Jaehee Song

Many safety-net programs deliver in-kind benefits through private providers, and program design determines who participates and at what price. We study landlord participation and pricing decisions in the U.S. Housing Choice Voucher program, linking voucher administrative data to national rental listings and to a new panel of the program’s price ceilings. We show that landlords are more likely to participate and to explicitly target voucher holders in high-poverty neighborhoods and that they adjust rents substantially toward the program’s ceiling between listing and contract. We estimate a model of landlord participation and pricing. Counterfactuals show that targeting higher price ceilings to low-poverty neighborhoods shifts voucher holders toward them more cost-effectively than uniform increases or sign-up bonuses, while stricter rent review can finance such increases without raising program spending.

When startups innovate, does the surrounding area prosper? Exploiting quasi-random assignment of patent examiners with varying leniency, we show that patent grants to startups increase nearby annualized real estate returns by 0.4 to 0.6 percentage points for residential properties and 0.5 to 0.9 percentage points for commercial properties and vacant land. Effects are largest for the first successful startup in an area and decline with additional successes. We also find that patent-granted startups spur nearby patenting, establishments, and jobs. Yet these real effects emerge only over the following decade, while real estate return premia appear immediately.

The Housing Choice Voucher program provides substantial rental subsidies to low-income households, yet many recipients struggle to secure housing with their vouchers, particularly in low-poverty areas. This paper examines a key bottleneck in the program: landlord discrimination against voucher holders. Using a nationwide dataset from a major online rental platform, we identify listings that explicitly seek or reject voucher holders. We find significant variation across metropolitan areas, with voucher-seeking listings ranging from nearly zero to 18 percent and voucher-rejecting listings ranging from nearly zero to 28 percent. Within metros, landlords in high-poverty neighborhoods with larger Black and voucher populations are more likely to seek voucher holders, while rejection of voucher holders is relatively more common in low-poverty neighborhoods. Using a difference-in-differences design around the introduction of a statewide source-of-income law in Hawaii, we find that the law reduced explicit rejection of vouchers by two-thirds. This reduction is particularly pronounced in low-poverty neighborhoods and can eliminate cross-neighborhood disparities in discriminatory behavior.

Zoning datasets rarely combine fine spatial resolution, national coverage, and temporal variation. I construct a national minimum lot size panel by detecting notches in lot-size distributions using tax assessor records for 92 million single-family and small multifamily parcels. I estimate neighborhood-level minimum lot sizes across construction cohorts from 1916 to 2025 and allow multiple minimum lot sizes within the same area and period. The estimates closely reproduce statutory minimums where regulations bind. The parcel-weighted median tract has an estimated minimum of 7,800 square feet. Minimum lot size is positively related to existing density restrictions and a lower multifamily share, but negatively related to broader regulatory stringency. I release the estimates for 76,770 Census tracts and corresponding metropolitan areas.

Housing supply is shaped by land availability, construction costs, regulations, and administrative barriers. Using parcel, zoning, and construction cost data for Greater Boston, I examine how these constraints jointly shape single-family development. I develop a discrete-choice model where landowners choose whether and what to build and estimate that implicit development costs beyond formal zoning add $117,000 per project at the median, plus $45,000 for nonconforming development. Counterfactuals show that reducing the per-project development cost by $50,000 raises supply by 73–79% and removing minimum lot size requirements raises supply by about 27%. Individually these reforms lower prices by 1% or less, but combined they raise supply by 130–140% and lower prices by about 2–4%, indicating that the largest affordability gains come from relaxing multiple constraints together rather than any one in isolation.

Economists estimate that zoning regulations raise house prices, lower productivity, and reduce aggregate welfare, yet regulations remain widespread. We develop and solve a model in which fragmented zoning authority leads to overly strict regulations: homeowners impose stricter regulations to mitigate local congestion but fail to internalize the broader impact on metro-wide affordability. Empirically, the Herfindahl–Hirschman index of local governments explains 12 percent of the variation in zoning restrictiveness. Using an instrument based on 19th-century municipal fragmentation, we show that greater fragmentation leads to stricter zoning and higher housing costs. These findings suggest that centralizing zoning decisions could alleviate housing affordability challenges.

I construct a new nationwide dataset to measure the stringency of residential zoning in the United States and examine its effects on housing production, prices, and demographic sorting. First, I develop and implement a structural break detection algorithm to infer minimum lot size regulations. The dataset spans over 16,000 local jurisdictions within Core-Based Statistical Areas, capturing both cross-jurisdictional and within-jurisdictional variation in zoning stringency. I find that 18.5 percent of single-family home constructions bunch at the minimum lot size threshold, suggesting that these zoning requirements are binding for a substantial share of single-family development. Second, I estimate the effects of these regulations on housing market outcomes, exploiting variation across nearby zoning districts within municipal border regions. The results show that minimum lot size regulations increase home sizes, sales prices, and rents. Moreover, restrictive zoning disproportionately attracts high-income white homeowners, reinforcing patterns of residential segregation.