Local Effects of Large New Apartment Buildings in Low-Income Areas

Abstract

We study the local effects of new market-rate housing in low-income areas using microdata on large apartment buildings, rents, and migration. New buildings decrease rents in nearby units by about 6 percent relative to units slightly farther away or near sites developed later, and they increase in-migration from lowincome areas. We show that new buildings absorb many high-income households and increase the local housing stock substantially. If buildings improve nearby amenities, the effect is not large enough to increase rents. Amenity improvements could be limited because most buildings go into already-changing neighborhoods, or buildings could create disamenities such as congestion.

How to Increase Housing Affordability? Understanding Local Deterrents to Building Multifamily Housing

“…Given that there is also an option value for single-family homes, which increases the price when regulations are relaxed, we conclude that the difference in unit characteristics (Effect C) outweigh the equilibrium effect (Effect A) and the option value (Effect B). This is in line with the recent literature (Pennington, 2021;Asquith et al, 2021). Viewed through the lens of our theoretical framework, the fact that house prices fall more than rents despite the opposing option value for single-family homes suggests that the effects from the change in house characteristics is larger for singlefamily homes than apartments when DUPAC is relaxed.…”

Residential Integration on Fair Terms for the Disadvantaged

“…While research into advantaged relocation is still developing, there is emerging evidence from North America and the UK that these features are reasonably common. On Point 2, advantaged relocation often has little effect on the out-migration rate of disadvantaged individuals or in terms of raising their rents (Asquith, Mast and Reed 2021; Ding, Hwang and Divringi 2016; Dragen, Ellen and Glied 2019; Freeman, Cassola and Cai 2016; McKinnish, Walsh and White 2010). This is largely due to one way in which it often differs from the description of gentrification outlined earlier.…”

Small-area estimates from consumer trace data

“…Having the flexibility to deviate from these boundaries would allow researchers and planners to understand population dynamics in continuous space (e.g., to align with flood zones, forest fire spread) or in isolated areas (e.g., in response to building demolition). Temporally and spatially precise demographic data have extensive application potential: examining the link between new construction and a range of outcomes from health to economic mobility (Li 2021;Asquith et al 2021;Damiano and Frenier 2020;Pennington 2020), the relationship between transit investments and surrounding population change (Boarnet et al 2018), or the impact of zoning changes on population composition (Freemark 2020). In addition, high frequency, spatially precise population data can be used as denominators for temporally variant event rates, such as with criminal activity or disease contagion (though the use of mixed numerators and denominators can create major complications; see, e.g., Lopez-Vizcaıno, Lombardıa, and Morales 2013).…”