Using the National Longitudinal Survey of Youth 1997, Houle and Berger (2015) estimate that a $1,000 increase in student loan debt decreases the probability of homeownership by 0.08 percentage points among a population composed largely of 20- and 25-year-olds. Similarly, using the National Education Longitudinal Study of 1988, Cooper and Wang (2014) find that a 10% increase in student loan debt (approximately equivalent to a $1,000 increase for our sample) reduces homeownership by 0.1 percentage points among 25- and 26-year-olds who had attended college.

C. Instrumental Variable Estimation

While the estimators used above control for some important covariates, there may still be unobservable variables biasing the results. It is not clear, a priori, in which direction the estimates are likely to be biased by such unobservable factors. For example, students with higher unobservable academic ability may borrow more, either because they choose to attend more expensive institutions or because they anticipate greater future incomes. These higher-ability students would also be more likely to subsequently become homeowners, introducing a positive bias in the estimates. Conversely, students from wealthy backgrounds may receive financial assistance from their parents and therefore need to borrow less to pay for school than their less advantaged peers. For example, Lovenheim (2011) finds shocks to housing wealth affect the probability families send their children to college. Parental contributions could help these same students to later purchase a home, which would tend to introduce a negative bias. The covariates we have may not adequately control for these or other omitted factors. […]