Cost-benefit analyses of foreclosure typically ignore nonpecuniary costs to borrowers. Using random judge assignment for all foreclosure filings in Cook County, Illinois, from 2005 to 2012, we estimate the causal effects of foreclosure over 5–12 years for owners, renters, and landlords. Our IV addresses endogeneity arising from borrowers with greater private costs fighting foreclosure more aggressively. For owner-occupants, foreclosure causes reduced homeownership over a decade, financial fragility, moves to worse neighborhoods, and increased divorce. Landlords experience shorter-lived financial costs, but no non-financial impacts. Renters experience declines in neighborhood income. Our findings imply that foreclosure is far costlier than previously thought.

Did credit drive the 2000s housing cycle? The existing literature's findings range from credit having no effect to credit explaining most of the cycle. We show that these disparate results hinge on the extent to which landlords absorb credit-driven demand, which depends on the degree of housing market segmentation. We develop a model that nests cases between the extremes of no segmentation and perfect segmentation typically considered, estimate an elasticity that pins down the degree of segmentation, and use it to calibrate our model. We find that credit standards played an important role, explaining 32% to 53% of the boom.

With “2020 hindsight,” the 2000s housing cycle is not a boom-bust but a boom-bust-rebound. Using a spatial equilibrium regression in which house prices are determined by income, amenities, urbanization, and supply, we show that long-run city-level fundamentals predict not only 1997–2019 price and rent growth but also the amplitude of the boom-bust-rebound. This evidence motivates our model of a cycle rooted in fundamentals. Households learn about fundamentals by observing “dividends” but become over-optimistic in the boom due to diagnostic expectations. A bust ensues when beliefs start to correct, exacerbated by a price-foreclosure spiral that drives prices below their long-run level. The rebound follows as prices converge to a path commensurate with higher fundamental growth. The estimated model explains the boom-bust-rebound with a single shock and accounts quantitatively for the dynamics of prices, rents, and foreclosures in cities with the largest cycles.

We introduce and quantify a new channel through which the housing market affects household spending: the home purchase channel. Households spend on average $8,000 more on home-related durables and home improvements in the two years following a home purchase. Expenditures on nondurables and durables unrelated to the home remain unchanged or decrease modestly. The home purchase channel played a substantial role in the Great Recession, accounting for one-third of the decline in spending on home-related durables and home improvements from 2005 to 2010.

Recent empirical work uses variation across cities or regions to identify the effects of economic shocks of interest to macroeconomists. The interpretation of such estimates is complicated by the fact that they reflect both partial equilibrium and local general equilibrium effects of the shocks. We propose an approach for recovering estimates of partial equilibrium effects from these cross-regional empirical estimates. The basic idea is to divide the cross-regional estimate by an estimate of the local fiscal multiplier, which measures the strength of local general equilibrium amplification. We apply this approach to recent estimates of housing wealth effects based on city-level variation, and derive conditions under which the adjustment is exact. We then evaluate its accuracy in a richer general equilibrium model of consumption and housing.

We provide new time-varying estimates of the housing wealth effect back to the 1980s. We use three identification strategies: OLS with a rich set of controls, the Saiz housing supply elasticity instrument, and a new instrument that exploits systematic differences in city-level exposure to regional house price cycles. All three identification strategies indicate that housing wealth elasticities were if anything slightly smaller in the 2000s than in earlier time periods. This implies that the important role housing played in the boom and bust of the 2000s was due to larger price movements rather than an increase in the sensitivity of consumption to house prices. Full-sample estimates based on our new instrument are smaller than recent estimates, though they remain economically important. We find no significant evidence of a boom-bust asymmetry in the housing wealth elasticity.

How can mortgages be redesigned to reduce housing market volatility, consumption volatility, and default? How does mortgage design interact with monetary policy? We address these questions using a quantitative equilibrium life-cycle model with aggregate shocks, long-term mortgages, and an equilibrium housing market, focusing on designs that index payments to monetary policy. Designs that raise mortgage payments in booms and lower them in recessions do better than designs with fixed mortgage payments. The benefits are quantitatively substantial: in a simulated crisis under a monetary regime in which the central bank lowers real interest rates in a bust, house prices fall 2.24 percentage points less, 23 percent fewer households default, and consumption falls by 0.79 percentage points less with ARMs relative to FRMs.

This paper uses a structural model to show that foreclosures played a crucial role in exacerbating the recent housing bust and to analyze foreclosure mitigation policy. We consider a dynamic search model in which foreclosures freeze the market for non-foreclosures and reduce price and sales volume by eroding lender equity, destroying the credit of potential buyers, and making buyers more selective. These effects cause price-default spirals that amplify an initial shock and help the model fit both national and cross-sectional moments better than a model without foreclosure. When calibrated to the recent bust, the model reveals that the amplification generated by foreclosures is significant: Ruined credit and choosey buyers account for 25.4 percent of the total decline in non-distressed prices and lender losses account for an additional 22.6 percent.

House prices exhibit substantially more momentum, positive autocorrelation in price changes over two to three years, than existing theories can explain. This paper introduces, empirically grounds, and quantitatively analyzes an amplification mechanism for momentum that can reconcile theory with the data. Sellers have an incentive not to set a unilaterally high or low list price because the demand curve they face is concave in relative price: increasing the list price of an above-average-priced house rapidly reduces its probability of sale, while cutting the price of a below-average-priced home reduces revenue but only slightly improves its chance of selling. The resulting strategic complementarity amplifies frictions that generate sluggish price adjustment because sellers adjust their price gradually to stay near the average. New micro-empirical evidence shows that the demand curve faced by sellers is concave, and a search model calibrated to the micro evidence shows that concave demand amplifies momentum by a factor of two to three.

This paper develops a dynamic Heckscher–Ohlin–Samuelson model with sector-specific human capital and overlapping generations to characterize the dynamics and welfare implications of gradual labor market adjustment to trade. Existing generations that have accumulated specific human capital in one sector can switch sectors when the economy is hit by a trade shock. Nonetheless, the shock induces few workers to switch, generating a protracted adjustment that operates largely through the entry of new generations. This results in wages being tied to the sector of employment in the short run but to the skill type in the long run. Relative to a world with general human capital, welfare is improved for the skill group whose type-intensive sector shrinks.

Macroeconomic calibrations imply much larger labor supply elasticities than microeconometric studies. One prominent explanation for this divergence is that indivisible labor generates extensive margin responses that are not captured in micro studies of hours choices. We evaluate whether existing calibrations of macro models are consistent with micro evidence on extensive margin responses using two approaches. First, we use a standard calibrated macro model to simulate the impacts of tax policy changes on labor supply. Second, we present a meta-analysis of quasi-experimental estimates of extensive margin elasticities. We find that micro estimates are consistent with macro evidence on the steady-state (Hicksian) elasticities relevant for cross-country comparisons. However, micro estimates of extensive-margin elasticities are an order of magnitude smaller than the values needed to explain business cycle fluctuations in aggregate hours.