Investments in this strategy aim to improve housing quality by increasing energy efficiency, decreasing cost burden, and reducing exposure to airborne pollutants, harmful pests, molds, or harmful chemicals. The sections below include an overview of the strategy for achieving desired goals, supporting evidence, core metrics that help measure performance toward goals, and a curated list of resources to support collecting, reporting on, and using data for decision-making.
The quality of both affordable and market-rate housing significantly affects the lives and physical and mental health of its tenants. Poorly maintained homes are more likely to have mold, vermin, airborne pollutants, and lead paint—all of which can significantly hinder the development of children and contribute to negative health outcomes in otherwise healthy populations (3). These factors make it more challenging to focus on education or hold a job and contribute to frequent and disruptive moves (see Residential Stability strategy) (4). For any population or individual living in poor-quality housing for whom the quality of their housing impacts their health, educational outcomes, or ability to earn money, the outcomes associated with this investment strategy are likely essential. Investments in this theme can:
Taking 30% of income as a standard for housing affordability, the number of cost-burdened U.S. households overall has been estimated around 39 million (3, 7, 8). This number includes about 48% of renters. In the UK, 43% of homes fail Shelter’s Living Home Standard (5). Researchers at the University of Adelaide reported that an estimated one million Australians are living in poor- to very-poor-quality housing (6).
While any families or individuals with up to 70% of Area Median Income (AMI) may be good targets for access to high-quality affordable housing, this strategy can particularly help several specific groups:
Individuals Living in Poor-Quality Housing: Individuals living in poorly managed, lead-laden, or infested households will benefit more from high-quality housing than individuals already living in good-quality housing.
Individuals and Families Living in Housing that is Crowded or Too Densely Populated: Overcrowded housing contributes to significant mental and physical health challenges for its tenants, including by increasing the spread of disease. In New Zealand hospitals, for example, one in 10 patients are admitted for an infectious disease that could be attributed to crowded housing conditions (1).
Homeless Individuals: Roughly 30% of homeless individuals in the United States live in improvised shelters (e.g., shacks, cars, public areas). While any affordable housing would likely represent an improvement in shelter conditions (especially in temperate regions where the individual has regularly improvised shelter in temperatures below 40°F), placement in quality housing is especially beneficial (2).
Individuals Living in Temperate Zones: A review of the health effects of housing quality in geographies including Australia, New Zealand, the U.K., and the U.S. noted that the single clearest positive impact on health came from warmth and energy efficiency in housing. Access to housing that was sufficiently warm in the winter months contributed to improvements in general physical, respiratory, and mental health (13).
In most developed-market countries, homeless populations live in urban or peri-urban areas. In the U.S., for example, between 4% and 7% of the homeless population (compared to about 15% of the total population) live in rural areas (2). While more homeless individuals are in urban areas, rural areas often have worse-quality housing (2). Because homelessness can be more difficult to identify in rural areas, and because impoverished rural communities rarely have the formal social service networks of their urban counterparts, many end beneficiaries of this investment strategy may live in rural areas.
The extent to which this strategy can address housing quality depends on the housing a specific affordable housing project brings to market. For this strategy, increasing access to housing that is of comparatively better quality than other housing at similar price points would likely make an investment much better than what would occur without it.
The number of individuals who can receive outcomes through this strategy is limited only by the number of individuals who lack adequate access to quality affordable units. Estimates vary by country and region, but as an example, more than 19 million U.S. households spend more than half of their household income on housing; many of the current housing options for low-, very-low, and extremely-low-income and vulnerable individuals or families are likely of low quality.
The amount of change that end beneficiaries can receive through this strategy depends on the housing itself, the extent to which the project succeeds in providing quality housing for tenants, and establishment of housing maintenance procedures consistent with best practices or certifications.
In 2008, 198 units of the 135th Street Green Affordable Housing project in New York’s Harlem neighborhood were purchased by the Rose Smart Growth Investment Fund, including 10 six-story buildings in close proximity to trains and with nearby access to food. Shortly after purchase, with financing from a number of sources, the project was renovated, including all 159,000 square feet of residential property and 4,500 square feet of retail. The LEED-certified Section 8 housing was upgraded with the installation of additional insulation, double pane windows, a 250kw rooftop solar array, and significantly improved indoor air quality (11).
