Low value and hard to stack

Opportunity zones and the low-income housing tax credit

Bibliographic Data

ID6439271
AuthorsMichael Snidal (0000-0003-2114-2764, Columbia University, corresponding author), Tyler Haupert (0000-0003-3132-6540, New York University Shanghai), Guanglai Li (0000-0002-0383-0611)
Year2023
Volume47
Issue5
Pages1759-1775
Publication date2023-09-11
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Urban Affairs (JOURNAL)
Journal identifiersISSN: 0735-2166 • E-ISSN: 1467-9906
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/07352166.2023.2245076
OpenAlexW4386601303
LanguageEN
Citations received1
References cited23

Established in 2017, Opportunity Zones (OZs) promised to spur investment in undercapitalized communities. Early evaluations find that OZs have had nominal effects on employment and real estate outcomes. Distressed community development, however, has historically been driven by affordable housing production. Conceptually, developers can stack OZs with the Low-Income Housing Tax Credit (LIHTC), the nation’s largest program for affordable housing. Therefore, this study seeks to estimate whether OZs have increased affordable housing production. First, we scan press announcements and OZ-tracking websites through July 2022 to document evidence of OZ-financed affordable housing. Second, we use a difference-in-differences approach to compare LIHTC outcomes through 2018 in OZs with areas that were OZ-eligible but not designated. We find only 60 examples of OZs supporting affordable housing projects across the country. We also find that OZs do not have statistically significant effects on LIHTC outcomes. We document findings from 16 interviews conducted in 2019 and 2020 to contextualize why OZs are failing to stimulate affordable housing production. In conclusion, we discuss how OZs could be modified to better encourage affordable housing, but we also reflect on whether such modifications would be desirable for goals of efficiency and distressed community development.KEYWORDS: Affordable housingeconomic developmenttax policy AcknowledgmentsThe first author thanks Lance Freeman, Weiping Wu, Malo Hutson, Ingrid Gould Ellen, Darrick Hamilton, and Sandra Newman for their thoughtful feedback on this research.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. The federal Low-Income Housing Tax Credit (LIHTC) program was established under the Tax Reform Act of 1986 and is the primary public subsidy for affordable housing development in the United States. LIHTC provides an incentive for taxable entities to invest equity in rental properties in which units are reserved for households making 60% or less of the area median income. Since its inception, the program has facilitated the development, rehabilitation, and preservation of over 3 million affordable housing units—the majority of national construction and preservation of affordable housing development—and roughly one third of multifamily housing development. See U.S. Department of Housing and Urban Development (Citation2022) and Joint Center for Housing Studies (Citation2022).2. This analysis was conducted by, and this spreadsheet is available upon request to, the first author.3. Defined by the U.S. Office of Management and Budget, CBSAs consist of one or more counties anchored by an urban center of at least 10,000 people plus adjacent counties that are socioeconomically integrated with the urban center by commuting ties.4. For a check on the sample and robustness we take two additional steps. First, we rerun models with the data disaggregated by census region to ensure our nationwide sample does not mask heterogeneity and produce a Type II error. Census region is a common variable of interest for researchers using econometric methods to investigate regional variation in housing-related processes like mortgage lending (Faber, Citation2013; Haupert, Citation2019) and LIHTC production (Freedman & McGavock, Citation2015). This check supports the findings. Second, as partial 2019 LIHTC data was available at the time of manuscript submission, we also model with an extended sample through 2019, increasing the post intervention period. We test the dummy for both 2018 and 2019 and just 2019. While results incorporating 2019 data are preliminary, they also support the findings.5. Traditional depository banks invest in LIHTCs not only to reduce their future tax liability but also to meet Community Reinvestment Act requirements. They thus tend to be less sensitive to pricing than purely economic investors. See Amstadt (Citation2017) for additional discussion.6. Interviewees were deeply knowledgeable in how LIHTC works including the rules and regulations that govern the program. For a technical overview of the LIHTC program see Scally et al. (Citation2018).7. Specifically, during at least 90% of the time in which the QOF holds or leases tangible property, at least 70% of the use of that property must be in the OZ. Moreover, less than 5% of the average of the aggregate unadjusted bases of the property of such entity is attributable to nonqualified financial property.Additional informationNotes on contributorsMichael SnidalMichael Snidal, PhD, is the principal of Snidal Real Estate, a Baltimore based real estate and property management company. His work, research, and opinions have been featured in a host of academic and popular news sources including Cityscape, the Financial Times, Governing, Urban Studies, and the Washington Post.Tyler HaupertTyler Haupert is an assistant professor of urban studies at NYU Shanghai. His research focuses on the social, economic, technological, and regulatory mechanisms contributing to racial segregation and exclusion in advanced economies, with particular interests in mortgage lending, housing policy, neighborhood change, and homelessness. He strives to design studies that inform policy and produce actionable results for legislators, regulators, planners, and advocacy organizations.Guanglai LiGuanglai Li is a data scientist based in Providence, Rhode Island

Business · Demographic economics · Economics · Labour economics · Low income · Public economics · Stack (abstract data type · Tax credit · Value (mathematics · Housing Market and Economics · Urban, Neighborhood, and Segregation Studies

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