# What Explains Racial Gaps in Large Graduate Student Debt Burdens?

In my previous blog post, I used brand-new data from the 2015-16 National Postsecondary Student Aid Study (NPSAS) to look at trends in debt burdens among graduate students. The data point that quickly got the most attention was the growth in the percentage of African-American graduate students with at least \$100,000 in debt between their undergraduate and graduate programs, with 30% of black students having six-figure debt burdens in 2015-16 compared to just 12% of white borrowers. This means that roughly 150,000 black borrowers had \$100,000 in debt, more than half of the number of white borrowers with the same debt level (250,000) despite white graduate student enrollment being four times as white as black grad student enrollment.

My next step is to examine whether the black-white borrowing gap could be explained by other demographic and educational factors. I ran two logistic regressions with the outcome of interest being \$100,000 or more in total educational debt using PowerStats, with the results presented in odds ratios. (To interpret odds ratios, note that they are percent changes from 1. So a coefficient of 0.5 means that something is 50% less likely to happen and 1.5 means that something is 50% more likely to happen.) The first regression below only controls for race/ethnicity.

 Table 1: Partial regression predicting likelihood of \$100,000 or more in debt among graduate students. Coefficient (Odds Ratio) Characteristic 95% CI p-value Race/ethnicity (reference: white) Black or African American 2.50 (1.91, 3.26) 0.000 Hispanic or Latino 1.12 (0.89, 1.41) 0.347 Asian 0.62 (0.46, 0.83) 0.002 American Indian or Alaska Native 1.31 (0.49, 3.50) 0.595 Native Hawaiian/other Pacific Islander 1.35 (0.38, 4.74) 0.640 More than one race 1.73 (1.08, 2.77) 0.023 Source: National Postsecondary Student Aid Study 2015-16.

This shows that black students were 150% more likely to have six-figure debt than white students (p<.001), while Asian students were 38% less likely (p<0.01). Hispanic students had a slightly higher point estimate, but it was not statistically significant.

I then controlled for a number of factors that could be associated with high graduate student debt amounts, including other demographic characteristics (gender, age, and marital status), level of study (master’s or doctoral), institution type, and field of study. The regression results are shown below.

 Table 2: Full regression predicting likelihood of \$100,000 or more in debt among graduate students. Coefficient (Odds Ratio) Characteristic 95% CI p-value Race/ethnicity (reference: white) Black or African American 2.30 (1.79, 2.97) 0.000 Hispanic or Latino 1.03 (0.80, 1.33) 0.828 Asian 0.69 (0.48, 0.98) 0.036 American Indian or Alaska Native 0.97 (0.25, 3.77) 0.964 Native Hawaiian/other Pacific Islander 1.61 (0.44, 5.84) 0.468 More than one race 1.82 (1.12, 2.95) 0.015 Female 1.00 (0.84, 1.19) 0.990 Age as of 12/31/2015 1.04 (1.03, 1.04) 0.000 Marital status (reference: single) Married 0.68 (0.55, 0.85) 0.001 Separated 0.94 (0.51, 1.73) 0.840 Graduate institution (reference: public) Private nonprofit 1.64 (1.36, 1.98) 0.000 For-profit 2.15 (1.64, 2.82) 0.000 Graduate degree program (reference: master’s) Research doctorate 3.00 (2.38, 3.78) 0.000 Professional doctorate 7.07 (5.61, 8.90) 0.000 Field of study (reference: education) Humanities 0.99 (0.66, 1.48) 0.943 Social/behavioral sciences 1.85 (1.38, 2.48) 0.000 Life sciences 1.71 (1.14, 2.56) 0.009 Math/Engineering/Computer science 0.34 (0.20, 0.57) 0.000 Business/management 0.91 (0.64, 1.28) 0.577 Health 1.93 (1.47, 2.53) 0.000 Law 1.38 (0.90, 2.11) 0.140 Others 1.26 (0.89, 1.79) 0.186 Source: National Postsecondary Student Aid Study 2015-16.

Notably, the coefficient for being African-American (relative to white) decreased slightly in the regression with additional control variables. Black students were 130% more likely to have six-figure debt burdens than white students, down from 150% in the previous regression. Not surprisingly, doctoral students, students at private nonprofit and for-profit colleges, and students studying health, life sciences, and social/behavioral sciences were more likely to have \$100,000 in debt than public university students, master’s students, and those studying education. Meanwhile, STEM students were far less likely to have \$100,000 in debt than education students, which is not surprising given the large number of assistantships available in STEM fields.

This regression strongly suggests that the black/white gap in large student debt burdens cannot be explained by other demographic characteristics or individuals’ fields of study. Financial resources (such as the large wealth gap between black and white families) are likely to blame, but this is not well-measured in the NPSAS. The best proxy is a student’s expected family contribution (EFC), which only measures a student’s own resources as an adult student. Including EFC as a variable in the model brings the black/white gap down to 120% (not shown here for the sake of brevity), but a good measure of wealth likely shrinks the gap by a much larger amount.

## Author: Robert

I am an a professor at the University of Tennessee, Knoxville who studies higher education finance, accountability policies and practices, and student financial aid. All opinions expressed here are my own.