Giving Compass' Take:
- Erica Blom et al. explain why Obama-era gainful employment regulation methods are flawed, and offer a strategy for assessing programs more effectively.
- Why do the methods of regulation and data-counting affect program outcomes? How can you support regulation that is more difficult for institutions to "game"?
- Read about fostering equity through tech apprenticeships.
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Gainful employment (GE) regulations, implemented by the Obama administration in 2015, were intended to hold for-profit and nondegree programs accountable by assessing whether graduates’ earnings were high enough to justify the debt they had taken on. Repealed under Trump, these rules could be reinstated by the Biden administration. If so, policymakers should consider “rolling up” programs to include as many programs as possible.
GE regulations, as designed in 2015, were based on two debt-to-earnings ratios of graduates to assess whether their earnings were high enough to justify the debt. The first considered the ratio of annual student loan payments to total annual income, and the second considered the ratio of annual student loan payments to discretionary income (the amount above 150 percent of the federal poverty level). If the first ratio was more than 12 percent and the second more than 30 percent, the program could risk loss of Title IV eligibility (that is, they would no longer have access to federal grants and loans).
However, for privacy and statistical stability, programs with fewer than 30 graduates (pooled across two years) were not required to report data. This excluded a considerable share of programs and students: roughly 73 percent of GE-qualifying programs and 23 percent of students in those programs would have been excluded from measurement in the 2017–18 and 2018–19 graduate cohorts.
One way to address this issue is to iteratively “roll up” programs within a given credential level to four-digit or two-digit CIP codes, or even to the institution, until the threshold of 30 students is met. The concern, however, is potentially combining programs with very different outcomes. For example, a failing program could be reported along with a successful program, and either the failing program would get unfairly saved or the successful program unfairly put at risk of closing.
Read the full article about rolling up by Erica Blom, Robert Kelchen, Carina Chien, and Kristin Blagg at Urban Institute.