Research

Many studies use difference-in-differences to identify the impact of an event occurring at a location in space on house prices. I formalize this setting in a potential outcomes model where the treatment intensity is a continuous function of distance to the treatment site. This framework reveals that standard difference-in-differences approaches require a treatment effect homogeneity assumption to recover the price derivative with respect to distance. In the hedonic model, this derivative is what recovers homeowner marginal willingness to pay and so the parameter estimated by difference-in-differences does not have a clear welfare interpretation under treatment effect heterogeneity. I introduce an alternative assumption. Instead of requiring homogeneous effects, I assume effects are concave in distance from the treatment site, reflecting an underlying intuition of spatial decay in many applications. I use this restriction to derive bounds on a treatment event’s welfare impact. I find in two applications, polluting industrial plants and low income housing developments, that the estimated bounds are tight.

We investigate the effects of sewer access on neighborhood characteristics in developing world cities. Because it is more difficult to move sewage uphill than downhill, otherwise similar neighborhoods on opposite sides of drainage basin divides may face different costs of sewer access. We exploit this intuition to identify the effect of sewer access by comparing outcomes for neighborhoods on opposite sides of drainage basin divides. We estimate the effect of sewer access on census tract population density, literacy, and income for Brazil, Colombia, South Africa, Jordan, and Tanzania. On average, sewer access has a large effect on population density and almost none on demographics. These estimates imply that sewer networks are often as important for the economic geography of cities as transportation networks.

We characterize the distribution of suburban homeowners’ preferences for housing unit density. To measure welfare changes under counterfactual increases in density, we first construct a novel house-level measure of exposure to density and identify its price effects in a boundary discontinuity design. On the borders of municipalities with larger minimum lot sizes, lots are 3,000sqft larger and houses are 40,000 costlier. We exploit the systematic variation in density exposure induced by these discontinuities to estimate price effects. We then connect these estimates to a structural hedonic model of housing choice to retrieve individuals’ preferences for density. Overall, we find an average welfare loss among incumbent homeowners from a 1/2 unit per acre increase in density (which is equivalent to a 0.3 standard deviation in density) of about 9,500, with significantly larger losses under counterfactual increases solely from rental units. There is other noteworthy heterogeneity in these preferences, too. Most households have only a moderate preference over density. The median welfare loss is only 55% of the average, implying a long, left tail of those with more extreme aversions to density. This tail disproportionately contains households in affluent, low density neighborhoods. In sum, our results document an important foundation of the demand for density regulation across U.S. suburbs that we hope serves as a valuable input into future research into the considerable costs of that policy.

We estimate the impact of more stringent minimum lot size restrictions across small border areas of neighboring communities using data from the Wharton Residential Land Use Regulatory Index (WRLURI) surveys. Economically meaningful effects are found on the built environment, not just house prices. Within 100 meters of the borders, housing density as reflected in the number of single family homes per acre is about 11% lower on average in the most restricted communities compared to the least restricted communities in terms of minimum lot sizes. Individual homes are bigger by about 80 square feet, an amount equal to about 4% of typical unit square footage. Lots are over 3,000 square feet larger in the most restricted compared to the least restricted communities’ border areas, an increase equal to 28% of the sample mean lot size. Hence, among the smaller number of homes that exist in the most regulated places, their physical structures are modestly bigger and they sit on appreciably larger lots. Finally, house prices are nearly $30,000 higher in the more regulated border areas compared to the least regulated border areas. This price impact can be accounted for by differences in house quality, structure and lot size specifically, on the two sides of a border.