Regulation and Housing Supply

Gyourko, Joseph; Molloy, Raven

doi:10.1016/b978-0-444-59531-7.00019-3

Cited by 197 publications

(125 citation statements)

References 84 publications

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“…Increasing housing supply should therefore be an important part of any solution to the present affordability crisis. One way to do so is to relax regulations that make it difficult to build in many cities (Gyourko and Molloy 2015;Ganong and Shoag 2017;Glaeser and Gyourko 2018), and another is to directly incentivize localities to increase housing production. However, we note several caveats to our findings.…”

Section: Resultsmentioning

confidence: 99%

“…find that the introduction of condominiums did not increase central city income, education, or share white, which they attribute in part to the fact that most were built in areas that were already attractive to high-income households Freemark (2019). finds that increasing zoned capacity in Chicago raised the value of affected land but does not study the effect on rents.10 SeeGyourko and Molloy (2015) and Glaeser andGyourko (2018) for recent reviews.11 We restrict to the borough of Brooklyn when studying New York City because this is the only borough included in our data use agreement with Zillow ™ .…”

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confidence: 99%

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Supply Shock Versus Demand Shock: The Local Effects of New Housing in Low-Income Areas

2019

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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 nearby rents by 5 to 7 percent relative to locations slightly farther away or developed later, and they increase in-migration from low-income areas. Results are driven by a large supply effect-we show that new buildings absorb many high-income households-that overwhelms any offsetting endogenous amenity effect. The latter may be small because most new buildings go into already-changing areas. Contrary to common concerns, new buildings slow local rent increases rather than initiate or accelerate them. JEL Codes: R21, R23, R31 the regional and local effects of new housing construction. It benefits both.Causal identification in this setting is challenging because developers select the locations of new buildings based in part on unobserved local characteristics and trends. In addition, the size and shape of a new building's amenity or reputation effects is unknown, making it difficult to know where they may shrink or reverse the negative effect of added supply. We attempt to overcome these challenges by leveraging our unique data to construct three related empirical strategies. The first is a difference-in-differences specification that compares the area very close to a new building to the area slightly farther away (our "near-far" specification). 4 The idea is that frictions in the land assembly and development approval processes lead to random variation in building placement and timing at the hyper-local level, making the outer area a good control for the treated inner area. This specification is well suited to detect one way that new buildings could raise rents-through amenity effects that fade out quickly with distance, such as increased retail options or the replacement of a vacant lot.The second exercise is a difference-in-differences that compares listings near buildings completed in 2015 and 2016 to listings near buildings completed in 2019, after the conclusion of our sample (our "near-near" specification). The underlying logic is that developers choose sites in both groups for similar reasons, but one building is completed before the other for idiosyncratic reasons, such as the timing of when sites are available for purchase. Because the treatment and control areas are not necessarily in the same neighborhood, this specification can detect price changes driven by broader effects that may cross the near-far boundary of the first exercise. A variant of this specification also allows us to examine how congestion effects near the building could influence our results. Finally, we combine both sources of variation into a triple-difference specification that effectively compares the near-far difference around 2015-2016 buildings to the near-far difference around 2019 buildings.We first study the effect on rents using listing-level data from Zillow ™ that span 2013 to 2018. All three empirical approaches show that new construction in low-income neighbo...

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Supply Shock Versus Demand Shock: The Local Effects of New Housing in Low-Income Areas

2019

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“…33 See Diamond (2017) on housing supply and rent extraction, Saiz (2010) on geographical and regulatory restrictions and housing supply, Epple et al (2010) and Combes et al (2016) on estimating housing production functions, and Paciorek (2013) and Murphy (2018) on price and cost dynamics and housing supply. See also Gyourko and Molloy (2015) for a comprehensive review of the literature on regulation and housing supply. 34 In our three-county region, about 85% of all the new homes supplied during our study period were supplied within a residential subdivision development.…”

Section: Discussionmentioning

confidence: 99%

“…Understanding residential housing supply is important for explaining urban land use. It is also critical for designing effective policy (Nechyba and Walsh, 2004;Gyourko and Molloy, 2015;Glaeser and Gyourko, 2017). Property taxes and zoned-density restrictions, or minimum-lot zoning, are common tools for managing land use; their effect on urban land use has received considerable theoretical attention (Turnbull, 1988(Turnbull, , 1991Brueckner, 2000).…”

Section: Introductionmentioning

confidence: 99%

Space and Time: A Competing Risks Analysis of the Impact of Property Taxes and Zoning Restrictions on Residential Development

Wrenn

Klaiber

2019

Int Economic Review

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Property taxes and zoning restrictions are prevalent tools for managing land use. We combine microlevel data on residential subdivision development from the Baltimore, Maryland, metro area from 1994 to 2007 with a competing risks model to examine how both policies influence the density and timing of residential development. Consistent with theory, we demonstrate that the impact of both policies on optimal density and timing depends on whether density and time are substitutes or complements in the profit function. Our results have important implications as they provide key empirical insights into how property taxes and zoning interact to influence development patterns.

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“…The vast majority of studies on housing regulations find that increasing the strictness of building regulations increases housing prices by limiting the growth of housing supply (Gyourko and Molloy 2015). For example, in a study of Boston-area housing policies, Glaeser and Ward (2009) show that individual regulations can reduce the supply of housing by up to 22 percent.…”

Section: The Effect Of Land-use Regulation On House Pricesmentioning

confidence: 99%

Through the Roof: The High Cost of Barriers to Building New Housing in Canadian Municipalities

Dachis¹,

Thivierge

2018

SSRN Journal

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Regulation and Housing Supply

Cited by 197 publications

References 84 publications

Supply Shock Versus Demand Shock: The Local Effects of New Housing in Low-Income Areas

Supply Shock Versus Demand Shock: The Local Effects of New Housing in Low-Income Areas

Space and Time: A Competing Risks Analysis of the Impact of Property Taxes and Zoning Restrictions on Residential Development

Through the Roof: The High Cost of Barriers to Building New Housing in Canadian Municipalities

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