Overseeing Infill

Abstract

AbstractProblem, research strategy, and findings Several U.S. states with high housing costs have recently adopted laws intended to promote infill development. These new laws expand state agencies’ supervisory responsibilities to ensure that local governments comply with state mandates. Effective administration of these laws will require state agencies to accurately estimate the amount of new housing that might be created and to target review to the jurisdictions that are failing to meet the relevant requirements. Here we present quantitative tools both for prioritizing review of local plans and zoning ordinances and for estimating future housing development. We applied the tools to the implementation of California laws requiring local governments to amend their zoning ordinances to allow accessory dwelling units on parcels zoned for detached single-family housing development. We provide computer code, written in the open-source statistical computing language R, that implements these tools. Although we present off-the-shelf tools, our proposed tools should supplement other regulatory techniques rather than serving as a substitute.Takeaway for practice Requirements for local governments to allow infill development should be accompanied by mandates for data collection. With good data, state agencies can use open-source statistical software to create quantitative measures that can help estimate future housing production and set priorities for reviewing local plans and zoning ordinances.Keywords: housinginfill developmentland use planningregulationzoning Supplemental MaterialSupplemental data for this article can be found on the publisher’s website. Replication code is available at https://doi.org/10.7910/DVN/LNJ5X3Notes1 This follows from two provisions of state law. First, regional housing need is subdivided into different levels of affordability, with “housing for lower income households” defined as housing that is affordable to households earning up to 80% of the area median income (California Government Code, sec. 65584(f), Citation2023; California Health and Safety Code, sec. 50079.5, Citation2023). Such households typically comprise about 40% of the total (see, e.g., California HCD, Citation2020a, Attachment 1; Citation2020b, Attachment 1). Second, the sites through which cities accommodate their “lower income” housing target must be zoned at densities that allow for multifamily housing (California Government Code, sec. 65583.2, Citation2023).2 In 2023, Montana also adopted laws enhancing planning requirements and requiring certain jurisdictions to allow duplexes in areas zoned for single-family development, but these laws do not require state administrative review of local ordinances (State of Montana, Citation2023a, Citation2023b).3 If an Oregon city fails to adopt a compliant, state-certified missing-middle zoning ordinance, it eventually becomes subject to a default state-promulgated missing-middle code (Oregon House Bill 2001, Citation2019, sec. 3).4 Although there are 88 cities in Los Angeles County, our sample included only 85. Two cities, Industry and Vernon, had no single-family zoning, and we were unable to match building footprint data for Avalon, the only incorporated area on the otherwise largely uninhabited Santa Catalina Island.5 It is also possible that our results could reflect unobserved parcel- or tract-level characteristics that affect ADU production and that are more common in some cities than in others.Additional informationFundingThis work was supported by Furman Center for Real Estate and Urban Policy, New York University, and the Pew Charitable Trusts. Notes on contributorsNicholas J. MarantzNICHOLAS J. MARANTZ (nmarantz@uci.edu) is an associate professor of urban planning and public policy at the University of California, Irvine (UCI).Christopher S. ElmendorfCHRISTOPHER S. ELMENDORF (cselmendorf@ucdavis.edu) is a professor of law at the University of California, Davis.Youjin B. KimYOUJIN B. KIM (youjinbk@uci.edu) is a PhD student at UCI.