Colburn, Gregg, and Rebecca J. Walter. Affordable Housing in the United States. Routledge, 2025.
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Abstract
Affordable Housing in the United States addresses the issue of affordability of housing, or the lack thereof, going beyond conventional policy discussions to consider fundamental questions such as: What makes housing affordable and for whom is it affordable? What are the consequences of a lack of affordable housing? How is affordable housing created? And what steps can be taken to ensure all people have access to affordable housing?
With the understanding that different households face different challenges, the book begins by breaking down the variables relevant to the study of affordable housing, including housing costs, household income, geographic location, and market forces, to help readers understand and quantify affordability at the individual and societal level. Part II examines the consequences of unaffordable housing, highlighting racial inequities in housing access and affordability, and multiple forms of housing precarity including eviction and homelessness. Part III explores the entities involved in providing affordable housing such as local and federal governments, regulatory agencies, non-profit organizations, and for-profit developers. In Part IV, case studies from US cities demonstrate the complex web of organizations, policies, and market conditions that influence housing affordability, revealing substantial regional variations in access and policy response. Part V proposes a future roadmap and outlines four potential states with radically different outcomes for the affordable housing system in the United States.
An ideal book for graduate and undergraduate courses in economics, public policy, real estate finance and development, sociology, and urban planning, this title will also be of value to professionals and policymakers seeking to understand and improve housing affordability and access.
Ruoniu (Vince) Wang, Wei Kang, Xinyu Fu, Do inclusionary zoning policies affect local housing markets? An empirical study in the United States, Cities, Volume 158, 2025, 105736, ISSN 0264-2751, https://doi.org/10.1016/j.cities.2025.105736.
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Abstract
In the face of a housing affordability crisis, many cities have adopted inclusionary zoning (IZ) policies to increase the supply of affordable housing. Yet, IZ remains a controversial local policy due to its varied and inconclusive effects on housing market outcomes. This study investigates this debate by adopting a quasi-experimental design with a national dataset of IZ policies in the United States. We find that, on average, IZ policies did not affect municipality-wide housing permits or rents. However, the implementation of IZ resulted in an average of 2.1 % increase in home prices. Our results also underscore the connection between IZ policy design and market outcomes: more stringent IZ policies (i.e., those that are mandatory and apply to the entire jurisdiction) led to a higher impact on home prices while mitigating the rent effect. Additionally, IZ's market effects varied based on market conditions and the time elapsed since policy adoption. We discuss these findings in terms of implications for policy design and planning practice.
Keywords
Inclusionary zoning; Housing market outcome; Policy effect; United States; Staggered Difference-in-Differences
Bourassa, S. C., Dröes, M. I., & Hoesli, M. (2024). Housing Market Segmentation: A Finite Mixture Approach. De Economist (Netherlands), 172(4), 291–337. https://doi.org/10.1007/s10645-024-09446-2
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Abstract
This paper investigates the usefulness of adding a discrete choice model to the hedonic model via a finite mixture approach. Our approach leads to different hedonic models for different housing market segments based on household information. As such, the proposed method goes beyond measuring the average price of housing attributes. As a case study, we estimate the finite mixture model for the Miami and Louisville metropolitan areas using information on race, ethnicity, and income from the American Housing Survey. We find that the model outperforms the standard hedonic model or a model with linear interaction terms between demographics and housing characteristics. Moreover, market segmentation is based on a complex combination of race, ethnicity, and income. For Louisville, Black households need 2.5 times higher income than White households to advance to a higher market segment and even at high incomes tend to occupy their own segment. For Miami, low-income, non-Hispanic households live in their own segment even if occupying the same dwelling size as households in other segments.
Keywords
Housing market segmentation; Hedonic model; Finite mixture model; R31; O18; D51
The Washington Center for Real Estate Research has released a new report entitled “The State of the State’s Housing.” This is an inaugural annual report. View the report here.
Professor Steve Bourassa of the Washington Center for Real Estate Research (WCRER) and Runstad Department of Real Estate was quoted in a story entitled “First-time Buyer Affordability at Lowest Point in Four Years” in The Bellingham Herald. Read the full article here.
Mason Virant works in the Washington Center for Real Estate Research
Professor Steve Bourassa of the Washington Center for Real Estate Research (WCRER) and Runstad Department of Real Estate was quoted in a story entitled “Listings are up, interest rates may come down.” Read the full article here.
Wang, R., & Spicer, J. (2024). “All roads lead to Rome?” Performance evaluation across different types of community land trusts based on a large-scale survey. Journal of Urban Affairs, 1–22. https://doi.org/10.1080/07352166.2024.2371400
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Abstract
Community land trusts (CLTs) seek to keep homes and other urban spaces permanently affordable and community controlled. As their number across the United States has increased, different iterations of the CLT model seem to have proliferated in practice, stoking scholarly debate as to their varying outcomes and benefits. There has, however, been little attempt to empirically measure the relationship between this institutional diversity and outcomes. Applying institutional theory to a national CLT dataset, we identify five main organizational sub-types of CLT: traditional CLTs, start-up CLTs, government-housed CLTs, nonprofits with a CLT/shared equity (SE) program, and adapted CLTs. Statistical tests confirm a high degree of similarity in operational scope, organizational capacity, and performance outcomes across the most prominent sub-types. The limited statistical differences which can be identified are consistent with known CLT and urban institutional development processes. Further studies might seek to determine how consequential such limited differences may be.
Keywords
Community land trust; permanently affordable housing; historical institutionalism; community control; shared equity housing
A cohort of 4 projects were awarded Inspire Funds in April 2023. The report-outs from these projects are described below with a summary of project work and progress. The 2023 cohort of Inspire Fund awardees met with the 2024 cohort of awardees in May 2024 to share their accomplishments, successes, and challenges, and to foster a connection between these research teams as resources to one another. The 2024 cohort has begun their projects and will share their products in 2025….
Wang, Z., Ito, K., & Biljecki, F. (2024). Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery. Cities, 145, 104704-. https://doi.org/10.1016/j.cities.2023.104704
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Abstract
The well-being of residents is considerably influenced by the quality of their environment. However, due to the lack of large-scale quantitative and longitudinal evaluation methods, it has been challenging to assess residents' satisfaction and achieve social inclusion goals in neighborhoods. We develop a novel cost-effective method that utilizes time series street view imagery for evaluating and monitoring visual environmental quality in neighborhoods. Unlike most research that relies on site visits or surveys, this study trains a deep learning model with a large-scale dataset to analyze six perception indicators' scores in neighborhoods in different geographies and does so longitudinally thanks to imagery taken over a period of a decade, a novelty in the body of knowledge. Implementing the approach, we examine public housing neighborhoods in Singapore and New York City as case studies. The results demonstrated that temporal imagery can effectively assess spatial equity and monitor the visual environmental qualities of neighborhoods over time, providing a new, comprehensive, and scalable workflow. It can help governments improve policies and make informed decisions on enhancing the design and living standards of urban residential areas, including public housing communities, which may be affected by social stigmatization, and monitor the effectiveness of their policies and actions.
Keywords
Residential quality; Public housing; Environmental quality; Spatial equity; Street view imagery; Visual environment