Income-Driven Repayment: Who’s Using it—And How COVID-19 Could Change the Landscape

Income-Driven Repayment: Who’s Using it—And How COVID-19 Could Change the Landscape

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Part ten in the Series

The Upshot

Although fixed-payment, mortgage-like student loan repayment plans were the norm for decades, income-driven repayment (IDR) has become an increasingly popular option for borrowers since the Great Recession. Today, over six million federal borrowers are enrolled in income-based repayment programs. These programs allow students to make loan payments based on their income, with monthly payment amounts decreasing if income decreases.1 A recent examination of nationally representative data on IDR borrowers found that:

  • Borrowers with more than $50,000 in student loan debt are more likely to participate in IDR;
  • Borrowers in households earning under $12,500 per year are less likely than borrowers with larger incomes to enroll in IDR;
  • Borrowers with “some college, no degree” or a two-year degree are more likely to participate in IDR than those with a bachelor’s degree;
  • Women and borrowers of color are more likely than men and white borrowers to participate in IDR; and
  • Enrollment in IDR is not linked with other financial behaviors like savings, homeownership, or retirement.2

Due to economic uncertainty created by COVID-19, the number of federal student loan borrowers who opt into IDR—as well as the cost of administering these programs—will likely grow substantially. As policymakers consider how to support and sustain IDR programs, this policy brief offers insight into who is benefiting from them, who is not, and how the landscape may change.

Narrative

IDR programs were intended to protect borrowers who have elevated debt and low-to-moderate earnings—and to shield borrowers from economic shocks, such as the Great Recession or more recent effects from COVID-19.3 With unemployment rates reaching 15% for those with some college or an associate degree and 8% for those with a four-year degree or higher in April 2020, the need to find safety in IDR is likely to surge.4 Since low-income borrowers would most benefit from the income-driven repayment structure, a strong argument can be made for encouraging increased participation, especially in a time of economic downturn.

Despite the fact that millions of borrowers are currently enrolled in IDR, relatively little information is available about who participates.5 This study is the first of its kind to use a nationally representative dataset to examine which student characteristics are linked to enrollment in IDR and test how IDR relates to borrowers’ other financial situations and behaviors. The study revealed three key findings:

Student Loan Balances and Income Don’t Predict IDR Enrollment

Counterintuitively, neither a borrower’s student loan debt balance nor their income level predicts enrollment in IDR. Borrowers participate at about even rates (near 27%) in IDR across most ranges of income ($12,500-$100,000 per year) and for most student loan debt balances (less than $20,000 to more than $100,000, viewed in categories). However, two key exceptions to this rule exist. The first exception is that those with a high debt load—borrowers who possess $50,000 or more in debt—have a higher chance of participation in IDR. Once someone hits that $50,000 threshold, their likelihood of entering IDR increases, regardless of their actual loan amount above that threshold.

The second exception is for borrowers in households earning less than $12,500—a measurement well below the poverty-line for a traditional two-earner household with two children ($26,200) and equivalent to slightly less than the annual wages earned in a full-time job set at the federal minimum wage.6 IDR enrollment among individuals in these households was surprisingly low: although 18% of respondents with student loan debt had household wages under $12,500, only 6% of IDR participants had wages under that amount.7 This signals that many borrowers who stand to benefit from these programs are not currently doing so and that additional outreach may be needed to this demographic of low-income borrowers.

IDR Enrollment Seems to Have Demographic Links

IDR participation varies across demographic groups, with women and borrowers of color being more likely to enroll. These findings support narratives that IDR can be an important social safety net for women, and expand the conversation to start more carefully considering how IDR may be engaged by people of color.8 Given the elevated debt loads of borrowers of color and the well-established systemic disadvantages they have long faced in the US, the rate and impacts of enrollment in IDR for borrowers of color are worth further investigation and should be considered in debates about IDR modification.9   

Critically, some models show an elevated chance of married women of color enrolling in IDR. Given that women and borrowers of color have higher overall debt loads—including non-student-loan debt—IDR programs may be extraordinary lifelines for these borrowers. Mothers of color, in particular, are likely to be breadwinners and account for a greater share of their family’s income.10

