To Begin Solving Student Debt, the Education Department Must Factor In Race and Ethnicity
In fall 2017, the U.S. Department of Education released shocking findings about the long-term outcomes of student borrowers of color, particularly those who are black or African American. The data showed that the average black or African American borrower who entered college in the 2003-04 academic year had made no progress paying down their debt by 2015; in fact, they owed more than they originally borrowed. Even worse, nearly half of black or African American student borrowers had defaulted on their loans within the 12-year time period. These findings revealed a repayment crisis for black borrowers and raised serious questions about how the American higher education system serves all communities of color.
But the data have not yet led to any major plans in Congress to improve the outcomes of student borrowers of color. Just last month, for example, front-page headlines trumpeted a wealthy financier’s pledge to pay the student loan debt of an entire graduating class at historically black Morehouse College, demonstrating anew how much student debt is still weighing down African American borrowers—and why these students need systemic solutions.
In part, the lack of progress is due to the fact that the data only skim the surface and don’t reveal enough to allow policymakers, researchers, or institutional leaders to build policy solutions to tackle discrimination. To shed light on why so many borrowers of color are not benefiting from their time in college, the Department of Education should start collecting more-detailed data on the race and ethnicity of students, especially those who receive federal financial aid. It could best do this in one of two ways: 1) adding a question on race and ethnicity to the application that students complete when they apply for federal financial aid; or 2) requiring institutions to submit information on race and ethnicity as part of larger data reforms that allow the Education Department to collect records on every student attending a U.S. college.
The Beginning Postsecondary Students Longitudinal Study
Currently, the Education Department only collects longitudinal data that show debt outcomes by student race and ethnicity. The Beginning Postsecondary Students Longitudinal Study is one of these efforts, following a new cohort every eight years. This survey unpacks valuable details about how borrowers progress through loan repayment over time, but it doesn’t collect enough responses to analyze smaller groups of color, such as Asian Americans and American Indians or Alaska Natives. It also doesn’t track students year to year. Therefore, it fails to answer many of the most pressing questions about inequities in borrowing. It would be too costly for sample surveys to interview enough borrowers to estimate outcomes in every state or at every college or to break down the results by multiple intersecting identities, such as black or African American borrowers who attend part time and have dependents.
It’s understandable that any proposal to bring more information about race and ethnicity into the student loan conversation may raise concerns about the possible misuse of these data to engage in discriminatory practices. But laws dictating the collection of data about race and ethnicity in the home mortgage market have proved that the data are a crucial part of combating discrimination such as redlining. This column looks at why more data on race and ethnicity are necessary in solving the student loan crisis, using the example of data collection in the home mortgage market to illustrate the benefits of more closely considering race and ethnicity.
Why more data on the race and ethnicity of student borrowers are necessary
Obtaining data on race and ethnicity at the borrower level would offer two benefits: improved oversight and the opportunity to develop fairer policy solutions.
Information on the race and ethnicity of financial aid recipients is crucial to enforcing anti-discrimination and civil rights laws effectively. That information would make it possible to conduct quantitative analyses that could be used to identify patterns of bias. For example, knowing the race and ethnicity of borrowers would allow Education Department staff to use existing oversight tools to identify disparities and ensure that student loan servicers are not discriminating against black or African American borrowers, whether intentionally or as a result of unconscious bias. The department could use the data to examine the average length of calls between servicers and borrowers by borrower race and ethnicity, for example, or it could listen to recordings of borrower phone calls to look for differences in how servicers speak with borrowers of different races and ethnicities.
Obtaining data on race and ethnicity would unlock similar possibilities for oversight of individual colleges. To identify institutions that may be systematically shortchanging students and borrowers of color, the Department of Education could look for disparate outcomes among students who withdraw from a college, the amount of loans borrowed, repayment success, and many other measures.
Developing fairer policies
Student-level data on race and ethnicity can also assist with constructing more equity-minded policy solutions. For instance, there is interest in Congress in making changes to income-driven repayment plans that tie what a borrower pays each month to their income. Having data on race and ethnicity would make it possible to see the equity implications of various proposals to revamp these plans. For example, there are wage gaps between white and black and white and Hispanic college graduates that could affect the earnings for these borrowers of color and lead to differing repayments rates for borrower groups.
Similarly, race and ethnicity data would allow policymakers to head off changes to student loans that could deepen inequities. For example, some researchers have called to introduce underwriting into the student loan system; this would limit access to loans for students who appear to be more of a credit risk, such as black and Hispanic borrowers living in low-income areas. Although existing data—such as a family ZIP code or address—could potentially help illustrate that these borrowers would be disproportionately affected by underwriting, having data on students’ race and ethnicity would make it easier to show the disparate impacts of limiting loans by explicitly connecting race and ethnicity data with discriminatory actions. This could make it much harder for lawmakers to enact concerning policy changes.
Home mortgage market provides a model for addressing discrimination through data
The United States uses data to help prevent and remedy discrimination in another major area of lending—mortgages. In the 1960s and 1970s, pervasive redlining harmed homeowners of color by undervaluing homes in predominately black and Latino neighborhoods and simultaneously preventing these borrowers from getting reasonable home mortgages. While discriminatory housing practices still exist today, the prevalence of anti-discrimination housing legislation has helped black and Latino homeowners make some gains in the market and hold lenders accountable for discrimination. The most noteworthy bill is the Home Mortgage Disclosure Act (HMDA), which Congress passed in 1975; it mandated that financial institutions collect and disclose mortgage data such as the race and ethnicity of the borrower. Having race and ethnicity data was vital, as it allowed researchers and policymakers to identify instances of discrimination.
And the HMDA is still a vital tool for identifying discriminatory actions against black and Latino borrowers. In 2016, for example, the Consumer Financial Protection Bureau found that BancorpSouth Bank regularly discriminated against black and Latino borrowers by systematically preventing them from accessing loans comparable to what was available to white borrowers. For instance, black borrowers were more likely to be denied loans and were also charged higher interest rates than white borrowers with similar credit backgrounds. Without data on applicants’ racial and ethnic backgrounds, the agency would have had much more trouble connecting widespread acts of discrimination to a predictor like race and ethnicity.
Instead of being a tool to further discrimination in the mortgage market, data on race and ethnicity became a powerful means to combat it. However, discrimination still manifests itself in many ways. While the HMDA is focused on private loans, having equivalent data on student loans could help in identifying similar discrimination in the federal student loan system.
As more people of color enroll in college and take on student loan debt, there is growing recognition that student loans are a civil rights issue, with borrowers of color shut out in large numbers from experiencing the benefits that American higher education can and should offer. With more comprehensive race and ethnicity data on student loans, the federal government could identify instances of discrimination against borrowers, such as loan servicers performing worse with borrowers of color or financial aid administrators more often denying professional judgement reviews to borrowers of color. Reviews could also be conducted to see if schools are intentionally or unintentionally saddling students of color with more debt. Continuing to ignore the role of race and ethnicity in student loan outcomes, however, means allowing the inequities in the system to fester.
Victoria Yuen is a policy analyst for Postsecondary Education at the Center for American Progress.
The positions of American Progress, and our policy experts, are independent, and the findings and conclusions presented are those of American Progress alone. A full list of supporters is available here. American Progress would like to acknowledge the many generous supporters who make our work possible.