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 and $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.

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 a Federal Housing Administration 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% of the affected market completely and reduced leverage for another 20% 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.

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 long-term 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.

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.