Lastly, when compared to borrowers with bachelor’s degrees, those with “some college” (meaning an associate degree or some semesters completed in a four-year program with no degree earned) appear more likely to participate in IDR. Borrowers who fall into the “some college, no degree” category have taken on debt to pursue their education, but do not receive the full labor market benefits that come with earning a degree and are therefore more likely to struggle to repay their debts. This finding again shows that not all borrowers who could most benefit from IDR programs are currently participating in them. Efforts to educate borrowers about the lifeline these programs can provide should be a high priority for Congress and the administration as they consider ways to help students navigate the fallout of the COVID-19 crisis.

IDR Enrollment Does Not Impact Other Financial Behaviors

The study also assessed whether borrowers participating in IDR showed different measures of other financial behaviors, such as possessing savings (and the amount of money saved), homeownership, the use of payday lending, and participation in retirement savings (and the amount contributed), in comparison to borrowers in traditional repayment. Enrollment in IDR was not significantly correlated with any financial outcomes, nor was the amount of student loan debt for those enrolled in IDR.11

Potentially, without IDR, high-debt borrowers would show worse financial outcomes in these areas—making it hard to isolate whether IDR is equalizing financial outcomes. This would make sense in the context of prior findings that those with higher student loan debt amounts showed lower savings, retirement, and rates of homeownership for younger adults.12 Though further study is required, these findings suggest that carrying student debt does not block borrowers from achieving the “American Dream” of homeownership and financial security, if they enroll in IDR.

How COVID-19 is Likely to Affect IDR Enrollment

COVID-19 will likely increase overall enrollment in IDR. Enrollment spikes after the Great Recession provide some insight into the magnitude we may see. Between 2009 and 2011, first-time enrollees in IDR hovered around 200,000, despite the implementation of the income-based (IBR) program, which widened access to IDR.13 In 2012, new IDR enrollments spiked to over 400,000, and in 2013 grew to over 600,000.14 These enrollment spikes likely illustrate some lagged effects associated with unemployment, as the peak unemployment rate for those with a bachelor’s degree or higher was 5% in November 2010.15 The spikes also likely captured a response to younger graduates’ (ages 21-24) unemployment and underemployment, as both peaked in July 2011 at 9% and 17.4% respectively.16 Recent tabulations of employment for those with some college or a two-year degree (15%) and a four-year degree or higher (8%) already outpace peak Great Recession employment; therefore, relying on prior trends, we would expect a considerable increase in IDR uptake in the foreseeable future. 

In addition, the likely increased enrollment from borrowers experiencing strain due to economic pressures related to COVID-19 will put further demands on IDR funding in both the short and long term. Nearly half (45%) of the volume of direct federal loans were already under IDR in 2017, consisting of 4.6 million undergraduate borrowers and 1.8 million graduate degree borrowers.17 Recent examinations show that 27% of borrowers with federal student loan debt were enrolled in IDR, while in 2010 only 10% of all borrowers with federal debt were enrolled in IDR. Due to these increases over time, the cost to subsidize the loans has doubled initial estimates.18 Continuing to monitor and understand these enrollment trends will be of particular importance to policy efforts to sustain IDR programs.

Policy Implications

In designing policy interventions, we encourage lawmakers to consider that changes to IDR may have the greatest impact on female borrowers and potentially also on borrowers of color, and to target populations who stand to benefit the most from IDR participation. Federal policymakers could consider:

  • Low-touch interventions that provide information on IDR to all who apply for unemployment, to people whose prior-year taxes fell below a selected threshold (e.g. $50,000 household income), and at food banks or non-profits (like the United Way) that help struggling individuals and families hit by unemployment and recession effects related to COVID-19.
  • A behavioral intervention that makes IDR an opt-out, rather than an opt-in, repayment structure. Currently, the default choice for borrowers is a traditional mortgage-like repayment scheme. Making IDR the “default” enrollment option would help better align participation with intended beneficiaries.
  • A tax credit incentive: To encourage participation in IDR and help struggling borrowers, a one-time refundable tax credit could be offered for enrolling in IDR for households with incomes below a certain threshold, such as $50,000. This incentive would likely have a large impact for students graduating in 2020 and 2021 and could be used by low-income borrowers, many working women and mothers, and those financially affected by the COVID-19 crisis.

