Can Subsidized Housing Help Address Homelessness in New England?
The relationship between subsidized housing and homelessness is hard to measure, but our research indicates that low-cost housing is likely to bring down homeless rates.
Federal and state governments spend considerable sums on housing programs for the poor. Programs that offer subsidized housing to mitigate homelessness have attracted increased interest in the wake of the foreclosure crisis that began in 2007 and extended well beyond the Great Recession of 2008–2009. However, whether subsidized housing is effective at combating homelessness remains an unresolved question.
Homelessness in New England
On a single night in January 2014, nearly 580,000 people were homeless in the United States, with 32,500 of them residing in New England.1 Since 2007, trends in homelessness in New England have diverged from those in the nation overall, with national homeless counts on the decline but regional counts on the rise.
When normalized to population to create a rate of homelessness (the number of homeless per 10,000 residents), we see that the rise in measured homelessness in New England has been driven exclusively by a surge in homeless families in shelters and transitional housing, rather than increases in homelessness among unsheltered families or among individuals. (See “Homelessness Rates by Family and Sheltered Status, 2007–2014.”) In contrast, sheltered family homelessness has been flat for the United States as a whole, and the decline in national homelessness largely reflects falling rates among unsheltered families and individuals. (People are considered unsheltered if they are living on the street or in cars or tents, etc.)
The increase in the rate of sheltered family homelessness in New England is driven by the large increases in this measure in Massachusetts and Vermont. In turn, it's possible that the increases in sheltered family homelessness in these two states reflect an interaction between nationwide market forces pushing more families out of their homes, such as rising rents and/or declining incomes, or policies in both states that guarantee access to shelter for homeless families. In both Massachusetts and Vermont, families are offered access to shelter even when traditional shelter beds are not available: hotels and motels are used for this purpose.2 In areas without such flexible shelter policies, if shelters fill to capacity, anyone who finds themselves homeless will likely either fall into the category of unsheltered homelessness or will find temporary accommodation (e.g., doubled up) with friends or family. Those who are unsheltered should be accounted for as such in homeless measures, but it is rare for families—as opposed to individuals—to be found in unsheltered situations. Homeless families are more likely to double up with friends or family, and if they do, they will not be recorded in homeless counts. Therefore, similar increases in family homelessness across states might nonetheless boost official homeless counts more in Massachusetts and Vermont than in states without similar shelter guarantees.
Unfortunately, it is difficult to observe changes in doubled-up populations in data sources, and the evidence remains inconclusive about this explanation.3 Other potential explanations include unique market forces in states with rising rates of family homelessness and methodological issues with counting the unsheltered populations. However, these hypotheses cannot be easily studied with the limited data currently available on homeless populations.
A Role for Subsidized Housing?
Legislation passed by the US Congress in 2009 amending the definition of homelessness included this statement: "A lack of affordable housing and limited scale of housing assistance programs are the primary causes of homelessness."4 Nevertheless, the role of subsidized housing in reducing homelessness is extremely difficult to measure. This is because subsidized housing is not randomly placed across areas, making it challenging to determine the impact of such housing on homelessness, separate from related factors such as neighborhood poverty or unemployment.
To overcome this hurdle, we concentrate on one source of subsidized housing: the Low-Income Housing Tax Credit (LIHTC). LIHTC, created in 1986, allocates tax credits to state housing agencies, which then distribute them to developers through a competitive process. The tax credits provide a dollar-for-dollar reduction in tax liabilities over 10 years.5
An advantage of focusing on LIHTC is that, under the program, projects that are placed in low-income areas designated as "qualified census tracts" (QCTs) are awarded 30 percent more credits than those in other areas.6 As a result of this rule, very similar tracts may receive different amounts of tax benefits for LIHTC-funded projects due to differences in QCT eligibility. This creates a quasi-experiment in housing placements when comparing moderately poor neighborhoods just above and below the QCT eligibility cutoff. For these similarly poor tracts, observed differences in LIHTC housing are assumed to be quasi-random, due to eligibility differences.7
Impact of Subsidized Housing on Local Homelessness
Upon confirming that LIHTC leads developers to create subsidized housing, we examined the impact of such housing on local homelessness.8 In the figure "Impact of LIHTC on Homelessness in the Average Neighborhood Estimated Under Various Scenarios," the confidence intervals around the estimates given in the graph indicate the precision of each estimate and the range of possible "true" values associated with a given degree of certainty.9 When we did not use QCT eligibility to create a quasi-random experiment, we observed a counterintuitive, significantly positive relationship between LIHTC activity and homeless counts. That is, homeless counts were higher where the availability of low-cost housing was greater. This positive relationship may be due to factors that make neighborhoods attractive to both developers and the homeless (for example, access to public transportation), or alternatively could result from developers preferring areas with higher rates of homelessness.
