Wage garnishment allows creditors to deduct money from workers' paychecks to repay defaulted debts. We document new facts about wage garnishment between 2014 and 2019 using data from a large payroll processor that distributes paychecks to approximately 20 percent of US private-sector workers. By 2019, over 1 in every 100 workers was being garnished for delinquent debt. The average garnished worker experiences garnishment for five months, during which approximately 11 percent of gross earnings is remitted to their creditor(s). The beginning of a garnishment is associated with an increase in job turnover but no intensive margin change in hours worked.

Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric information in the market for online consumer credit. Building on methods from the insurance literature, we show how exogenous variation in interest rates can be used to estimate borrower demand and lender cost curves and recover implied welfare losses. While asymmetric information generates large equilibrium price distortions, we find only small overall welfare losses, particularly for high-credit-score borrowers.

Using data on 50 million home sales from the last U.S. housing cycle, we document that much of the variation in volume came from the rise and fall in speculation. Cities with larger speculative booms have larger price booms, sharper increases in unsold listings as the market turns, and more severe busts. We present a model in which predictable price increases endogenously attract short-term buyers more than longterm buyers. Short-term buyers amplify volume by selling faster and destabilize prices through positive feedback. Our model matches key aggregate patterns, including the lead-lag price-volume relation and a sharp rise in inventories.

We study how employment documentation requirements and out-of-pocket closing costs constrain mortgage refinancing. These frictions, which bind most severely during recessions, may significantly inhibit monetary policy pass-through. To study their effects on refinancing, we exploit an FHA policy change that excluded unemployed borrowers from refinancing and increased others’ out-of-pocket costs substantially. These changes dramatically reduced refinancing rates, particularly among the likely unemployed and those facing new out-of-pocket costs. Our results imply that unemployed and liquidity-constrained borrowers have a high latent demand for refinancing. Cyclical variation in these factors may therefore affect both the aggregate and distributional consequences of monetary policy.

This article studies how credit markets respond to policy constraints on household leverage. Exploiting a sharp policy-induced discontinuity in the cost of originating certain high-leverage mortgages, we study how the Dodd-Frank "Ability-to-Repay" rule affected the price and availability of credit in the U.S. mortgage market. Our estimates show that the policy had only moderate effects on prices, increasing interest rates on affected loans by 10-15 basis points. The effect on quantities, however, was significantly larger; we estimate that the policy eliminated 15 percent of the affected market completely and reduced leverage for another 20 percent of remaining borrowers. This reduction in quantities is much greater than would be implied by plausible demand elasticities and indicates that lenders responded to the policy not only by raising prices but also by exiting the regulated portion of the market. Heterogeneity in the quantity response across lenders suggests that agency costs may have been one particularly important market friction contributing to the large overall effect as the fall in lending was substantially larger among lenders relying on third parties to originate loans. Finally, while the policy succeeded in reducing leverage, our estimates suggest this effect would have only slightly reduced aggregate default rates during the housing crisis.

I empirically analyze how changes in access to housing collateral affect homeowner borrowing behavior. To isolate the role of collateral constraints from that of wealth effects, I exploit the fully-anticipated expiration of resale price controls on owner-occupied housing in Montgomery County, Maryland. I estimate a marginal propensity to borrow out of housing collateral that ranges between $0.04–$0.13 and is correlated with homeowners’ initial leverage. Additional analysis of residential investment and ex-post loan performance indicates that some of the extracted funds generated new expenditures. These results suggest a potentially important role for collateral constraints in driving household expenditures.

One of the striking features of the last U.S. housing boom was the heterogeneity in the timing of its onset across local markets. In this paper, we exploit this heterogeneity to estimate the extent to which the boom was spread via spatial spillovers from one market to another. Our analysis focuses on spillovers that occur around the time that a local market enters its boom, which we identify using sharp structural breaks in house price growth rates. On the extensive margin, there is evidence that the likelihood of a market booming increases substantially if nearby neighbors boom. On the intensive margin, we also find statistically significant but economically modest effects of the size of a neighbor’s boom on subsequent price growth in nearby markets. These affects appear to be unrelated to local market fundamentals, suggesting a potential role for non-rational factors.

This paper provides novel estimates of the interest rate elasticity of mortgage demand by measuring the degree of bunching in response to a discrete jump in interest rates at the conforming loan limit—the maximum loan size eligible for purchase by Fannie Mae and Freddie Mac. The estimates indicate that a 1 percentage point increase in the rate on a 30-year fixed-rate mortgage reduces first mortgage demand by between 2 and 3 percent. One-third of this response is driven by borrowers who take out second mortgages, which implies that total mortgage debt only declines by 1.5 to 2 percent.

We analyze and find empirical support for a model of strategic renegotiation in which firms scheduled to roll over debt during a crisis reduce operations to discourage lenders from seizing the collateral. Our empirical analysis exploits contractual features of commercial mortgages that generate exogenous variation in whether debt matures during a crisis. A crisis debt maturity causes large relative drops in output, labor, and profits at the collateral property, even holding the borrower fixed. Consistent with the model, these real effects decrease with the lender’s operating adjustment costs, reverse after renegotiation, and occur primarily for highly-levered loans without term-extension options.

The COVID-19 pandemic saw an unprecedented expansion of federal emergency rental assistance (ERA). Using applications to ERA lotteries in four cities linked to survey and administrative data, we assess its impacts on housing stability, financial security, and mental health. We find that assistance increased rent payment modestly and improved mental health. However, in contrast to pre-pandemic studies of similar assistance programs, we find limited effects on financial or housing stability. Several pieces of suggestive evidence indicate this discrepancy is likely due to macroeconomic conditions, including expanded government support and rental market slackness, rather than ERA generosity or targeting.