At the administrative level, COVID-19 has created a clear need for modifications of projected IDR use—and therefore also for the amount of funding required to sustain the program moving forward. Increased unemployment as a result of COVID-19 and reduced long-term earnings even after employment rates recover will likely encourage IDR enrollment even if no other efforts to encourage IDR participation are made, making an increase in funding for IDR administration a necessity.19 To this end, lawmakers should be cognizant that the cost estimates developed in February 2020 by the Congressional Budget Office (CBO) for administering over and covering subsidies related to IDR are likely too low, and that more precise estimates may not be available until after the Coronavirus Aid, Relief, and Economic Security (CARES) Act forbearance period.20

Methodology

Our study used the most recent (2016) nationally representative Survey of Consumer Finances (SCF) database from the US Federal Reserve, which matches individual profiles to enrollment in an IDR program and is more detailed than most publicly available datasets.21 Due to these advantages, SCF has been used by researchers at the Urban Institute, US Federal Reserve, and in academic settings to explore questions surrounding student loan debt and to understand other financially-related trends.22 For more information on our dataset and methodology please see the following endnote.23

We used SCF data to examine whether, controlling for other debt and borrower characteristics, people are more likely to participate in IDR based on specific characteristics that prior research predicts may be linked. We used multivariate linear regression, examined in a variety of ways because it appears that the way that you test IDR enrollment influences findings. In the first set, we looked at student loan debt and income as both continuous and as categorical variables. In the second set, we looked at student loan debt as a binary “high” debt categorization—borrowers with $50,000+ loan balance— and we examined wages on a log scale. Finally, we shifted from IDR as an outcome variable to IDR as a predictor of interest in regression analyses examining financial behaviors: having savings, amount saved, amount in checking, homeownership, use of payday loans, saving for retirement, and amount of retirement savings.

Importantly, while findings generally remained consistent across our two sets of analyses, others transitioned from being a significant finding to not being significant over the two analyses. The differences in outcomes between these two approaches illustrate the overall complexity of IDR enrollment and emphasize that the approach researchers take may impact their findings. Given the sensitivity expressed in these findings and the varying results of other IDR research, simplistic answers to questions about IDR are likely misleading, and policymakers should practice caution in interpreting or applying the results of any single study. Instead, we urge lawmakers to identify trends that are consistent across studies and to make decisions based on the growing body of research.

Topics
  • Higher Education343

Endnotes

  1. US Congressional Budget Office. “Income-Driven Repayment Plans for Student Loans: Budgetary Costs and Policy Options.” Congress of the United States Congressional Budget Office, Feb. 2020, www.cbo.gov/system/files/2020-02/55968-CBO-IDRP.pdf.

  2. Collier, Daniel A., et al. Exploring the Relationship of Enrollment in Income-Driven Repayment to Borrower Demographics and Financial Outcomes. Preprint, Politics and International Relations, 6 Apr. 2020, DOI.org (Crossref), doi:10.33774/apsa-2019-nd8n2-v2.

  3. Shireman, Robert. “Learn Now, Pay Later: A History of Income-Contingent Student Loans in the United States.” The ANNALS of the American Academy of Political and Social Science, vol. 671, no. 1, May 2017, pp. 184–201. DOI.org (Crossref), doi:10.1177/0002716217701673.

  4. US Bureau of Labor Statistics. “Table A-4. Employment Status of the Civilian Population 25 Years and over by Educational Attainment.” Economic News Release, www.bls.gov/news.release/empsit.t04.htm. Accessed 26 May 2020.

  5. The Federal Reserve Board of Governors in Washington DC. “Federal Reserve Board - Survey of Consumer Finances (SCF).” Board of Governors of the Federal Reserve System, 2018, www.federalreserve.gov/econres/scfindex.htm.

  6. “HHS Poverty Guidelines for 2020.” US Department of Health & Human Services, aspe.hhs.gov/poverty-guidelines.

