Investments in this strategy aim to reduce homelessness by increasing affordable units available, integrating links to social services like employment training and healthcare, and improving rental protections to reduce risk of eviction. 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.
Homelessness persists in all developed nations at various levels. Experts broadly define three types of homelessness: temporary homelessness due to an event like a natural disaster or eviction; episodic homelessness, with individuals or families frequently transitioning in and out of homelessness due to financial constraints or mental illness; and chronic homelessness, often due to mental health or substance abuse challenges.
Homelessness has proven and significant impacts on the mental and physical health of individuals who experience it (9). Because of the public cost of temporary housing, homelessness also has economic impacts on governments as well as individuals and communities (9). Some studies have found that the costs to the public of a homeless person can exceed by as many as five times the costs of a person in subsidized affordable housing, and high rates of homelessness can lead to challenges in childhood development, educational outcomes, community resilience, and violent crime (13, 14). For any individual who cannot access stable housing, the outcomes associated with this investment strategy are likely essential (10). Investments can reduce homelessness by:
Interested in understanding how gender relates to this strategy? Check out the gender lens summary and metrics created to complement this theme: Improving Access to Housing for Women and Gender and Sexual Minorities.
The most recent global housing-focused survey estimated a worldwide homeless population of 100 million, with up to 1.6 billion people occupying inadequate housing (12). Although most affordable housing units are constructed with the intention of serving lower-income communities, projects that do not offer resident services or subsidies remain out of reach for many extremely low-income homeless families. Investors wishing to combat homelessness can focus on projects that are committed to serving families below 30% AMI in areas that have unusually high levels of homelessness.
While no demographic is immune to the risk of homelessness, structural and systemic problems like lack of affordable housing, high unemployment, and poverty make certain populations more susceptible to homelessness. The following populations are often especially susceptible:
Individuals Fighting Substance Abuse: People living with addictive disorders, like drug and alcohol addiction, are often disproportionately susceptible to homelessness. Addiction often leads to economic stress, job loss, or disruption of support networks. Roughly two-thirds of homeless people report that drugs and/or alcohol were a major cause of their homelessness, and 68% of U.S. mayors found that addiction was the greatest cause of homelessness for single adults (1). In many cases, homelessness exacerbates these disorders, and lack of access to supportive services and healthcare often accompanies homelessness, making treatment all the more challenging (2).
Individuals Suffering from Severe Mental Illness: Often cited among the top three causes of homelessness, severe mental illness can disrupt a person’s capacity for everyday tasks and prevent individuals from forming meaningful relationships. As a result, those with severe mental illness often have less of a social safety net. Roughly 20–25% of the homeless population in the U.S. suffer from severe mental illness, and in a survey of the U.K.‘s homeless population found that up to 80% of homeless individuals reported a mental health issue (45% reported having been diagnosed as such) (3, 20).
Individuals with Physical Disabilities: Persons with physical disabilities, especially those with limited support networks, are highly susceptible to homelessness because of limited opportunities for employment, challenges in finding appropriate housing, and difficulty of everyday tasks (4). In Australia, for example, individuals with disabilities comprise 18% of the total population but 25% of the homeless population (5).
Veterans: In some developed-market countries, veterans are likely more susceptible to homelessness. In the U.S., veterans comprise 9% of the homeless population, compared to only about 6.8% of the total population (6). Veteran homelessness can often be attributed to differentially higher rates of severe mental health disorders, such as Post-Traumatic Stress Disorder (PTSD), depression, or anxiety. Veterans are also more likely to experience substance abuse, have lower socioeconomic status, or have trouble finding permanent employment (6).
Victims of Domestic Abuse: A significant proportion of homeless people have experienced domestic abuse in their lifetimes. Abuse is often cited as the primary source of family homelessness (7). Nearly 65% of homeless women in the U.S. report having been abused in adulthood. Domestic violence survivors often lack the resources to support themselves and their families, and can be forced to live on the street, in cars, in extremely crowded environments, or in emergency housing—or return to abusive households. In most cases, women leaving abusive situations leave with children (see also: Fewer Individuals Living in Abusive Homes) (7).
