Student Debt and Demographics: URM Status

In this blog post, we continue exploring various aspects of student loan debt, as we seek to greater understanding of the challenges facing students, families, and society. In our previous blog post, Exploring Student Debt: The National Perspective, we presented data from the Federal Reserve Bank of New York’s Center for Microeconomic Data that showed student loan debt has increased by more than 530% in the past 20 years (from $250 billion in 2003 to almost $1.6 trillion in 2021). Student loan debt is second only to mortgage loans ($10.93 trillion in 2021) in the types of household debt held by Americans, as total household debt in the US is closing in on $16 trillion.

Our attention now turns to slicing student loan debt in a variety of ways to see whether there are differential levels of student loan debt based on student characteristics. But first, we need to establish a baseline against which to measure those differences. For a number of years, the US Department of Education has been publishing the College Scorecards for more than 6,600 institutions that receive Title IV funds (federal financial aid). The intent of these Scorecards is to provide end-users, specifically prospective students and families, with data at their fingertips to aid in the college selection process. The Scorecard data will serve as our source for student loan debt data in this and upcoming blog posts.

Student Loan Debt Breakdown

While most metrics related to student loan debt are based on the median amount borrowed by only bachelor’s degree graduates, the College Scorecard data take a different spin on creating cohorts of students. Within an academic year, the Scorecard data capture all students who have left the university, whether through graduating with a bachelor’s degree or stopping-out. Because the Scorecard data are on all leaving students, not just those earning a degree, student loan debt values may seem to be lower than other published data points. This is partially due to the fact that median debt is calculated for students whether they stop-out after one semester or earn a degree after accumulating course hours across a decade of time.

Median Federal Loans (Texas Universities)

  • The first visualization below shows the median amount of federal student loan debt at Texas public universities, compared to the national and state averages.
  • The national average for four-year public universities in the College Scorecard data was $15,710 in the most recent cohort (AY2020), while the Texas average for public universities was $14,119. This places Texas 33rd out of the 50 states in the data.
  • There are five Texas institutions above the national average, with another six above the state average.

As we look toward the bottom of the chart, we see a group of institutions that are at or below a median federal loan debt value of $11,000. Within this group are several institutions with high concentrations of underrepresented minority (URM) student populations, which includes Black or African-American students, Hispanic students, or American Indian students. This observation prompted a series of questions pertaining to the connection between the level of URM undergraduate students and the median federal loan debt at that institution.

Median Federal Loan Trends by URM

  • Clicking on the second tab below shows the relationship between median federal loan debt (x-axis) and URM percentage of undergraduates (y-axis). All of the Texas public universities are shown using the color associated with their public university system affiliation.
  • The average percentage of URM students across American public four-year universities in the College Scorecard data was 28.9%.
  • The dotted line sloping downward from left-to-right shows the relationship between URM status and student loans; in general, the higher the percentage of URM undergraduates, the lower the median federal loan debt at that campus.

At the very top of the chart, you see 8 Texas universities that are either Historically Black Colleges and Universities (HBCUs) or Hispanic-Serving Institutions (HSIs). There are a number of high-URM institutions to the right of these Texas institutions, so we decided to create a chart with trendlines by institutional specialty: HBCU, HSI, or Not HBCU/HSI.

Median Federal Loan Trends (HBCU, HSI, Not HBCU/HSI)

  • In the third visualization below, HBCU institutions are shaded in blue, HSI institutions are shaded in orange, and Not HBCU/HSI institutions are shaded in gray.
  • The HSI and Not HBCU/HSI public four-year institutions in the College Scorecard data have essentially the same slope from left-to-right, although the intercept on the y-axis is different. This would indicate that the relationship between student loan debt and URM status is similar at these two institution types.
  • HBCU institutions, however, have a slope that is statistically different from the other two groups, as the line slopes up from right-to-left. This indicates that the association between the percentage of URM undergraduate students and student loan debt is different for students at HBCU institutions.

NOTE: Due to the volume of information in each visualization below, we recommend that you click the “Full Screen” button in the bottom-right corner to enhance viewing of the data.

So What?

In the last scatterplot above, many of the HBCU institutions were clustered above the median federal student loan debt of $15,710. The Median Federal Loan by Specialty Status visualization below shows the distribution of median federal student loans by institutional specialty type. The box-and-whisker plots show that the average federal student loan amount at the HSIs in the College Scorecard data was $12,133, while the average was $14,836 at Not HBCU/HSI institutions and $16,615 at HBCU institutions. Given the complex nature of these data, we will use the next few blog posts to connect additional student demographic and characteristics data to these findings to gain greater insight into challenges surrounding student loan debt.

NOTE: Due to the volume of information in each visualization below, we recommend that you click the “Full Screen” button in the bottom-right corner to enhance viewing of the data.

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