Subsidies Increase Tuition, Part XIV

In a new NBER paper, Accounting for the Rise in College Tuition, Grey Gordon and Aaron Hedlund create a sophisticated model of the college market and find that a large fraction of the increase in tuition can be explained by increases in subsidies.

With all factors present, net tuition increases from $6,100 to $12,559. As column 4 demonstrates, the demand shocks— which consist mostly of changes in financial aid—account for the lion’s share of the higher tuition. Specifically, with demand shocks alone, equilibrium tuition rises by 102%, almost fully matching the 106% from the benchmark. By contrast, with all factors present except the demand shocks (column 7), net tuition only rises by 16%.

These results accord strongly with the Bennett hypothesis, which asserts that colleges respond to expansions of financial aid by increasing tuition.

Remarkably, so much of the subsidy is translated into higher tuition that enrollment doesn’t increase! What does happen is that students take on more debt, which many of them can’t pay.

In fact, the tuition response completely crowds out any additional enrollment that the financial aid expansion would otherwise induce, resulting instead in an enrollment decline from 33% to 27% in the new equilibrium with only demand shocks. Furthermore, the students who do enroll take out $6,876 in loans compared to $4,663 in the initial steady state….Lastly, the model predicts that demand shocks in isolation generate a surge in the default rate from 17% to 32%. Essentially, demand shocks lead to higher college costs and more debt, and in the absence of higher labor market returns, more loan default inevitably occurs.

Sound familiar? Some of these results appear too large to me and the authors caution that they need to assume a lot of monopoly power to solve their model so the results should be taken as an upper bound. Nevertheless, the Econ 101 insight that subsidies increase prices (even net for those who are not fully subsidized) holds true.

I wonder where else (& here) we could apply this insight?