  7. Collier, Daniel A., et al. Exploring the Relationship of Enrollment in Income-Driven Repayment to Borrower Demographics and Financial Outcomes. Preprint, Politics and International Relations, 6 Apr. 2020, DOI.org (Crossref), doi:10.33774/apsa-2019-nd8n2-v2.

  8. Collier, Daniel A. Exploring IDR: A Comparison of Financial Situations and Behaviors Between Those in Traditional Student Loan Repayment and Those in Income-Driven Repayment. no. 2, 2020, p. 26; Miller, Kevin. Deeper in Debt: Women and Student Loans. AAUW, 2017, www.aauw.org/resources/research/deeper-in-debt/.

  9. Scott-Clayton, Judith, and Jing Li. Black-White Disparity in Student Loan Debt More than Triples after Graduation. Brookings Institution, 20 Oct. 2016, www.brookings.edu/research/black-white-disparity-in-student-loan-debt-more-than-triples-after-graduation/; Shireman, Robert. “Learn Now, Pay Later: A History of Income-Contingent Student Loans in the United States.” The ANNALS of the American Academy of Political and Social Science, vol. 671, no. 1, May 2017, pp. 184–201. DOI.org (Crossref), doi:10.1177/0002716217701673.

  10. Glynn, Sarah Jane. “Breadwinning Mothers Continue to Be the U.S. Norm.” Center for American Progress, 5 May 2019, www.americanprogress.org/issues/women/reports/2019/05/10/469739/breadwinning-mothers-continue-u-s-norm/.

  11. Collier, Daniel A., et al. Exploring the Relationship of Enrollment in Income-Driven Repayment to Borrower Demographics and Financial Outcomes. Preprint, Politics and International Relations, 6 Apr. 2020, DOI.org (Crossref), doi:10.33774/apsa-2019-nd8n2-v2.

  12. Elliott, William, et al. Student Debt and Declining Retirement Savings. “Federal Student Aid Posts New Reports to FSA Data Center.” Federal Student Aid, An Office of the U.S. Department of Education, 19 Feb. 2020, ifap.ed.gov/electronic-announcements/021920fsapostsnewreportstofsadatacenter; Grinstein-Weiss, Michal, et al. Does Unsecured Debt Decrease Savings? Evidence from the Refund to Savings Initiative. Brookings Institution, 5 Mar. 2015, www.brookings.edu/research/does-unsecured-debt-decrease-savings-evidence-from-the-refund-to-savings-initiative/; Houle, Jason N., and Lawrence Berger. “Is Student Loan Debt Discouraging Homeownership among Young Adults?” Social Service Review, vol. 89, no. 4, Dec. 2015, pp. 589–621. DOI.org (Crossref), doi:10.1086/684587.

  13. US Congressional Budget Office. “Income-Driven Repayment Plans for Student Loans: Budgetary Costs and Policy Options.” Congress of the United States Congressional Budget Office, Feb. 2020, www.cbo.gov/system/files/2020-02/55968-CBO-IDRP.pdf.

  14. Consumer Financial Protection Bureau. “Data Point: Borrower Experience on Income-Driven Repayment.” The CFPB Office of Research, Nov. 2019, files.consumerfinance.gov/f/documents/cfpb_data-point_borrower-experiences-on-IDR.pdf.

  15. Cunningham, Evan. Great Recession, Great Recovery? Trends from the Current Population Survey: Monthly Labor Review: U.S. Bureau of Labor Statistics, Apr. 2018, www.bls.gov/opub/mlr/2018/article/great-recession-great-recovery.htm.

  16. Gould, Elise, et al. Class of 2019: College Edition. Economic Policy Institute, 14 May 2019, www.epi.org/publication/class-of-2019-college-edition/.

  17. US Congressional Budget Office. “Income-Driven Repayment Plans for Student Loans: Budgetary Costs and Policy Options.” Congress of the United States Congressional Budget Office, Feb. 2020, www.cbo.gov/system/files/2020-02/55968-CBO-IDRP.pdf.

