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Principal Investigator: Lawrence M Berger
Organization: UNIVERSITY OF WISCONSIN-MADISON
Fiscal Year: 2024
Award: $660,124
Funding agency: Eunice Kennedy Shriver National Institute of Child Health and Human Development
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.
Terms: <0-11 years old><21+ years old><Adult><Adult Human><Behavior><COVID crisis><COVID epidemic><COVID pandemic><COVID-19 affected><COVID-19 consequence><COVID-19 crisis><COVID-19 effect><COVID-19 epidemic><COVID-19 era><COVID-19 global health crisis><COVID-19 global pandemic><COVID-19 health crisis><COVID-19 impact><COVID-19 impacted><COVID-19 pandemic><COVID-19 period><COVID-19 public health crisis><COVID-19 years><Characteristics><Child><Child Support><Child Youth><Children (0-21)><Cognitive><Data><Data Analyses><Data Analysis><Data Collection><Data Reporting><Demographic Analyses><Demographic Analysis><Development><Disadvantaged><Disparity population><Economic Income><Economical Income><Economics><Education><Educational Mainstreaming><Educational aspects><Employment><Equipment and supply inventories><Family><Family Demographies><Financial Hardship><Friends><Goals><Health><Heterogeneity><Household><Impoverished><Income><Individual><Inequality><Intervention><Intervention Strategies><Interview><Inventory><Knowledge><Legal><Link><Low Income Population><Low income><Low income group><Mainstreaming><Measures><Middle Class Populations><Modeling><Patient Self-Report><Performance><Personal Satisfaction><Pilot Projects><Play><Policies><Population Analysis><Poverty><Qualitative Research><Questionnaires><Race><Races><Randomized><Reporting><Research Design><Respondent><Role><SARS-CoV-2 epidemic><SARS-CoV-2 global health crisis><SARS-CoV-2 global pandemic><SARS-CoV-2 pandemic><SARS-coronavirus-2 epidemic><SARS-coronavirus-2 pandemic><Sampling><Security><Self-Report><Severe Acute Respiratory Syndrome CoV 2 epidemic><Severe Acute Respiratory Syndrome CoV 2 pandemic><Severe acute respiratory syndrome coronavirus 2 epidemic><Severe acute respiratory syndrome coronavirus 2 pandemic><Social Service><Social Welfare><Social Work><Source><Student Loan><Study Type><Survey Instrument><Surveys><United States><Wisconsin><Work><achievement Mainstream Education><adulthood><cognitive interview><coronavirus disease 2019 consequence><coronavirus disease 2019 crisis><coronavirus disease 2019 effect><coronavirus disease 2019 epidemic><coronavirus disease 2019 global health crisis><coronavirus disease 2019 global pandemic><coronavirus disease 2019 health crisis><coronavirus disease 2019 impact><coronavirus disease 2019 pandemic><coronavirus disease 2019 public health crisis><coronavirus disease crisis><coronavirus disease epidemic><coronavirus disease pandemic><coronavirus disease-19 global pandemic><coronavirus disease-19 impact><coronavirus disease-19 pandemic><cost><data infrastructure><data interpretation><data quality><data representation><data representations><developmental><disadvantaged group><disadvantaged individual><disadvantaged people><disadvantaged population><disadvantaged subgroup><disparities across groups><disparities in race><disparity across subgroups><disparity among groups><disparity among subgroups><disparity between groups><disparity between subgroups><disparity due to race><economic><economic analysis><economic assessment><economic evaluation><economic impact><experience><experiment><experimental research><experimental study><experiments><financial adversity><financial burden><financial distress><financial insecurity><financial literacy><financial strain><financial stress><group disparity><group inequality><group inequity><health assessment><improved><incomes><inequalities among populations><inequalities between populations><inequalities in populations><inequality across populations><inequality among groups><inequality between groups><inequality due to race><inequality in groups><inequities among populations><inequities between populations><inequities in populations><inequity across groups><inequity across populations><inequity between groups><inequity due to race><inequity in groups><instrument><interventional strategy><kids><low income individual><low income people><lower income families><middle class group><middle class individual><middle class people><pilot study><population health><population inequality><population inequity><programs><race based disparity><race based inequality><race based inequity><race disparity><race related disparity><race related inequality><race related inequity><racial><racial background><racial disparity><racial inequality><racial inequity><racial origin><racially unequal><randomisation><randomization><randomly assigned><severe acute respiratory syndrome coronavirus 2 global health crisis><severe acute respiratory syndrome coronavirus 2 global pandemic><social><social role><socio-demographics><sociodemographics><study design><subgroup disparity><unequal group><unequal population><well-being><wellbeing><youngster>