Once we introduced QCT eligibility to create a quasi-experiment, initial plots showed LIHTC development was no longer associated with increases in homelessness in New England. Rather, we found that an additional project reduces the homeless count by 24.9 individuals in New England and raises it by 4.4 individuals outside of New England. While neither estimate differs significantly from zero, the range of potential true effects in each case contains many negative values—that is, many values indicating decreases in homelessness. In fact, in New England, the majority of these potential true effects are negative. This suggests that, although we cannot rule out a zero effect with 90 or even 80 percent certainty, we can nevertheless infer that the true effect is much more likely to reduce homelessness than to have no effect or increase it.
LIHTC development might result in side effects or “spillovers” across nearby tracts that diminish the estimated effect of local LIHTC activity on neighborhood homelessness. For example, additional low-income housing construction in a given tract might lower the amount of LIHTC housing developments in nearby tracts (i.e., supply-side or development spillovers), and/or LIHTC development in a neighborhood could attract homeless populations from neighboring tracts who come in search of low-income housing (i.e., demand-side or mobility spillovers). Regardless of region, we find that adjusting for development spillovers has little impact on the results, although within New England, LIHTC projects are now estimated to reduce the homeless count by slightly more than in the initial quasi-experiment. In contrast, when accounting for mobility spillovers, we find that LIHTC activity leads to a decrease in local homelessness, regardless of region. Specifically, an additional LIHTC project now causes reductions of 33.4 and 9.4 homeless individuals in and outside of New England, respectively. Moreover, in both regions, the majority of the potential true effects are negative, particularly in New England, where we can now rule out the no-effect outcome with 80 percent certainty.
Conclusion
Homelessness is on the rise in New England, driven by an increase in family homelessness. Developers do tend to generate low-income housing when offered incentives to do so. Our quasi-randomized experiments revealed that when mobility-related spillovers across neighborhoods are taken into account, the majority of the evidence suggests that local increases in subsidized housing are likely to reduce neighborhood homelessness, particularly in New England. Our results suggest that on average, an additional LIHTC project could potentially eliminate the majority of local homelessness.
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About the Authors
Robert Clifford
Osborne Jackson,
Federal Reserve Bank of Boston
Osborne Jackson is a senior economist with the New England Public Policy Center in the Federal Reserve Bank of Boston Research Department.
Email: Osborne.Jackson@bos.frb.org
Acknowledgments
This article is a summary of findings from Robert Clifford and Osborne Jackson, “Can Subsidized Housing Help Address Homelessness in New England?” (New England Public Policy Center Research Report No. 15-3, Federal Reserve Bank of Boston, 2015), www.bostonfed.org/economic/neppc/researchreports/2015/rr1503.htm.
Endnotes
- Meghan Henry et al., "The 2014 Annual Homeless Assessment Report to Congress: Part 1 Point-in-Time Estimates of Homelessness" (report, US Department of Housing and Urban Development, Washington, DC, 2014), https://www.hudexchange.info/resources/documents/2014-AHAR-Part1.pdf.
- These policies are not unique to the region: New York City and Washington, DC, for example, have similar programs in place.
- Using the US Census Bureau's American Community Survey (ACS), we find no recent increases in the doubled-up population in states without flexible policies on shelter availability.
- See the Homeless Emergency Assistance and Rapid Transition to Housing (HEARTH) Act of 2009, p. 33, section 1003(A).
- The amount of credits a project receives is determined by applying the appropriate credit rate to the "qualified basis," equal to the eligible project costs multiplied by the share of units to be rent restricted and occupied by low-income residents.
- A tract where at least 50 percent of households have incomes below 60 percent of the area median income is eligible to be deemed a QCT, due to the Omnibus Reconciliation Act of 1989. See Michael Hollar and Kurt Usowski, "Low-Income Housing Tax Credit Qualified Census Tracts," Cityscape: A Journal of Policy Development and Research 9, no. 3 (2007): 153–60.
- A quasi-experiment has a framework similar to that of a traditional experiment but lacks random assignment to treatment and control groups. In place of purely random assignment, a quasi-experiment relies on other important restrictions or assumptions to achieve something that is like random assignment when those restrictions or assumptions are present.
- In New England, we estimate that the stock of subsidized housing is increased largely through the rehabilitation of extant buildings, while outside of New England, subsidized housing is increased mainly through new construction.
- For instance, the 90-percent confidence interval conveys that we can be 90 percent certain that the "true" effect lies within the displayed range of values.
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