Housing & Urban Economics

Using a nationally representative panel of consumer credit records for the US from 1999 to 2021, we document a positive correlation between child and parent homeownership. We propose a new causal mechanism behind this relationship based on parents extracting home equity to help finance their child’s home purchase and quantify this mechanism in several ways. First, controlling for cohort, zip code, age, and the creditworthiness of parents and children, we find that children whose parents extract equity are 60% more likely to become a homeowner than children whose homeowner-parents do not extract equity. Second, using an event study approach, we find that the increase in child homeownership occurs almost entirely in the year when parents extract equity. Third, using variation in leverage constraints as an instrument for parents’ equity extraction, we find that parental equity extraction increases the probability of a child becoming a homeowner by about five times. Our results highlight the importance of familial wealth for household wealth accumulation and housing wealth in particular. A back-of-the-envelope calculations suggest that dynastic home equity increases housing wealth inequality among young adults by 15%.

Using transaction records on housing sales and leases, we estimate the effect of Toronto’s imposition of a transaction tax on properties in 2008. We find three novel effects of an increase in land transfer tax: (1) a rise in buy-to-rent transactions but a fall in owner-occupier transactions despite the tax applying to both, (2) a simultaneous fall in the price-to-rent ratio and the salesto-leases ratio; and (3) a decline in the moving hazard for existing homeowners and an increase in the time on the market it takes to sell. We develop a housing search model with an owning or renting choice and entry of investors. It accounts for the three new facts by predicting an increase in demand in the rental market which generates a fall in the homeownership rate and a reduction in mobility within the ownership market. The implied deadweight loss as a percentage of tax revenue raised is large at 79%, with nearly 40% due to the presence of the rental market.

The property tax is the most under-utilized tax in developing countries. We evaluate the revenue and welfare effects of the main policy instruments used to raise property tax revenue: tax rate changes and enforcement. Using administrative data from Mexico, sharp tax rate increases, and an enforcement experiment, we show that both policy instruments increase revenue. We then provide a conceptual framework to assess the welfare costs of these policies. The welfare cost of tax increases incorporates changes in compliance and consumption drops for compliant taxpayers. The welfare effect of enforcement includes the cost to non-compliant taxpayers from threats of fines and property seizure, a cost we infer using tax rate and enforcement elasticities. In Mexico, tax hikes raise welfare since revenue gains exceed losses from consumption drops. In contrast, enforcement reduces welfare as its costs overshadow the revenue gains. Welfare-maximizing governments would therefore prefer increasing tax rates over enhancing enforcement. 

What are the effects of commercial real estate regulations on output, welfare, and the spatial allocation of workers and business activity across the U.S.? To answer this question, we develop a dynamic, spatial, general equilibrium model that yields an intuitive formula for identifying the extent to which commercial real estate investment decisions are distorted by zoning codes and other regulations. We apply our theory to the near-universe of commercial property tax records from CoreLogic in order to develop a model-consistent index of commercial regulations. We validate our index of commercial real estate regulations by showing that among the cities for which zoning codes are reported in CoreLogic, our index of commercial regulations positively correlates with several salient facets of statutory zoning restrictions. We then use our estimated model to evaluate both national and local changes to commercial regulations. Moderately loosening commercial regulation across all U.S. cities yields welfare gains worth 0.9% to 2.8% of lifetime consumption, depending on the counterfactual. We also measure how moving specific commercial parcels “up” zoning code rungs – with higher rungs being less regulated– affects output and the spatial location of business activity. In New York City alone, we find that moving each commercial parcel “up” three zoning codes rungs yields large local output gains of 6.2%.

I examine the influence of the United States’ first comprehensive land-use regulations (‘‘zoning’’) and the growth of transportation infrastructure on segregation and intra-city migration in New York City from 1870 to 1940. Combining a new panel dataset derived from historical US federal population censuses with newly digitized real-estate sales transaction records, I find that between-neighborhood socioeconomic segregation increased dramatically after the building of transit infrastructure, that zoning was largely an endogenous response to the socioeconomic segregation facilitated by transit infrastructure and that the combination of zoning and building new subways in a rapidly expanding city produced a pattern where inner-city neighborhoods zoned for factories and multi-family dwellings ‘flipped’ to African American majorities. I estimate the value of a “tipping point’’ beyond which mixed-race neighborhoods are no longer sustainable and show that housing prices in tipped neighborhoods decrease by 40% relative to non-tipped neighborhoods. Finally, while white and African American migrants from the rural South to New York City benefit from urban wage premia of about 40%, this premium is reduced for African American migrants living in segregated minority neighborhoods.

We investigate how a large place-based policy, the HOPE VI Revitalization program, affected people and places. The program sought to benefit people living in high-poverty neighborhoods by transforming these places into mixed-income communities through the demolition of public housing projects and the construction of new housing. We find that the program led to a large decline in neighborhood poverty rates, driven by changes in who moved into the neighborhood after a Revitalization award. Within five years of an award most original residents had moved away and were not exposed to the changed neighborhoods. The program reduced the number of subsidized renters in targeted neighborhoods, but those able to find a unit after an award lived in lower poverty neighborhoods. We find no evidence to suggest that the program had large spillover effects on the poverty rates of other neighborhoods.