In most developed-market countries, homeless populations live in urban or peri-urban areas. In the United States, between 4% and 7% of homeless people (compared to about 15% for the total population) live in rural areas (8).
The extent to which this strategy can reduce homelessness depends on the nature of the project and the housing brought to market. Housing accessibility requires units that are physically, financially, and intellectually accessible to their intended beneficiaries. For formerly homeless populations, affordable housing, to be successful, must be combined with supportive services, job training, and physical/mental healthcare. Projects that do not specifically target very-low-income or vulnerable populations risk having little impact on the problem. Affordable housing projects that target these populations, by putting in place the policies and service connections, will likely be better for the beneficiaries they reach.
The number of individuals who can receive outcomes through this strategy depends on the number of homeless individuals. While rates of homelessness vary significantly across and within developed markets, many areas hover around 100 homeless persons per 10,000 (for Australia, this number is around 105 per 10,000, for the U.S. it is roughly 111, and for Germany, it is around 35) (12).
The amount of change that beneficiaries can receive through this strategy depends on the housing itself and the extent to which it successfully provides sustainable housing for homeless individuals.
Alpha Project’s Permanent Supportive Housing Program was built explicitly to house homeless and very-low-income people in downtown San Diego. Residents have access to on-site support services, such as mental health and addiction counseling, transportation assistance, clothing and hygiene supplies, and employment readiness training. Communities that invest in such permanent supportive housing projects have shown steeper declines in chronic homelessness over time (15).
National Coalition for the Homeless. “Substance Abuse and Homelessness.” Fact sheet. July 2009. http://www.nationalhomeless.org/factsheets/addiction.pdf
National Alliance to End Homelessness. “Opioid Abuse and Homelessness.” April 5, 2016. http://www.endhomelessness.org/library/entry/opioid-abuse-and-homelessness
National Coalition for the Homeless. “Mental Illness and Homelessness.” Fact sheet. July 2009. http://www.nationalhomeless.org/factsheets/Mental_Illness.pdf
National Health Care for the Homeless Council. “Disability, Employment, and Homelessness.” 2011 Policy Statement. http://www.nhchc.org/wp-content/uploads/2011/09/disability2011_-final.pdf
Homelessness Australia. “DisabilityCare, Housing, and Homelessness.” January 2016. http://www.homelessnessaustralia.org.au/sites/homelessnessaus/files/2017-07/DisabilityCare.pdf
National Alliance to End Homelessness. “Veteran Homelessness.” Fact sheet. April 22, 2015. http://www.endhomelessness.org/library/entry/fact-sheet-veteran-homelessness
National Coalition for the Homeless. “Domestic Violence and Homelessness.” Fact sheet. July 2009. http://www.nationalhomeless.org/factsheets/domestic.html
National Alliance to End Homelessness. “State of Homelessness Report.” https://endhomelessness.org/homelessness-in-america/homelessness-statistics/state-of-homelessness-report/
The Homeless Hub. “Homelessness 101: Cost Analysis of Homelessness.” Canadian Observatory on Homelessness. http://homelesshub.ca/about-homelessness/homelessness-101/cost-analysis-homelessness
Charlene K. Baker, Sarah Cook, and Fran H. Norris. “Domestic Violence and Housing Problems.” Violence Against Women 9, No. 7 (July 2003): 754–83. http://socialsciences.people.hawaii.edu/publications_lib/domestic%20violence%20and%20housing.pdf
