Similar to our estimates, Shao (2015) and Bleemer et al. (2017) use variation in tuition at public institutions to conclude the attendance and completion margins, respectively, are insensitive to costs. Other studies have found more significant effects. As discussed in a review paper by Deming and Dynarski (2010), this literature often focuses on low-income or generally disadvantaged students, and the best identified papers find a $1,000 tuition increase (in 2003 dollars) reduces enrollment by 34 percentage points. These various findings may be reconcilable if the decision of traditional students to attend public 4-year colleges is price inelastic, while the attendance decision of marginal students considering community colleges or certificate programs is more price sensitive (Denning 2017). 17
We can test for this potential heterogeneity in price elasticity by regressing the probability of attending a public 2-year college against the average tuition charged by such schools in the individual’s home state in the 2 years after they turned 18. Results of these regressions are shown in column 3 of Table 6. This test is analogous to our baseline experiment, shown in column 1 of Table 6. This effect, although imprecisely estimated, is quite similar in magnitude to previous estimates covered in Deming and Dynarski (2010), especially when correcting for the 28 percentage points of inflation between 2003 and 2014.
Although not statistically significant, the point estimate of the effect of public 2-year tuition on enrollment at public 2-year colleges is substantially larger than the point estimate on the effect of public 4-year tuition on attendance at public 4-year universities
Tuition may also affect other educational outcomes, such as degree completion, take up of financial aid, or the choice of major. These outcomes may in turn affect the probability of homeownership-for example, completing a college degree may boost the student’s income and allow him or her to afford a home-which would violate the exclusion restriction. We therefore control for these outcomes in our preferred specifications. However, such outcomes may be endogenous to unobservable determinants of homeownership, in which case the estimator would still be inconsistentparing columns 1 and 2 of Table 4, we can see that the estimated effect of student loan debt on homeownership is qualitatively similar regardless of whether additional educational controls are included. We can also test for whether tuition is correlated with any of these outcomes. In columns 4 and 7 of Table 6, we present estimates of the effect of tuition on the probability of completing a bachelor’s degree before age 23 for the general population and for the subsample that attended college, respectively. We do not find any significant correlation between tuition and the completion of a bachelor’s degree. In columns 5 and 8, we estimate the effect of tuition on the probability of receiving any federal Pell Grants for the full sample and the college-going subsample. Again, the estimated effect is very small and not significant.
Specifically, a $1,000 tuition increase (in 2014 dollars) decreases public 2-year college attendance by more than 2 percentage points
Finally, we estimate the effect of tuition on the choice of major for those attending a public 4-year school before age 23, modeled as a multinomial logit regression with majors categorized into one of 16 groups. Results are presented in Table 7. We find little evidence of an effect of tuition on major choice. The estimated effect on the risk ratio relative to no declared major is significant for only one major choice: public administration and social work (number 13). This major choice is quite uncommon as well; only 42 individuals in our treatment group sample majored in this field.