I study the short-run effect of new housing construction on housing affordability using individual address history data. Because most new construction is expensive, its effect on the market for more affordable housing is unclear, since these could be effectively separate submarkets. I first show that new construction and low-income neighborhoods are connected by a short series of common moves—individuals frequently move to a census tract two to four income deciles higher than their origin. I then identify residents of new luxury multifamily buildings in large central cities, their previous address, the current residents of those previous addresses, and so on for six rounds. This sequence of previous addresses steadily adds more diverse neighborhoods, suggesting strong connections between new construction and affordable neighborhoods. Lastly, I quantify these descriptive patterns with a simple simulation model. Building 100 new luxury units leads 65 and 34 people to move out of below-median and bottom-quintile income neighborhoods, respectively, reducing demand and loosening the housing market in such areas. These results suggest that increasing housing supply improves housing affordability in the short run.
A common worry about building housing in gentrifying neighborhoods is that new units will induce additional housing demand by improving nearby amenities or changing household composition, counterintuitively increasing local rents and fueling further gentrification. This line of thought leads to strong local opposition to many new housing developments, likely reducing regional housing supply. We empirically test this theory of induced demand using data on new apartment construction, address-level rental listings, and address-level household migration. Using various spatial differencing approaches, we find that any induced demand effects are overwhelmed by supply effects. The average new apartment building in a low-income census tract decreases listed rents within 250 meters by about $154 dollars per month relative to listings 250-600 meters away. This pattern does not appear in a set of placebo locations—the areas around the sites of future apartment construction. Similarly, we find no evidence that the number or demographic composition of migrants to pre-existing nearby buildings changes after the building's completion. These results suggest that limiting housing construction in an attempt to slow gentrification may be counterproductive.
Revisions requested at Regional Science and Urban Economics
Federal place-based policy could improve efficiency if it targets areas with large amenity or agglomeration externalities. We begin by showing that positive shocks to federal spending in a county and their associated economic stimulus substantially decrease crime, an important amenity. We then employ two machine learning algorithms—causal trees and causal forests—to conduct a data-driven search for heterogeneity in this effect. The effect is larger in below-median income counties, and the difference is economically and statistically significant. This heterogeneity likely improves the efficiency of the many place-based policies that target such areas.
Information frictions in markets for insurance affect not only the choices consumers make, but also the menu of plans insurers offer. We illustrate this observation using an information friction in Medicare Advantage — beneficiaries pay two premiums, and one is much more salient. We begin by estimating demand and finding a larger elasticity for the salient versus non-salient premium. Next, we show that a model of insurer plan design produces simulated premiums matching the observed distribution when accounting for differential salience, but not when assuming equal elasticities across the two premiums. Finally, we simulate how plan enrollment would change if the friction were removed. Consumer surplus increases by $73/year when allowing insurers to redesign their plans, versus only $5/year holding supply fixed.
American Economic Journal: Applied Economics, forthcoming