“Building More Homes.” Shelter: The Housing and Homelessness Charity. http://england.shelter.org.uk/campaigns_/why_we_campaign/the_housing_crisis/building_more_homes/building_more_homes
“Global Homelessness Statistics.” Homeless World Cup Foundation. ”$”:https://www.homelessworldcup.org/homelessness-statistics/
Daniel Flaming, Patrick Burns, Michael Matsunaga. “Where We Sleep: Costs when Homeless and Housed in Los Angeles.” Economic Roundtable (2009). https://economicrt.org/wp-content/uploads/2009/11/Where_We_Sleep_2009.pdf
National Center for Children in Poverty. “Youth, Homelessness, and Education.” http://www.nccp.org/projects/yhe.html
“Affordable Housing.” Alpha Project. https://www.alphaproject.org/housing
Matthew Desmond, Carl Gershenson, and Barbara Kiviat. “Forced Relocation and Residential Instability among Urban Renters.” Social Service Review 89, no. 2 (June 2015): 227–62. h”$”:https://doi.org/10.1086/681091
Debra J. Rog, C. Scott Holupka, and Lisa C. Patton. Characteristics and Dynamics of Homeless Families with Children. Washington, DC: U.S. Department of Health and Human Services, Fall 2007. https://aspe.hhs.gov/report/characteristics-and-dynamics-homeless-families-children
Marybeth Shinn. Ending Homelessness for Families: The Evidence for Affordable Housing. National Alliance to End Homelessness and Enterprise Community Partners, 2009. https://b.3cdn.net/naeh/b39ff307355d6ade38_yfm6b9kot.pdf
Marybeth Shinn, Beth C. Weitzman, Daniela Stojanovic, James R. Knickman, Lucila Jiménez, Lisa Duchon, Susan James, and David H. Krantz. “Predictors of Homelessness Among Families in New York City: From Shelter Request to Housing Stability.” American Journal of Public Health 88, No. 11 (November 1998): 1651–57. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1508577/
Homeless Link. “Homelessness and Health Research.” http://www.homeless.org.uk/facts/our-research/homelessness-and-health-research
This mapped evidence shows what outcomes and impacts this strategy can have, based on academic and field research.
Giselle Routhier. Rejecting Low Expectations: Housing is the Answer. State of the Homeless. Coaliton for the Homeless, March 2017.
Administration for Children and Families. Early Childhood Homelessness in the United States: 50-State Profile. January 2016.
Marybeth Shinn. Ending Homelessness for Families: The Evidence for Affordable Housing. National Alliance to End Homelessness and Enterprise Community Partners, 2009.
Dennis P. Culhane. “The Quandaries of Shelter Reform: An Appraisal of Efforts to ‘Manage’ Homelessness.” Social Service Review 66, no. 3 (1992): 428–40.
Office of Policy Development and Research. The Family Options Study. Washington, DC: U.S. Department of Housing and Urban Development, 2016.
Yin-Ling I. Wong, Dennis P. Culhane, and Randall Kuhn. “Predictors of Exit and Reentry among Family Shelter Users in New York City.” Social Service Review 71, no. 3 (September 1997): 441–62.
Thomas Byrne, Jamison D. Fargo, Ann Elizabeth Montgomery, Ellen Munley, and Dennis P. Culhane. “The Relationship between Community Investment in Permanent Supportive Housing and Chronic Homelessness.” Social Service Review 88, no. 2 (June 2014): 234–63.
Dennis P. Culhane, and Thomas Byrne. Ending Chronic Homelessness: Cost-Effective Opportunities for Interagency Collaboration. Supplemental Document to the Federal Strategic Plan to Prevent and End Homelessness. United States Interagency Council on Homelessness, June 2010.
Joe Finn and Jeff Hayward. “Bringing Success to Scale: Pay for Success and Housing Homeless Individuals in Massachusetts.” Community Development Investment Review 9, no. 1 (2013): 135–38.
Thomas E. Gould and Arthur R. Williams. “Family Homelessness: An Investigation of Structural Effects.” Journal of Human Behavior in the Social Environment 20, no. 2 (2010): 170–92.
