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. Reverse causality is also a potential source of bias if purchasing a home before leaving school affects students’ subsequent borrowing behavior. To reliably identify the causal effect of student loan debt, we need a source of variation that is exogenous to all other determinants of homeownership.
We propose that the average tuition paid by in-state students at public 4-year universities in the subject’s home state during his or her prime college-going years provides quasi-experimental variation in eventual student loan balances for students who attended those schools
A large fraction of students attend public universities in their home state, so the loan amounts they require to cover costs vary directly with this price (in our sample, nearly half of the students who had attended any college before age 23 had attended a public 4-year university in their home state). Additionally, this tuition cannot be affected by the choice of any particular individual. Rather, changes in the tuition http://getbadcreditloan.com/payday-loans-or/ rate depend on a number of factors that are arguably exogenous to the individual homeownership decision, ranging from the level of state and local appropriations to expenditure decisions by the state universities.
A short overview of the major drivers of prevailing tuition rates will help clarify the validity argument and locate potential points of failure. One major source of tuition increases is changes to particular schools’ cost structures. According to Weeden (2015), these costs include compensation increases for faculty members, the decision to hire more administrators, benefit increases, lower teaching loads, energy prices, debt service, and efforts to improve institutional rankings, all of which have been linked to tuition increases since the 1980s. Institutions also compete for students, especially those of higher academic ability, by purchasing upgrades to amenities such as recreational facilities and residence halls. These upgrades are often associated with increased tuition to pay for construction and operation of new facilities. Finally, tuition and fees are frequently used to subsidized intercollegiate athletic ventures. In recent years, athletic expenses have increased and now may require larger subsidies from tuition and fee revenue at many colleges.