  18. US Government Accountability Office. Federal Student Loans: Education Needs to Improve Its Income-Driven Repayment Plan Budget Estimates. GAO-17-22, Nov. 2016, www.gao.gov/products/GAO-17-22.

  19. Carruthers, Celeste K., et al. “Class of 2020 Was to Enter the Strongest Job Market in 50 Years — and Now Graduates’ Earnings Will Lag Peers’ for a Decade.” MarketWatch, 2 Apr. 2020, www.marketwatch.com/story/class-of-2020-was-to-enter-the-strongest-job-market-in-50-years-and-now-graduates-earnings-will-lag-those-of-peers-for-a-decade-2020-04-01.

  20. Collier, Daniel A., et al. Congress CARES but Private Student Loan Debt Remains Blind Spot in the COVID-19 Relief Package. W.E. Upjohn Institute for Employment Research, 6 Apr. 2020, www.upjohn.org/research-highlights/congress-cares-private-student-loan-debt-remains-blind-spot-covid-19-relief-package; US Congressional Budget Office. “Income-Driven Repayment Plans for Student Loans: Budgetary Costs and Policy Options.” Congress of the United States Congressional Budget Office, Feb. 2020, www.cbo.gov/system/files/2020-02/55968-CBO-IDRP.pdf.

  21. Bricker, Jesse, Alice Henriques, et al. “Estimating Top Income and Wealth Shares: Sensitivity to Data and Methods.” American Economic Review, vol. 106, no. 5, May 2016, pp. 641–45. DOI.org (Crossref), doi:10.1257/aer.p20161020; The Federal Reserve Board of Governors in Washington DC. “Federal Reserve Board - Survey of Consumer Finances (SCF).” Board of Governors of the Federal Reserve System, 2018, www.federalreserve.gov/econres/scfindex.htm; Hillman, Nicholas, and Ellie Bruecker. “Finding and Using Student Loan Data – SHEEO.” SHEEO, 12 Jun. 2019, postsecondarydata.sheeo.org/finding-and-using-student-loan-data/.

  22. Blagg, Kristin. “Who Uses Income-Driven Student Loan Repayment?” Urban Institute, 20 Feb. 2018, www.urban.org/urban-wire/who-uses-income-driven-student-loan-repayment; Bricker, Jesse, Alice Volz, et al. “Education Debt Owed by Older Families in the 2016 Survey of Consumer Finances Accessible Data.” Board of Governors of the Federal Reserve System, www.federalreserve.gov/econres/notes/feds-notes/education-debt-owed-by-older-families-in-the-2016-survey-of-consumer-finances-accessible-20181221.htm; Frost, Riordan. Piling Ever Higher: The Continued Growth of Student Loans. Joint Center for Housing Studies, Harvard University, 25 Jul. 2019, www.jchs.harvard.edu/research-areas/research-briefs/piling-ever-higher-continued-growth-student-loans; Hanna, Sherman D., et al. “Behind the Numbers: Understanding the Survey of Consumer Finances.” Journal of Financial Counseling and Planning, vol. 29, no. 2, Nov. 2018, pp. 410–18. DOI.org (Crossref), doi:10.1891/1052-3073.29.2.410.

  23. We accounted for the complex structure of the SCF using the STATA package SCFCOMBO (Pence, 2015); this addressed survey weights and multiple imputation in order to produce both correct point estimates and correct standard errors to guide inferences. Please read our working paper for advanced methodological notes (preprints.apsanet.org/engage/apsa/article-details/5e8b3bedcf138e0019f49641); Collier, Daniel A., et al. Exploring the Relationship of Enrollment in Income-Driven Repayment to Borrower Demographics and Financial Outcomes. Preprint, Politics and International Relations, 6 Apr. 2020, DOI.org (Crossref), doi:10.33774/apsa-2019-nd8n2-v2; Looney, Adam, and Constantine Yannelis. Borrowers with Large Balances: Rising Student Debt and Falling Repayment Rates. Brookings Institution, Feb. 2018, www.brookings.edu/wp-content/uploads/2018/02/es_20180216_looneylargebalances.pdf.