Wilma McCorkindale. “House Overcrowding Disease Fears.” Stuff [Fairfax Media New Zealand]. June 7, 2013. http://www.stuff.co.nz/national/health/8768249/House-overcrowding-disease-fears
National Alliance to End Homelessness. “State of Homelessness Report.” https://endhomelessness.org/homelessness-in-america/homelessness-statistics/state-of-homelessness-report/
Center for Housing Policy. “The Impacts of Affordable Housing on Health: A Research Summary.” http://www.homelesshub.ca/resource/impacts-affordable-housing-health-research-summary-0
Rebecca Cohen and Keith Wardrip. “Should I Stay or Should I Go? Exploring the Effects of Housing Instability and Mobility on Children.” http://homelesshub.ca/resource/should-i-stay-or-should-i-go-exploring-effects-housing-instability-and-mobility-children
“The Living Home Standard.” Shelter: The Housing and Homelessness Charity. http://www.shelter.org.uk/livinghomestandard
Australian Associated Press. “One Million Australians Living in Substandard Housing, Study Finds.” The Guardian. August 25, 2016. https://www.theguardian.com/australia-news/2016/aug/25/one-million-australians-living-in-substandard-housing-study-finds
National Low Income Housing Coalition. “The Long Wait for a Home.” Housing Spotlight 6, no. 1 (Fall 2016). http://nlihc.org/sites/default/files/HousingSpotlight_6-1_int.pdf
Joint Center for Housing Studies. The State of the Nation’s Housing. Cambridge, MA: Harvard University, 2017. http://www.jchs.harvard.edu/research/state_nations_housing
“West 135th Street.” Jonathan Rose Companies. http://www.rosecompanies.com/projects/west-135th-street/
Rebecca Cohen, Jeffrey Lubell, and Rosalyn Crain. The Positive Impacts of Affordable Housing on Health: A Research Summary. The Center for Housing Policy, 2007. http://www.enterprisecommunity.org/resources/positive-impacts-affordable-housing-health-research-summary-13889
Tim K. Takaro, James Krieger, Lin Song, Denise Sharify, and Nancy Beaudet.
This mapped evidence shows what outcomes and impacts this strategy can have, based on academic and field research.
Leonard M. Lopoo and Andrew S. London. “Household Crowding During Childhood and Long-Term Education Outcomes.” Demography 53, no. 3 (2016): 699-721.
R. Cohen. “The Positive Impacts of Affordable Housing on Health: A Research Summary.” Washington, DC: Centre for Housing Policy. (2009).
Susan Kay Cummins and Richard Joseph Jackson. “The Built Environment and Children’s Health.” Pediatric Clinics of North America 48, no. 5 (2001): 1241-1252.
Hood, Ernie. “Dwelling Disparities: How Poor Housing Leads to Poor Health.” Environmental Health Perspectives 113, no. 5 (2005): A310.
Olden, Kenneth, and Sandra L. White. “Health-Related Disparities: Iinfluence of Environmental Factors.” Medical Clinics 89, no. 4 (2005): 721-738.
Sard, Barbara, and Will Fischer. “Preserving Safe, High Quality Public Housing Should Be A Priority of Federal Housing Policy.” Center on Budget and Policy Priorities 1 (2008): 36.
MacDonald, Heather, Richard Funderburg, David Swenson, Anne Russett, and Malynne Simeon. “Housingâ€™s Economic and Social Impacts.” (2007).
Pollack, Craig Evan, Beth Ann Griffin, and Julia Lynch. “Housing Afordability and Health Among Homeowners and Renters.” American Journal of Preventive Medicine 39, no. 6 (2010): 515-521.
Sandel, M., J. Cook, and A. Poblacion. “Housing as a Health Care Investment: Affordable Housing Supports Childrenâ€™s Health.” Insights from Housing Policy Research (2016).
Braveman, Paula, Mercedes Dekker, Susan Egerter, Craig Pollack, and Tabashir Sadegh-Nobari. “Where We Live Matters for Our Health: The Links Between Housing and Health.” (2008).
Freeman, Lance, and Hilary Botein. “Subsidized Housing and Neighborhood Impacts: A Theoretical Discussion and Review of the Evidence.” CPL Bibliography 16, no. 3 (2002): 359-378.