Flood events and flood risk have been increasing in the past few decades and have important consequences on the economy. Using county-level and ZIP-code-level data during 1998–2018 from the U.S., we document that (1) increased flood risk has large negative impacts on firm entry, employment and output in the long run; (2) flood events reduce output in the short run while their impact on firm entry and employment is limited. Motivated by these findings, we construct a spatial equilibrium model to characterize how flood risk shapes firms’ location choices and workers’ employment, which we use to estimate the aggregate impact of increased flood risk on the economy.We find that flood risk reduced U.S. aggregate output by 0.52 percent in 2018, 80% of which stemmed from expectation effects and 20% from direct damages. We also apply our model to studying the distributional consequences and forecasting the impact of future changes in flood risk. Our results highlight the importance of considering the adjustment of firms and workers in response to risk in evaluating the consequences of natural disasters

This paper considers how the spatial distribution of U.S. economic activity may be impacted by climate change in the decades ahead. First, we use recently developed daily weather data at the county level from 1951-2020 to construct annual measures of average and extreme precipitation and the number of days per year in various temperature bins. Second, we exploit the substantial geographic and temporal variation in these data to estimate the longer-run effects of weather on local population, employment, wages, and house prices. In contrast to prior studies inferring longer run effects from short-run effects, we estimate the full dynamic response of economic outcomes to weather shocks using panel autoregressive distributed lag (ADL) models covering 30 years of weather. This model accounts for both ex-post and ex-ante adaptation to the extent agents have adaptive expectations. Our historical results point to long-lasting effects of extreme temperature and precipitation on local employment and population. Lastly, we use the estimated models to project the spatial distribution of these local outcomes in 2050 using historical and projected county-level weather. We project substantial reallocations of people and jobs across the U.S.. In terms of direction, the results point to shifts away from the southeast and toward the mountain west. In terms of magnitude, we estimate climate change will increase population reallocation over the next three decades by as much as 55%.

We analyze the effect of working from home on the agglomeration economies of large cities and the aggregate productivity implications of such effect. Using advertised wages from job ads, we show that occupations with the highest work-from-home adoption during the COVID-19 pandemic saw a strong decrease in the urban wage premium. The decline in the urban wage premium is accompanied by an exodus of employment (based on firms’ locations) from large cities to small cities. In contrast, occupations with low or moderate levels of work-from-home adoption saw little overall reduction in the urban wage premium. The empirical evidence in our paper points to weakened agglomeration economies in large cities among professions with the highest prevalence of working from home. A decomposition exercise reveals that a sizable portion of the decline in the urban wage premium is driven by the decline in the urban wage premium of relationship-building skills, suggesting the decreased agglomeration effect in large cities is at least partially a result of reduced occurrence of interactive activities.

Information and communication technology (ICT) can widen firms’ geographic span of control by reducing internal communication costs. Combining comprehensive establishment-level datasets with ownership linkages, geographic locations, and ICT adoption, I document that firms with more advanced technology have both higher within-firm communication and larger geographic coverage. Exploiting natural experimental variation from the Internet privatization in the early 1990s, I show that better access to ICT helped firms expand geographically. Using a model where firms endogenously adopt ICT, choose multiple production locations, and trade domestically, I estimate that the Internet privatization increased overall efficiency by 1.1%. Compared to a trade-only model, a model with multi-unit firms predicts that efficiency gains are larger and more geographically dispersed. Policy counterfactuals show that to improve local welfare, a policy coordinated across locations that improves ICT access can be more effective than uncoordinated local policies.

We propose a model that can match gravity patterns of U.S. interstate migration based on persistent and spatially-correlated preferences. The model also matches many untargeted dynamic moments of migration, previously a challenge for the literature. From the model, we learn five lessons with implications for regional evolutions, migratory insurance, and macroeconomic misallocation: moving costs need not be large to generate gravity patterns; return migration patterns can be the result of persistent preferences; short-run elasticities of migration vary by distance; bilateral migration flows are informative of population elasticities to local shocks; and short- and long-run population elasticities are the same.

We quantify the roles of increasing returns and trade costs in medical services. Using data on millions of Medicare claims, we document that “imported” medical procedures— defined as a patient’s consumption of a service produced by a medical provider in a different region—constitute about one-fifth of US healthcare consumption. Larger markets specialize in the production of less common procedures, and these procedures are more traded between regions. These patterns reflect economies of scale: larger regions produce higher-quality care because they serve more patients. Revealed-preference estimates of quality, which are positively related to external measures of quality of care, have a scale elasticity around 0.7. We use these estimates to evaluate the proximity concentration tradeoff associated with various policy options for improving access to medical care.