Essays in Housing Economics

Abstract

Political debate around land use in cities often proceeds from the counterintuitive premise that housing development reduces affordability. In my first chapter I show that in Boston, the decision to approve a multifamily residential development causes a spillover effect: multifamily buildings within an 0.1-mile radius of the approval appreciate by 10% compared to control sales before and slightly further from the approval. My results suggest a real tradeoff in affordable housing policy between the marketwide benefits of increasing supply and the possibility of local displacement. Given the influence of project abutters on the approval process in many US cities, place-based policy targeting to compensate current residents who may be negatively affected by development could be Pareto-improving. In my second chapter, I compile a novel dataset providing information on the incidence and location of residential eviction filings in Boston. I show that eviction is associated with low household income at the block group level, but not with levels of nor changes in housing cost. I find that a habitability complaint to the city predicts an approximately doubled probability of an eviction at the same address within the same week. I find suggestive evidence of complaints causing evictions using weather-induced variation in complaints, but future work should seek out better exogenous shocks to habitability or eviction filings. Finally, we ask how computer vision techniques can help answer two sets of real estate-related questions: does appearance impact price, and do incentive-related events, like foreclosure, impact the maintenance and appearance of a home. We find that a one standard deviation improvement in the appearance of a home in Boston is associated with a .16 log point increase in the home's value, or about $55,000 at the sample mean. The additional predictive power created by images is modest relative to location and basic home variables, but external images do outperform variables collected by in-person home assessors. There are spillovers from appearance: a home's value increases by 0.7 log points when its neighbor's visually predicted value increases by one log point. The price impact of easily visible neighbors is larger than the impact of less visible neighbors. We find that homes that experienced foreclosure during the 2008-09 financial crisis experienced a .04 log point decline in their appearance-related value, as predicted by appearance, suggesting that foreclosure reduced maintenance incentives. We do not find more depreciation of appearance in rental properties, or more upgrading of appearance by owners before resale.