Each resource is assigned a rating of rigor according to the NESTA Standards of Evidence.
Number of housing units constructed as a result of investment by the organization during the reporting period.
Organizations should footnote all assumptions that went into calculating or counting new units, as well as the sources of their data.
The total number of new units constructed should be easily accessible from the developer or architect of the project. Depending on the nature of the investment vehicle, mandated reporting against this metric by the project developer may merit inclusion in a terms sheet to guarantee high-quality, timely data. Organizations should count new units as complete at the conclusion of their construction—meaning at the point when they could reasonably be occupied.
This metric is essential to understand the scale of potential impact delivered by the investment. New units of housing are necessary in order to deliver on outcomes related to the affordable occupancy of these units.
Number of housing units rehabilitated or preserved as a result of investment by the organization during the reporting period.
Organizations should footnote all assumptions that went into calculating or counting preserved or rehabilitated units, as well as the sources of their data.
The total number of rehabilitated/preserved affordable housing units should be easily accessible from the project developer or management company. Depending on the nature of the investment vehicle, reporting against this metric by the project developer or management company may merit inclusion in a terms sheet to guarantee high-quality, timely data.
Like the number of units of affordable housing, this metric is essential to understand the scale of the potential impact delivered by the investment. Preservation and rehabilitation of new units are necessary in order to deliver on outcomes related to the affordable occupancy of these units.
Number of individuals housed or projected to be housed in single-family or multi-family dwellings as a result of new construction, loans, repairs, or remodeling resulting from investments made by the organization during the reporting period.
Organizations should footnote whether they are reporting on the number of individuals housed or the number of individuals projected to be housed. For reasons related to the structure of the investment vehicle, organizations may prefer and choose either. Organizations should also footnote the source of the data.
These data should be available at an individual investee level; if not, it can sometimes be found from public sources (depending on source of funding for the housing development). Household-level data per decade are also available in the United States via the Census.
This metric captures the number of individuals who are provided housing in this unit. Measuring against this metric helps to articulate the performance of the product (housing, in this case). Constructed/preserved units are useful as a means of delivering impact only insofar as they are occupied. Ideally, this metric can also be understood alongside potential individuals housed by a project as a means to understand occupancy rate.
The number of residential units that are hold third-party certifications as of the end of the reporting period.
Organizations should footnote the certification name, certifying body, and date since the product/service has been certified.
This metric is intended to capture third-party, standards-based, assurance-based certifications. The process of certification should be performed by a recognized body that is independent from interested parties. These data should be collected directly from the housing developer or management company. While these certifications are typically applied to entire developments or facilities, the unit of measure is housing units as a means to understand the scale of the unit alongside the certification. Organizations should, if possible, tie these data to the above metrics to understand the number of individuals or families housed in units with quality certifications.
While certifications are not necessarily the best indicator of ongoing housing quality, they are rough and easily measurable indicators that housing meets certain base requirements. Because the data are often available from the certification body, as well as from the housing developer or management company, it can be good to track this metric during due diligence or at a portfolio level to inform asset allocation.
The percentage of tenant requests for repair/complaints that received satisfactory responses during the reporting period.
Organizations should footnote the types of complaints (or broadly classify types of complaints into tiers) and any assumptions that went into the calculation. Organizations should also footnote how they determine whether or not the request was addressed.
This metric is intended to capture the percentage of requests from tenants that were met by the landlord or management company in a satisfactory manner.This data should be collected directly from the housing development or management company. While most will have repair logs to track costs and expenditures, some investees may need to develop systems to collect this data.
This metric is an especially good indicator of performance if tracked before and after rehabilitation/renovation of housing units. Generally, responsiveness to tenant requests indicates the housing quality is better, though a growth in the number of requests may indicate that housing stock is depreciating and may need to be renovated or rehabilitated.
The number of individuals per area unit in affordable housing units.
Organizations should footnote all sources of data, as well as all assumptions used in calculating this metric.
Habitable space in each affordable housing development should be available from project developer or management company. For information on tracking number of individuals housed, see Number of Individuals Housed (P12640). Organizations should calculate this metric using only habitable space within units, not shared spaces in apartment buildings.
