How do economic forces affect the real estate market
Estimated to be worth more than 225 trillion USD in 2019, real estate is the world’s largest investment class (Savills 2019). Yet, even within the same country, housing wealth is largely unequally distributed across space. Cities and high-amenity places typically account for the lion’s share of it. This unequal distribution results from tension forces between the demand and supply side of the real estate market operating at the local level.
On the demand side, perhaps the most crucial factor is the decision of households about where to live and work according to a variety of subjective and economic factors. Naturally, the demand for real estate concentrates in high-amenity areas. These areas are typically more productive and feature desirable characteristics such as natural amenities and proper public good provision. Unfortunately, the desire of households to increase their utility by sorting into these high-amenity areas, is not always met with a likewise propensity to supply housing in these areas. On the contrary, in many high demand areas, the supply side of the market has failed to keep up with the demand side. This has lead to skyrocketing prices and affordability issues. In that regard, the observed unequal value of real estate across space is the result of a congestion force that drives people away from more productive areas, thus imposing a burden on the whole society.
A legitimate question is whether we can escape, or at least lessen, the congestion force coming from real estate markets. Many governments have tried to do so by implementing a variety of housing policies acting on both the demand and supply side of the market. Unfortunately, these policies usually neglect the local nature of the real estate and economic incentives driving the market. This has lead to unintended consequences. To understand these consequences, this thesis investigates the endogenous response of economic fundamentals in a spatial framework that accounts for the localized nature of housing demand and supply.
Specifically, I employ either a theoretical structural approach featuring local areas or an empirical approach using fine-scale housing data to investigate housing supply elasticities, housing subsidies, redevelopment option value, and regulation at the local level.
In Chapter 1, co-authored with Maximilian von Ehrlich and Olivier Schöni, we provide empirical evidence that increases in the periodic costs of housing lead to a larger supply response than price increases of the same percentage value. We rationalize this differential in supply responsiveness with an amplication mechanism arising from adjustments of capitalization rates to changes in the periodic costs. We document that the amplification of the housing supply price elasticity is less pronounced in geographically constrained and tightly regulated neighborhoods and areas having more sophisticated buyers. Our findings hold valuable lessons for public policies affecting the periodic cost of housing, such as rent control and housing subsidies.
In Chapter 2, co-authored with Yashar Blouri and Olivier Schöni, we analyze such a public policy. Specifically, we investigate the spatially heterogeneous impact of the U.S. federal mortgage interest deduction (MID) on the location and tenure decisions of households. We develop a general equilibrium model at the county level featuring an endogenous itemization of housing subsidies. Despite being a vital tax expenditure, repealing the MID would only slightly lower homeownership rates while leaving welfare mostly unchanged. The policy is ineffective because it targets locations with congested housing markets, creating a spatial shift of the housing demand toward areas that capitalize the subsidy into higher prices. We provide evidence that a repeal of the MID is to be preferred to an increase of standard tax deductions as recently implemented under President Trump’s administration.
In Chapter 3, co-authored with Alex van de Minne, we analyze the impact of the redevelopment potential on commercial real estate transaction prices. First, using a probit model, we compute the fitted redevelopment potential. This potential is primarily determined by the difference in net operating income (NOI) per square foot of land (sql) to the potential highest and best use (HBU) of the property. This difference reflects the economic obsolescence of a property. Second, we run a 2SLS model with the fitted redevelopment potential as an instrument for the redevelopment dummy. We find that having a 100 percent redevelopment potential increases the property’s price by nine to 17 percent.
In Chapter 4, I develop a methodology and the corresponding survey to construct a land-use regulation index for over 2200 Swiss municipalities. This index documents how regulation of residential buildings varies across space. It is composed of ten sub-indices that capture the different aspects and degrees of local regulation. To develop these indices, I suggest using land-use regulation data and complementing it with answers from a comprehensive survey. These indices provide harmonized information about what local regulation entails and the local regulatory environment across municipalities