Figure 2.

In each year, one million individuals with student debt between the ages of 18-35 are observed, along with all of their student loans. The yellow series shows the share of student loans in each year of the cross section in which the current balance exceeds the starting balance.

The credit reporting data also includes each individual’s zip code. We match that to zip code-level demographic data from the American Community Survey to try to see how non-repayment differs by race. The pink series shows that same share of loans for individuals who reside in zip codes that are majority white, and the purple series shows that share for individuals who live in majority-minority zip codes. Even though there’s no direct information about the race of the actual individuals in the credit reports, and plenty of non-white people live in majority-white zip codes, while a smaller but still significant share of white people live in majority-minority zip codes, we can be fairly certain from this data that non-repayment is concentrated among non-white borrowers, as measured by loans with a higher balance than their original balance. That racial gap in non-repayment is significant throughout and rises slightly over time even while the overall rate of non-repayment also rises. (Note the kink point in 2016, after which non-repayment across all zip codes increases dramatically.) It’s the case that borrowers with higher balances are likelier to enroll in IDR because the savings from doing so is greater the higher the payments you would otherwise have to make, and higher-balance borrowers are, in general, higher-income. Still it’s also very likely that non-white borrowers are more likely to have enrolled in IDR, since they carry more debt conditional on income than white borrowers do. The pattern depicted in Figure 2, both over time and in the cross-section of zip codes, is consistent with that inference.

Figure 2 plots the percentage of loans at each observation date that had a higher balance at that point than they did at origination

One concern with this metric as a measure of non-repayment is that loans in deferment increase their principal balance as a matter of course, and younger’ loans are more likely to be in deferment. Therefore, it’s theoretically possible that an increasing share of loans with a higher current balance than initial balance reflects the changing age distribution of loans: more loans are taken out cohort-by-cohort, so over time, an increasing share of student loans would be younger and thus more likely to be in deferment. In plotting non-repayment through the share of loans where balances exceed the original, a greater share of student loans would appear by this metric to be in non-repayment status due to a rising share of loans in deferment, not IDR, delinquency, or some other reason pertaining to the non-repayment of loans over their term.

Figure 3 addresses this concern by illustrating how the student loan age distribution has changed over time. It’s getting older, not younger-itself evidence of declining repayment, and suggesting that the non-repayment or level effect outweighs the increased-origination or composition effect. Note especially the rising share of loans that are 10+ years old, which is to say, older than the term in which a traditional student loan is supposed to be paid off.

To return to payday loans Deer Park TX the bathtub metaphor, overall, the water in the tub is getting older’ because the old’ water that isn’t draining out and thus remains in the tub for longer counteracts the young-ness’ of the new’ water pouring in. The implication for Figure 2, then, is that even though you’d expect more loans to be out of deferment and in repayment due to the mix of loans getting older, we still see increasing balances and therefore not actual repayment. And that, in turn, is further evidence that if we had 10 years of panel data for subsequent cohorts following the 2009 cohort depicted in Figure 1, that data would show even worse progress toward repayment for those younger cohorts.