projects; Play; Policies; Population Analysis; Poverty; Qualitative Research; Questionnaires; Race; Randomized; Reporting; Research Design; Respondent; Role; Sampling; Security; Social Welfare; Social Work; Source; Student Loan; Surveys; United States; Wisconsin; Work; cognitive interview; cost; data infrastructure; data quality; demographics; economic evaluation; economic impact; experience; experimental study; financial literacy; improved; instrument; lower income families; population health; programs; racial disparity; social; sociodemographics

Project Summary/Abstract Individual and household debt plays an increasingly important role in the dynamics of inequality in the United States. However, current data limitations impede scientific understanding of the role of indebtedness in reducing or exacerbating economic insecurity. At best, existing social surveys collect data on a subset of mainstream debts most often encountered by middle-class populations (mortgages, credit cards, auto loans, student loans), while debts common to low-income populations (payday loans, legal debts, past due bills, child support arrears, loans from employers, family, and friends) are less well represented. Without better data, scientific analyses of population health and wellbeing may understate and misidentify crucial sources of economic insecurity and disadvantage, as well as reciprocal effects of debt with poverty, health, and family functioning. This project consists of a multi-pronged data collection and analysis effort to build a stronger data infrastructure, more adequate and accurate measures of indebtedness, and best practices for analyzing various forms of indebtedness and their relation to economic hardship and financial strain for low-income families. The project has three Specific Aims: (1) To conduct qualitative cognitive and developmental interviews with low-income families on their experiences with debt and use these results to develop an enhanced survey instrument that comprehensively and accurately captures low-income debt holding; (2) To field a two-wave pilot study designed to allow comparison of data quality and accuracy when collected via the enhanced instrument versus current ‘gold standard’ instruments (instruments will be randomly assigned); and (3) To analyze linked pilot survey, high-quality administrative (employment, earnings, and benefit receipt), and individual credit report data to (a) document consistency of self- reported debt data collected via each instrument with credit report data; (b) examine whether consistency and differences by data collection instrument differ by respondent financial literacy and sociodemographic characteristics (education, race); (c) estimate associations of types and amounts of debt using the enhanced module, existing modules, and credit report data with economic hardship and financial strain; and (d) investigate the causal order of associations of (the three measures of) debt with economic hardship and financial strain. The study will be the first to provide detailed data on the full range of types and amounts of indebtedness among low-income populations and their associations with hardship and financial strain. By improving data collection and analysis, the study had the potential to identify policy levers that could reduce potential negative effects of debt on disadvantaged families and better target interventions to lessen economic insecurity and improve well-being.

项目总结/摘要 个人和家庭债务在全球不平等的动态中发挥着越来越重要的作用。 美国的然而，目前的数据局限性阻碍了科学理解的作用， 债务减少或加剧经济不安全。现有的社会调查充其量只能收集 中产阶级人群最常遇到的主流债务子集的数据 （抵押贷款、信用卡、汽车贷款、学生贷款），而低收入人群常见的债务 （发薪日贷款、法律的债务、过期账单、子女抚养费欠款、雇主、家庭的贷款，以及 朋友们，代表性不太好。如果没有更好的数据，对人口健康和 幸福可能低估和错误识别经济不安全和不利的关键来源， 以及债务与贫困、健康和家庭功能的相互影响。该项目由 多管齐下的数据收集和分析工作，以建立更强大的数据基础设施， 适当和准确的债务措施，以及分析各种形式的债务的最佳做法， 债务及其与低收入家庭经济困难和财政紧张关系。的 项目有三个具体目标：（1）进行定性认知和发展访谈 与低收入家庭的债务经验，并利用这些结果来制定一个 增强调查工具，全面准确地掌握低收入债务持有情况; (2)开展两波试点研究，以便在以下情况下比较数据质量和准确性： 通过增强型仪器与当前的“黄金标准”仪器（仪器将 随机分配）;（3）分析联系试点调查，高质量的行政（就业， 收入和福利收据）和个人信用报告数据，以（a）记录自我的一致性， 通过具有信用报告数据的每个工具收集的报告债务数据;（B）检查是否 数据收集工具的一致性和差异因受访者的金融知识而异， 社会人口特征（教育、种族）;（c）估计类型和数量的关联 债务使用增强模块，现有模块和信用报告数据与经济困难 和财政紧张;以及（d）调查（三项措施）之间关联的因果顺序 债务与经济困难和财政紧张。该研究将首次提供详细数据， 低收入人口负债的种类和数额及其 与困难和财政紧张的联系。通过改进数据收集和分析， 有可能确定政策杠杆，减少债务对发展中国家的潜在负面影响， 贫困家庭和更有针对性的干预措施，以减轻经济不安全， well-being.