Abstract: How Deep in Debt? How Levels of Unsecured Debt Affect Hardship Among Low- and Middle-Income Households (Society for Social Work and Research 22nd Annual Conference - Achieving Equal Opportunity, Equity, and Justice)

How Deep in Debt? How Levels of Unsecured Debt Affect Hardship Among Low- and Middle-Income Households

Schedule:
Friday, January 12, 2018: 4:00 PM
Marquis BR Salon 8 (ML 2) (Marriott Marquis Washington DC)
* noted as presenting author
Sam Bufe, MS, Statistical Data Analyst, Washington University in Saint Louis, St. Louis, MO
Mathieu Despard, PhD, Assistant Professor, University of Michigan-Ann Arbor, Ann Arbor, MI
Stephen Roll, PhD, Research Assistant Professor, Washington University in Saint Louis, St Louis, MO
Michal Grinstein-Weiss, PhD, Professor, Director, Envolve Center for Health Behavior Change, Associate Director, Center for Social Development, Washington University in Saint Louis, St. Louis, MO
Purpose. In the run-up to the Great Recession, credit usage was expanding rapidly in the United States. Several years out from the financial crisis, unsecured debt levels have now reached and may soon surpass its former high. While credit can help smooth consumption or finance large purchases, unsecured debt burden may increase risk for hardship among low- and moderate-income (LMI) households who have lower levels of liquid assets (Collins & Gjertson, 2013), pay higher rates on credit cards (Weller, 2007), and are more likely to rely on high-cost payday loans (The Pew Charitable Trusts, 2012). As levels of unsecured debt continue to rise, it is important to understand at what levels unsecured debt increases LMI households' risk for hardship. 

Methods. This paper uses data from the 2016 Household Financial Surveys (HFS), which ask 10,830 LMI households questions about their financial situations when they file their taxes and six months later.  In addition to questions about assets and liabilities, these surveys include questions about material (difficulty affording basic needs) and health care (difficulty affording medical and dental care, and prescription drugs) hardships.  Using data from the baseline HFS, we grouped respondents into quintiles based on their levels of unsecured debt, which included credit card, payday and auto tile loans, and negative balances. We used Coarsened Exact Matching to adjust for demographic, financial, and geographic differences among households across debt quintiles. Linear probability modeling was used to assess the association between unsecured debt quintiles at baseline and material and health care hardship six months later.

Results. Preliminary results show that higher levels of unsecured debt significantly increase the probability of experiencing material hardship as well as the number of hardships experienced in the six months after filing taxes. Interestingly, preliminary findings suggest a more nuanced story for the relationship between unsecured debt and medical hardship: When unsecured debt is low, increases in unsecured debt are associated with increases in the probability of experiencing medical hardship. However, once unsecured debt reaches a relatively low threshold (approximately $1,000), increases in unsecured debt do not appear to marginally increase the probability of experiencing medical hardship. These results hold and are largely unchanged when controlling for other financial characteristics like the level of liquid assets held by a household.

Implications. Our findings suggest that policymakers consider strategies to help LMI households lessen their unsecured debt in addition to policies aimed at building assets. Strategies might include expanding access to safer and more affordable small dollar installment loans (Pew Charitable Trusts, 2016) and integrating credit counseling with access to safe and affordable financial products (Federation of Community Development Credit Unions, 2015). Our findings concerning medical hardship suggests that debt levels may affect LMI households' decisions to seek health care differently than the ability to meet other needs such as housing and warrant further investigation to help inform health coverage policies.