John M. Quigley and Steven Raphael. “The Economics of Homelessness: The Evidence from North America.” International Journal of Housing Policy 1, no. 3 (2001): 323–36.
David L. Shern, Chip J. Felton, Richard L. Hough, Anthony F. Lehman, Stephen Goldfinger, Elie Valencia, Deborah Dennis, Roger Straw, and Patricia A. Wood. “Housing Outcomes for Homeless Adults with Mental Illness: Results from the Second-Round McKinney Program.” Psychiatric Services 48, no. 2 (February 1997): 239–41.
Sam Tsemberis and Ronda F. Eisenberg. “Pathways to Housing: Supported Housing for Street-Dwelling Homeless Individuals with Psychiatric Disabilities.” Psychiatric Services 51, no. 4 (April 2000): 487–93.
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.
Number of formerly homeless individuals housed in single- 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 the source of their data, as well as any assumptions that went into calculating this metric.
This metric is intended to capture either a) the number of formerly homeless families provided affordable housing as a result of the investment, or b) the number of formerly homeless individuals provided affordable housing as a result of the investment. Investors should footnote whether they choose to measure at a family or an individual level. Organizations may also want to report this metric alongside the total number of individuals or families housed as a means to understand what proportion of their investee’s residents were formerly homeless. Collection of these data likely relies on a long-term relationship with the investee. A short-term debt investor may find it challenging to capture this metric.
This metric indicates the level of success at providing housing for homeless individuals. If the strategy selected by the investor relies on converting homeless individuals to housed individuals, this is a key performance indicator.
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 rate of people experiencing homelessness during the reporting period.
This metric is necessarily measured at some aggregate level (neighborhood, city, county, state, country).
Depending on the country, data should be available from city/town or federal governments. In some cases, reputable data can also be found through reputable think tanks or NGOs focused on homelessness eradication.
While some organizations measure the homelessness rate longitudinally to track changes in the wake of affordable housing investments, this rate is unlikely to change significantly, at any level, based on a single investment or even a portfolio of investments. This metric is a useful tool to understand areas of greatest need.
Number of formerly incarcerated individuals or families housed in single- 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 the source of their data, as well as all assumptions used in their calculations.
This metric is intended to capture either a) the number of formerly incarcerated families provided affordable housing as a result of the investment, or b) the number of formerly incarcerated individuals provided affordable housing as a result of the investment. Investors should footnote whether they choose to measure at a family or an individual level. Organizations may also want to report this metric alongside the total number of individuals/families housed as a means of understanding what proportion of their investee’s residents were formerly incarcerated. Collection of these data likely relies on a long-term relationship with the investee. A short-term debt investor may find it challenging to capture this metric.
Investors interested in working to reduce recidivism may choose to capture this metric, which indicates performance toward the outcomes and impacts outlined in the logic model. If the strategy selected by the investor relies on converting incarcerated individuals to affordably housed individuals, this metric is a key performance indicator.
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.
Number of reports issued to the local police or enforcement office regarding issues of domestic abuse.
Organizations should footnote the type and number of each sort of violation. Organizations should also footnote the source of their data, as well as any assumptions that went into calculating this metric.
This metric is intended to capture the unique number of reports to the police or local enforcement agency from the housing project or development. These data may be challenging to capture. While most management companies will have records of domestic abuse reported on their premises, they may not track or aggregate that data. Data may also be available from the municipality, depending on the location.
Investors focused on reducing homelessness related to domestic violence may choose to track this metric, which is an imperfect indicator of the extent of domestic abuse in a particular area. Comparison to a baseline of domestic abuse in shelters and among homeless populations may also indicate performance toward the goal of reducing domestic abuse.
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 end beneficiaries at risk of housing instability may want to track this metric, which indicates expenditures on rent/mortgage and utilities, along with Client savings (PI1748, below). 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 ? 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 end beneficiaries at risk of housing instability may want to track this metric along with Percent of household income spent on rent/mortgage and utilities during the reporting period (above).
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.