A concern with this framework is that selection into the treatment group (i.e., attendance at a public 4-year university before age 23) is a choice on the part of the individual. It would seem quite plausible that the attendance choices of prospective students depend on the tuition they face, and such endogenous selection would bias our estimates. We show, however, that an individual’s probability of attending a public 4-year university is essentially uncorrelated with the average tuition charged, at least for the relatively small increases in tuition used in this study to identify the effect of interest. In section IV.E, we discuss the issue of endogenous selection in detail and place our findings in the context of the relevant literature.
Using the aforementioned treatment/control group framework, we find a substantial negative effect of student loan debt on homeownership early in the life cycle. In particular, a $1,000 increase in student loan debt accumulated before age 23 (representing an approximate 10% increase in early-life borrowing among the treatment group) causes a decrease of about 1.8 percentage points in the homeownership rate of treatment group students by their mid-20s in our preferred specification. 3 Given the rapidly increasing age profile of homeownership early in the life cycle, our results imply that a young person’s entry into homeownership would be delayed 1 year by an increase of a little over $3,000 in student loan debt. 4
Our findings may therefore be more relevant for times of relatively easier mortgage credit, as opposed to the immediate postcrisis period in which it was much more difficult to get a home loan
In section IV.G, we present evidence that credit scores provide a significant channel by which student loan debt affects borrowers ability to obtain a mortgage. Higher debt balances increase borrowers’ probability of becoming delinquent on their student loans, which has a negative impact on their credit scores and makes mortgage credit more difficult to obtain.
To be sure, this paper estimates the effect of a ceteris paribus change in debt levels, rather than the effect of a change in access to student loan debt, on future homeownership. In particular, if student loans allow individuals to access college education-or, more broadly, acquire more of it-student loan debt could have a positive effect on homeownership as long as the return to this additional education allows individuals to sufficiently increase their future incomes. Thus, our exercise is similar in spirit to a thought experiment in which a small amount of student loan debt is forgiven at age 22, without any effect on individuals’ decisions on postsecondary education acquisition.
We also extend the analysis to investigate whether student loans affect the size of the first observed mortgage balance and whether credit scores provide a channel by which student loan debt can restrict access to homeownership
Another caveat to keep in mind is that our estimation sample mostly covers the period prior to the Great Recession. We discuss in section II.B how various underwriting criteria in the mortgage market may interact with student loan debt to restrict some borrowers’ access to credit.
Several recent studies have looked at the effect of student loans in different contexts, finding that greater student loan debt can cause households to delay ) and fertility ), lower the probability of enrollment in a graduate or professional degree program (Malcom and Dowd 2012; Zhang 2013), reduce take-up of low-paid public interest jobs (Rothstein and Rouse 2011), or increase the probability of parental cohabitation (Bleemer et al. 2014; Dettling and Hsu 2017).
The rest of our paper is organized as follows. Section II briefly reviews the institutional background of the student loan ines the main theoretical channels through which student loan debt likely affects access to homeownership. Section III gives an overview of the data set and defines variables used in the analysis. Section IV presents check over here the estimator in detail, as well as the results of both the instrumental variable analysis and a selection-on-observables approach. The instrument is then subjected to a series of validity checks. Section V interprets and caveats our main findings. Section VI concludes.