Sources of rising student debt in the U.S.: College costs, wage inequality, and delinquency
What this paper finds — and why it matters
Layer 1: Overview
U.S. outstanding student debt rose roughly 20-fold, from about $50 billion in 1985 to nearly $1 trillion in 2014 (about 7% of GDP), making it the second-largest form of household debt after mortgages. Kim and Kim ask how much of this growth in undergraduate loans can be explained by three forces: rising college costs, rising wage inequality, and the option to become delinquent. They build a partial-equilibrium incomplete-markets overlapping-generations (OLG) model with a three-stage life cycle (college, work, retirement, ages 18-85, annual periods). Individuals are endowed with heterogeneous ability (decile distribution of demeaned log AFQT80) and correlated parental transfers, and choose college attendance, government student-loan borrowing, and whether to repay or become delinquent (90+ days past due, carrying a skill-specific utility cost). College lasts 4 years; lower-ability students face a dropout probability at year 2 (aggregate enrollment-to-non-completion is ~54%). Loans follow a fixed 10-year repayment schedule (nT=10), accrue interest at rb=6.1% (risk-free r=3%), with a cumulative borrowing limit of $23,000 (raised to $31,000 from 2008) and a cap of 70% of tuition.
The model is calibrated to the 1985 steady state, mainly with NLSY79 (plus NLSY97 for transfers/costs and PSID for the experience premium and wage-shock process). Transitional dynamics 1985-2014 feed in three time-varying inputs: rising college costs (net cost rises from $5,859 in 1985 to $12,000 in 2014), rising wage inequality (persistent-shock variance rises from 0.015 to 0.03 and transitory from 0.05 to 0.08; college wage premium from 1.2 to 1.37; skilled ability premium from 0.89 to 1.33; shock persistence ρ=0.9791), and a growing preference for college (a declining psychic cost calibrated to reproduce rising attainment).
Main results: the benchmark economy raises aggregate undergraduate debt from $37 billion (1985) to $351 billion (2014), a $314 billion increase that explains about 64% of the observed U.S. rise — without being calibrated to the debt increase. Rising college costs are the primary driver of higher borrowing; rising income risk and declining average student ability drive higher delinquency (the aggregate delinquency rate more than triples 1985-2014; 16% of borrowers delinquent in 2014). In a decomposition (Table 3), fixing college costs cuts the debt rise to +$33B; fixing ability premia leaves it roughly unchanged (+$317B); fixing the college wage premium lowers it by $49B (to +$265B); and fixing wage-shock variances raises it to +$418B (less risk means less delinquency but more borrowing). Removing the delinquency option entirely cuts the debt rise to $178 billion, so delinquency accounts for about 43% of the transitional increase. Delinquency works through a mechanical channel (missed payments plus accrued interest) and an incentive channel (delinquency as insurance encourages borrowing, the Domar-Musgrave effect); roughly one-third of the benchmark/no-delinquency gap is mechanical and two-thirds incentive. Finally, an income-driven repayment (IDR) plan (10% of discretionary income) cuts delinquency from 5.0% to 2.2% and slows debt growth to a $169 billion rise over the transition, because IDR substitutes for delinquency as insurance.
Layer 2: Deep Dive
What is the model and the identification/quantification strategy, and what are the main threats to it?
It is a partial-equilibrium incomplete-markets OLG model solved as two steady states (1985 and 2014) with a transition path. Identification of the aggregate-debt contribution is not econometric but quantitative: the model is calibrated to 1985 cross-sectional moments (and a few transition-path moments) WITHOUT targeting the aggregate debt increase, then exogenous time-varying inputs (college costs, wage inequality, college preference) are fed in and the resulting debt path is compared to data, explaining ~64% of the rise. The main threats are: (i) the model is partial equilibrium, taking costs/inequality/preferences as exogenous (general-equilibrium feedback, e.g. tuition responding to inequality per Cai-Heathcote 2022, is abstracted from); (ii) the residual 36% is unexplained and could reflect omitted forces such as private loans, for-profit institutions, or graduate-school spillovers; (iii) the ‘preference for college’ is a reduced-form declining psychic cost that absorbs many unmodeled drivers (job amenities, over-optimism about graduation) rather than being separately identified.
What are the two channels through which delinquency raises debt, and how are they distinguished?
The mechanical channel: missed scheduled payments plus accrued interest are added directly to the outstanding balance. The incentive channel: the option to delay payment acts as insurance against adverse post-college income shocks, encouraging students to borrow more ex ante (the Domar-Musgrave effect). They are separated with a ‘mechanical effect counterfactual’ that removes delinquency but holds borrowing fixed at benchmark levels: the gap between benchmark and this counterfactual is the mechanical effect, and the gap between the mechanical counterfactual and the full no-delinquency economy is the incentive effect. The incentive effect dominates — roughly two-thirds of the benchmark/no-delinquency gap — because the mechanical effect operates only through the small share of delinquent borrowers (16% in 2014), while the incentive effect shapes all college students’ borrowing. The incentive channel grows over time as income risk rises.
