Does Income Driven Repayment Help Low-Income, Underserved Borrowers?

Published Apr 28, 2017

by: Tyler Wu, Policy Research Intern

Cumulative student loan debt in the United States totals $1.3 trillion for just over 44 million total borrowers. The U.S. Department of Education (ED) recently announced that about 14 percent of those borrowers defaulted on their loans within three years of entering repayment.

What are the different repayment options for federal borrowers? Currently, there are nine repayment plans that borrowers can select based on their type of loan—including five income-driven repayment (IDR) plans. IDR plans base monthly payments on a share of the borrower’s income rather than the amount that the borrower owes. IDR plans keep monthly payments manageable, comprise a system that takes into consideration life events, and contribute to a financial safety net for borrowers. Since 2016, about 25 percent of borrowers have enrolled into income-based plans.

However, we do not have the data to fully understand the potential effect these programs have on underrepresented and low-income students at the national level. How many students of color use IDR plans? Do first-generation college students use IDR plans? How does enrollment in these plans affect delinquency and default rates? According to a study by Young Invincibles, students of color disproportionately default on their loans. Furthermore, while 35 percent of White students paid off their loan balances, Latinx students were over five times more likely to be behind on payments.

To address these important issues, ED should collect disaggregated data for borrowers in different repayment plans in order to inform policies intended to streamline repayment options. These data will provide needed context around who benefits from IDR, and to what extent, especially for low-income students and students of color.

Before enacting policy change, policymakers should:

  • Consider input from higher education experts on the types of data that should be collected related to federal student loans, including—
    • This October 2016 letter to former Secretary of Education John King, highlighting ways that ED can facilitate in-depth research on student loan outcomes using data from the Office of Federal Student Aid.
    • This March 2017 letter to current Secretary of Education Betsy DeVos, urging her to enhance postsecondary education data quality and improve data transparency by collecting more accurate information on debt repayment, including IDR borrower characteristics like race/ethnicity and status as a first-generation college student.
    • This April 2017 letter to the Consumer Finance Protection Bureau, outlining support for additional collection of disaggregated data to better understand student loan outcomes by servicer.
  • Leverage existing bipartisan support to streamline and simplify loan repayment. Policymakers should consult with experts to create policy that best serves low-income and underserved student populations, with a goal to improve their outcomes. Recent examples of bipartisan legislation include the Repay Act of 2015 (S. 85, 114th Congress) and the Dynamic Repayment Act of 2017 (S.799, 115th Congress).
  • Another approach would be to automatically enroll borrowers into an income-based repayment plan if they are eligible. A report, Automatic for the Borroweroutlines examples of this policy that could be explored in the upcoming Higher Education Act reauthorization. In order to implement this type of policy effectively, federal data systems must be able to automatically retrieve income information, to streamline the process and remove unnecessary obstacles for borrowers.

To ensure that repayment policies are effective and target the neediest students, policymakers should use disaggregated data when crafting policy.  A data-driven approach should lessen the burden on federal borrowers and lead to improved student loan outcomes.