We study the distributional consequences of student debt forgiveness in present value terms, accounting for differences in repayment behavior across the earnings distribution. Full or partial forgiveness is regressive because high earners took larger loans, but also because, for low earners, balances greatly overstate the benefits of debt cancellation. Consequently, forgiveness would benefit the top decile as much as the bottom three deciles combined. Enrolling households who would benefit from income-driven repayment is less expensive and distributes more funds to lower-income households.

We examine the rise in student loan defaults in the Great Recession by linking administrative student loan data at the individual borrower level to student loan borrowers’ individual tax records. A Blinder-Oaxaca style decomposition shows that shifts in the composition of student loan borrowers and the massive collapse in home prices during the Great Recession can each account for approximately 30% of the rise in student loan defaults. Falling home prices affect student loan defaults by impairing individuals’ labor earnings, especially for low income jobs. By contrast, when comparing the default sensitivities of homeowners and renters, we find no evidence that falling home prices affect student loan defaults through a home equity-based liquidity channel. The Income Based Repayment (IBR) program introduced by the federal government in the wake of the Great Recession reduced both student loan defaults and their sensitivity to home price fluctuations, thus providing student loan borrowers with valuable insurance against negative shocks.

We report evidence from a randomized field experiment conducted by a major student loan servicer, Navient, in which student loan borrowers received prepopulated applications for income‐driven repayment (IDR) plans. Treatment increased IDR enrollment by 34 percentage points relative to the control group. Using the random treatment assignment as an instrument for IDR enrollment, we furthermore provide local average treatment effect (LATE) estimates of the effects of IDR enrollment on new delinquencies, monthly student loan payments, and consumer spending. Our study is the first field‐experimental evaluation of a U.S. government program designed to address the soaring debt burdens of U.S. households.

We use staggered banking deregulation across states in the United States to examine the impact of the resulting increased credit supply on college enrollment from the 1970s to the early 1990s. Our research design produces estimates that are not confounded by wealth effects due to changes in income or housing wealth. We find that lifting banking restrictions raises college enrollment by about 2.6 percentage points (4.9%). We rule out alternative interpretations by examining results for different income groups and bankrupt households. We also find similar effects for two-year or four-year college completion and supporting evidence in household educational borrowing.

The federal government encourages human capital investment through lending and grant programs, but resources from these programs may also finance non-education activities for liquidity-constrained students. To explore this possibility, we use administrative data for federal student borrowers linked to tax records and a sharp discontinuity generated by the timing of a student's 24th birthday, which induces a jump in federal support. We estimate a corresponding increase in homeownership, with larger effects among those most financially constrained, and find supplemental evidence of lagged marriage and fertility effects. Analysis of earnings, savings, and heterogeneity favors liquidity over human capital in explaining the results.

The efficiency of federal lending guarantees depends on whether guarantees increase lending supply or simply act as a subsidy to lenders. We use notches in the guarantee rate schedule for Small Business Administration (SBA) loans to estimate the elasticity of bank lending volume to loan guarantees. We show significant bunching in the loan distribution on the side of the size threshold that carries a more generous loan guarantee. The excess mass implies that increasing guarantee generosity by one percentage point of loan principal would increase per-loan lending volume by $19,000. Excess mass increases in periods with guarantee generosity, and placebo results indicate that the effect disappears when the guarantee notch is eliminated.

This paper studies the link between credit availability and student loan repayment using administrative federal student loan data. We demonstrate that policy-driven changes in credit available to high-default institutions explain almost all of the historical time-series variation in defaults. Between 1981 and 1988, eligibility for federal loans was expanded, leading to the entry of institutions with borrowers more likely to default. From 1988 to 1992, credit access was tightened, leading to the exit of many institutions with high default rates. After 1992, the cycle was repeated, with credit access gradually loosened by unwinding many of the pre-1992 reforms.

Screening in consumer credit markets is often associated with large fixed costs. We present both theory and evidence that, when lenders use fixed-cost technologies to screen borrowers, increased competition may increase rather than decrease interest rates in subprime consumer credit markets. In more competitive markets, lenders have lower market shares, and thus lower incentives to invest in screening. Thus, when markets are competitive, all lenders face a riskier pool of borrowers, which can lead interest rates to be higher. We provide evidence for the model’s predictions in the auto loan market using administrative credit panel data.

This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China. We identify a strong discount rate channel driven exclusively by cycle-amplifying surprises, defined as rate cuts during easing cycles and surprise hikes during tightening cycles. A 100 basis point of such cycle-amplifying surprise induces a 30 basis point change in the price ratio within five days.