Essays on Housing Supply, Affordability, and Policy Incentives: Causal and Quantitative Approaches to Modeling Housing Market Dynamics and Policy Evaluation

Abstract

This dissertation advances the economic understanding of a dual challenge confronting policymakers in many cities with high rent burdens: housing affordability and supply constraints. It provides empirical evidence on the effectiveness of housing policies in addressing these challenges through a combination of descriptive analyses and causal inference methods that exploit spatial and temporal variation in housing and related data. The empirical analyses employ advanced difference-in-differences research designs developed in recent econometric literature. Complementing the empirical work, the dissertation develops a quantitative urban model of affordable housing, augmented with simulation exercises, to examine how such policies redistribute households, housing development, and prices across space, and to evaluate the welfare implications of these redistributions. Future work will structurally estimate this model using empirical data to assess the effectiveness of alternative affordable housing policies in expanding supply and improving affordability. The first chapter examines inclusionary zoning (IZ) policies—an increasingly common tool in many cities that use subsidies and tax exemptions to incentivize the inclusion of income-restricted units in market-rate developments. Focusing on a long-running IZ program in Seattle, we study how such policies shape the spatial distribution of new housing and affect neighborhood outcomes. Although program requirements are uniform, variation in local market conditions generates heterogeneous responses from developers and landlords. Leveraging policy changes over time and detailed rental microdata, we identify a key trade-off: in higher-income neighborhoods, rent discounts for subsidized units are larger, but developer participation is more sensitive to reductions in policy generosity. IZ also lowers nearby rents in lower-income areas but raises them in higher-income areas, consistent with direct competition in the former and building-induced neighborhood changes in the latter. The second chapter develops a quantitative spatial equilibrium model of an urban housing market that allows for features uncovered in the first chapter. The model includes heterogeneous households and profit-maximizing developers to evaluate the general equilibrium effects of an inclusionary zoning policy. The model extends Ahlfeldt, Redding, Sturm, and Wolf (2015) by explicitly modeling developers’ building and participation decisions under endogenous amenities and heterogeneous housing quality. Developers choose whether to construct market-rate or MFTE housing and determine building intensity based on local market rents and program parameters. On the demand side, high- and low-skilled households select residential locations based on wages, amenities, and rents, with low-skilled households eligible for rationed MFTE units. Amenities evolve endogenously with neighborhood housing stock, generating feedback between development and residential demand. The model is closed with equilibrium conditions that ensure market clearing in market-rate housing, rationing in MFTE housing, and dynamic consistency in housing stock evolution. Simulations illustrate how the MFTE program can influence developer entry, clustering of new construction, and access to high-amenity locations for lower-income households, thereby providing a framework to quantify the welfare and spatial redistribution effects of affordable housing policy. The third chapter examines a growing source of pressure on rental housing supply in recent decades: the expansion of investment properties used for short-term vacation rentals. I exploit the economic shocks of the COVID-19 pandemic as a natural experiment to study how property owners reallocated investment homes between short-term rental (STR) markets, such as Airbnb, and long-term rental (LTR) markets. Before the pandemic, many homeowners increasingly used Airbnb to rent investment properties to tourists rather than residents, raising concerns about the platform’s impact on housing affordability in supply-constrained markets. Using a continuous difference-in-differences design, I estimate that a 1 percentage point (pp) greater exposure to pre-pandemic tourism demand led to a 1.2–2.1 pp decline in Airbnb listings on average. I also provide evidence that Airbnb hosts shifted to LTR markets, as reflected in short-run increases in LTR rents during 2020. The effects were strongest among owners of two- to three-bedroom properties in areas with higher ownership costs—such as mortgage payments and property taxes—suggesting possible heterogeneous responses driven by homeowner liquidity constraints or financial leverage.