A new report from the Postsecondary Education and Economic Research Center digs into the economic value of graduate degrees, this time factoring in the full cost of tuition and fees.
Researchers Joseph Altonji and Zhengren Zhu used administrative data from the Texas Education Research Center to estimate the real impact of 121 advanced degree programs.
They compared graduates’ actual outcomes to what they might have earned if they’d skipped grad school.
Some fields actually show negative cost-adjusted lifetime returns, while others offer big positive gains.
It’s clear that the value of graduate study depends a lot on your field and the way the job market shifts—especially with AI shaking things up.
Study snapshot: methods and key numbers
The analysis doesn’t just look at salary bumps—it tries to estimate what graduates would have made if they hadn’t gone for that extra degree. That way, you get a clearer sense of the real cost-adjusted return across 121 programs.
They leaned on strong causal methods and administrative data to tease out the effect of grad school from everything else affecting careers. The end result? A detailed, field-by-field look at which advanced degrees actually pay off once you count tuition.
Headline results at a glance
On average, grad degrees still boost earnings by about 17% after costs, but the range is huge depending on your field. MDs are in a league of their own, racking up a wild 173% cost-adjusted return—even with medical school costing around $229,000. Law degrees and MBAs also do well, at 41% and 13% respectively. But some areas—like psychology (-8%), clinical psychology (-5%), social work, and curriculum and instruction—actually show negative returns. So, yeah, it’s risky to assume every grad degree guarantees a payoff.
Field-by-field returns: who gains and who loses
Digging deeper, the study shows that plenty of master’s programs in supposedly “AI-proof” or stable fields don’t actually deliver strong cost-adjusted returns once you count tuition and lost time. Even some tech and engineering master’s degrees only offer modest gains, mostly because undergrads in those fields already earn well. For instance, computer science gives about 6%, electrical and mechanical engineering about 4%, and computer engineering around 2%.
Practical implications for students and families
- Check cost-adjusted ROI for each field instead of trusting degree prestige or average salaries.
- Think about AI-driven demand and whether AI skills will boost your earnings or job options.
- Don’t forget opportunity costs—tuition, time spent in school, and missed paychecks all matter when you weigh long-term gains.
- Look at alternatives like focused professional credentials in hot fields if a full grad degree doesn’t offer much ROI.
Context, AI, and the policy implications
The study drops into a labor market that’s changing fast. AI is pushing up demand for experienced workers, but at the same time, it’s cutting out some entry-level roles.
AI-related skills pull in a premium—23% compared to just 8% for a plain bachelor’s degree. Advanced training can really make a difference, but only if the field sticks around and keeps needing people.
The researchers point out something bigger happening too. More Americans are getting graduate degrees—31% in 1993, up to 42% by 2022. But even with that rise, a lot of folks are starting to wonder if grad school is really worth it, especially in some fields.
For institutions and policymakers, these findings push for clearer ROI data and better career advising. Programs should actually match up with jobs that are in demand.
Causal estimates help here, since they tease out what grad study really does for people, instead of just reflecting who they already were or what the job market looked like when they started.
Here is the source article for this story: College grads in ‘AI-proof’ careers like psychology and education are seeing negative returns on their degrees