What heterogeneity is documented?
Borrowing increases with ability and (weakly) with parental transfers, driven by consumption smoothing: high-ability individuals anticipate higher lifetime earnings and borrow more against future income. Notably, in the 1985 simulation, average earnings during college exceed college costs across all ability groups, so most students could self-finance but still borrow. Dropout probability declines sharply with ability (so ~54% of enrollees do not complete). Delinquency rates differ by skill: 7% for college graduates vs 25% for college dropouts in 2010 (calibration targets). The stronger college preference draws more low-ability students into college over time, lowering average student ability and raising delinquency. Under IDR, the rise in borrowing participation (34%->40%) is driven primarily by low-ability students.
What robustness/validation checks are run?
Validation (not targeted): the model reproduces the rising trend in average annual borrowing 1993-2014 (NPSAS), the cross-sectional borrowing distribution by ability tercile and parental-transfer quartile in 1997 (NLSY97), the more-than-tripling of the aggregate 90+ day delinquency rate (FRBNY), and ~8% of borrowers behind on payments 10 years after graduation (Table D1). It also replicates the untargeted population distribution across ability/transfer cells. Robustness: results are stable with 10 or more ability grid points; the implied ~12% decline in average student ability between the 1960s and 1990s cohorts is consistent with Hendricks-Schoellman (2014). An alternative delinquency definition using 270-day default plus wage garnishment (Appendix C) yields similar aggregate effects, with delinquency explaining about 33% of the debt increase (vs 43% in the 90-day benchmark). A weakness flagged by the authors: the model generates flat college costs across parental-transfer quartiles and so misses the non-monotonic (U-shaped) cost pattern in the data, because ability and transfers are positively correlated.
How does this paper relate to and differ from closely related prior work?
It builds directly on Abbott, Gallipoli, Meghir, Violante (2019), whose framework of government grants/loans and college attainment it extends by adding an endogenous delinquency choice on student debt to capture debt amplification. It differs from Ionescu (2008, 2009), which evaluate specific loan-policy reforms (lock-in interest, flexible repayment, eligibility) for enrollment/default, by focusing on the dynamics of the aggregate debt stock rather than direct policy evaluation. It connects to the credit-constraints/family-income literature (Belley-Lochner 2007, Lochner-Monge-Naranjo 2011, Carneiro-Heckman 2002, Keane-Wolpin 2001) by jointly modeling parental transfers and borrowing, and to the repayment/default-determinants literature (Looney-Yannelis 2015, Lochner-Monge-Naranjo 2015, Deming-Goldin-Katz 2012). It remains agnostic about private loans (only 6-7% of outstanding debt and structurally different, per Ionescu-Simpson 2016).
What are the policy implications and their scope conditions?
IDR is identified as an effective instrument for managing student-loan burdens: capping payments at 10% of discretionary income reduces delinquency sharply (5.0%->2.2% in steady state) and slows the transitional debt rise from $314B to $169B, because formal repayment flexibility substitutes for informal insurance via delinquency. Scope conditions: IDR also increases loan participation (34%->40%), so the slowdown in debt comes from the delinquency-reduction effect dominating the borrowing-increase effect; in steady state total debt falls only $3 billion, the larger effect being on the transition. The result holds in partial equilibrium with no model re-calibration and assumes borrowers choose labor supply anticipating 10%-of-income repayment; general-equilibrium and fiscal-cost (loan-forgiveness) implications are not modeled. Take-up was low over 1985-2014 (11% of undergraduate borrowers in 2010, 24% by 2017), so IDR is treated as a forward-looking policy extension rather than a driver of the historical debt rise.
What other significant findings or caveats appear?
Fixing wage-shock variances counterintuitively raises debt (+$418B vs +$314B) because lower income risk reduces delinquency but encourages more borrowing — illustrating that inequality’s net effect on debt runs partly through the insurance/incentive channel rather than just borrowing need. The annual flow of newly delinquent debt rose from about $200 million (1985) to $5.5 billion (2015) in the benchmark (Figure D9). The number of borrowers and average debt per borrower both rose (borrowers from 8% of population in 2004 to 14% in 2014; average debt per borrower from $15,106 to $21,677). The model abstracts from endogenous dropout during college (no idiosyncratic risk in college) and from graduate loans, focusing on undergraduate debt as the largest component.