This metric is intended to capture the crowdedness of affordable housing units. Many place-based diseases are exacerbated or more easily spread via closely packed affordable housing units. For more information on measuring crowdedness, see the U.S. Department of Housing and Urban Development’s website, or similar resource in the country of interest.
Ratio between the number of tenants departing the housing unit and the average number of permanent tenants during the reporting period.
Organizations should footnote whether the individuals have left their units to other affordable or market-rate housing, or whether their exit is unknown.
This metric is intended to capture the ratio between individuals exiting affordable housing and the total number of individuals housed in all units. These data should be collected directly from the management company or building management.
This metric concerns retention rate and the likelihood of achieving the impacts outlined in the logic model. If tenants are evicted after several months in affordable units or leave voluntarily, the impacts are less likely to be achieved, as stability decreases. However, organizations should consider, to the extent that data are available, to where their tenants exit: if they are moving into other affordable units or, ideally, to market-rate housing, this metric may indicate successful performance.
The types of supportive housing services linked to affordable housing developments as of the end of the reporting period.
Organizations should footnote details of the supportive services, ideally outlining key performance indicators for each.
This qualitative metric is intended to capture the scope of the services offered by the affordable housing development during the reporting period. The type of each supportive service should be collected at the end of each reporting period.
Investors interested in providing resources to support continued housing stability for formerly homeless individuals ? e.g., life skills training, mental and physical healthcare centers, alcohol and substance abuse treatment, or vocational programs ? may use this metric to track the provision of those services. Supportive services in and of themselves do not indicate performance toward outcomes and impacts. However, this qualitative metric can indicate whether an investee has begun to consider the role that supportive services can play in retaining and advancing beneficiaries of their project.
Percentage of a household’s income that is spent on rent/mortgage and utilities (including heat, water, electricity, and cooling).
"Spending on Rent/Mortgage and Utilities / Total Household Income"
Organizations should footnote the source of their data, as well as any assumptions used in calculating total income and spending on rent/utilities.
Unless a management company requires their tenants to regularly report their income (not common), this metric is often based on the income recorded for the threshold requirement at the time of application for occupancy. Spending on rent/mortgage and utilities should be accessible to the management company.
Investors interested in decreasing the cost burden for beneficiaries at risk of housing instability may want to track this metric, which indicates expenditures on rent/mortgage and utilities (see also: Client Savings [PI1748]). Percent of household income spent on housing can be compared to the 30% suggested baseline for spending on rent/mortgage and utilities as a share of income.
Average cost savings per client obtained by renting or purchasing an affordable unit compared to the average price that client would otherwise pay for a unit during the reporting period.
"Average cost of market-rate unit per individual âˆ’ Average cost of affordable unit per individual"
Organizations should footnote the source of their data, as well as any assumptions used in calculating the cost of the market rate and affordable units.
This metric relies on assumptions for the average cost per client for affordable and market-rate housing. When calculating the market-rate alternative, organizations should use an average from the surrounding area that they deem appropriate, footnoting assumptions. Cost of affordable housing per unit can most often be accessed through the management company.
Investors interested in decreasing the cost burden for beneficiaries at risk of housing instability may want to track this metric, which indicates savings as a result of affordable housing.
The number of residential units that have received third-party energy efficiency audits.
Organizations should footnote the supplier of the audit, the results, and the source of the data.
This metric is intended capture third-party energy audits of individual units. This data should be collected from the developer or management company. Ideally, these should be done before and after an energy retrofit to understand the energy and cost savings that resulted from the investment.
Typically, a home energy audit is the first step to understanding how and which energy efficiency improvements could benefit a unit or development. Ongoing auditing of housing stock often does not yield significantly different results unless there has been significant retrofit or renovation. Organizations should implement the recommended changes from each audit in order for this metric to indicate performance.
Indicates whether the organization implements policies to protect its clients.
Organizations should footnote details on the types of policies it implements.
This data should be available at an individual investee level. If it is not directly available from the investee, it can sometimes be found through public sources. Example policies that an organization might have in place to protect its clients may include: rent collection policies, internal audits to check practices that could increase indebtedness, eviction policies, employee training practices, resident response policies, and late payment penalty processes.
This metric is intended to capture the policies the project puts in place to protect its residents from unnecessary sources of residential instability and to ensure continued housing quality. This metric shows how successfully projects are laying policy groundwork for stable and long-term periods of residency.