«Moving to opportunity voluMe 14, nuMber 2 • 2012 U.S. Department of Housing and Urban Development | Office of Policy Development and Research ...»
A number of factors could contribute to these very high housing cost burdens. First, the information to calculate housing cost burdens comes primarily from self-reports provided during the survey and not from HUD administrative records that verify rents paid and family incomes. The survey asked families how much they pay for their portion of rent or mortgage, whether their utilities (that is, electricity and gas) are included in their rent, and, if not, how much utilities cost the previous month.9 As in the case with the American Housing Survey, families did not have to provide documentation to prove amounts. Determining whether respondents provided information that represented the full private-market rent (as opposed to just their portion of rent) or whether they took the PHA’s utility allowances into account when reporting their utility costs is also not possible.10 The denominator of the housing cost burden—families’ incomes—also comes from survey responses and, in some cases, administrative data sources. Researchers did not apply HUD’s countable income rules and family income adjustments, which are used for Housing Choice Voucher Program (HCVP) programmatic purposes to the information collected from the survey, because much of the information would not be available.
Information on utility allowance maximums for the different housing authorities is available on the PHA websites: Baltimore (http://static.baltimorehousing.org/pdf/2010util.pdf), Boston (http://www.bostonhousing.org/pdfs/LHS2011UtilityChart.pdf), Chicago (http://www.lakecountyhousingauthority.org/HousingChoiceVoucherProgram/Owners/ProgramRentsUtilityAllowance.
aspx), Los Angeles (http://www.hacla.org/attachments/wysiwyg/149/Util-12-1-11MFR1.pdf), and New York (http://www.
Additional policy reasons could explain the high housing cost burdens. HUD applies prorated rents to households with one or more people without eligible citizenship status. By definition, all those households pay more than 30 percent of their adjusted income for rent. This policy could be a factor in Los Angeles, in particular.
payment standard and 30 percent of the participant’s adjusted income, and the participant pays 30 percent of his or her adjusted income plus the additional rent and utility costs. If the total payment for a unit exceeds 40 percent of the recipient’s income, however, the unit does not meet program requirements and cannot be rented with a voucher (Finkel and Buron, 2001). This hard cap at 40 percent of families’ incomes applies only to those renting new units or to new participants using assistance in place, however. MTO families who have not moved in more than 1 year could be paying more than 40 percent of their incomes for housing if landlords increased rent.12 The fact that the MTO demonstration occurred during a national housing boom (and bust) provides some evidence that rent increases could be another factor contributing to the surprisingly large housing cost burdens.
Housing Boom Contributed to High Housing Cost Burdens The national housing boom affected all five MTO sites, creating serious challenges for voucher holders attempting to navigate the private market (Briggs, Popkin, and Goering, 2010). When the MTO demonstration began, the rental market was relatively soft (moderate vacancy rates and prices), particularly in Los Angeles, where participants were able to lease single-family homes in the San Fernando Valley. Starting in the early- to mid-2000s, prices soared for both owner-occupied and rental units. For example, controlling for inflation, home values in Boston’s metropolitan area increased from an average of $343,533 in 2000 to $451,153 during 2005 through 2009. This increase was modest in comparison with that in the Los Angeles metropolitan area, where average home values increased from $384,905 in 2000 to $604,337 during 2005 through 2009.13 Meanwhile, the affordable housing stock plummeted, especially for low-income renters. From 2003 through 2009, the number of very low-income renters across the nation (with incomes of less than 50 percent of the area median) swelled from 16.3 to 18.0 million, while the number of rental units affordable at those income levels, not rented by higher income households and of adequate quality, dropped from 12.0 to 11.6 million. In 2009, extremely low-income renters (with incomes of less than 30 percent of area median) outnumbered affordable, available, and adequate units almost three to one (Steffen et al., 2011).
Exhibit 7 shows that in all five MTO sites, families faced housing markets in which average rents had increased substantially between the beginning and end of the decade.14 Even after controlling for inflation, average monthly rents in Baltimore, Los Angeles, and New York increased more than $100 during this period. To a lesser extent, rents at the lower end of the spectrum also increased, particularly in Los Angeles, where the 25th percentile of monthly rent increased nearly $100.
With the exception of Baltimore, rental vacancy rates also started relatively high in 1990, giving unsubsidized and subsidized renters more opportunities to rent. Rental vacancy rates had tightened For more information on the HCVP, see http://portal.hud.gov/hudportal/HUD?src=/program_offices/public_indian_ housing/programs/hcv/about/fact_sheet.
Home values are from the 2000 Census and the 2005/2009 American Community Survey. Values are CPI-adjusted to 2009 U.S. dollars.
Exhibit 7 shows the increases in rent at the city level. The trends for the metropolitan statistical areas are similar.
considerably by 2000, meaning that low-income renters faced a much more challenging housing market.15 These tight rental markets also could have encouraged MTO families to stay put and attempt to pay increased rents out of pocket. Exhibit 8 shows that vacancy rates rose again after 2005, presumably reflecting the national recession.
Challenges of Managing the Private Market One question raised at the beginning of the MTO demonstration was whether families from distressed public housing who received vouchers would be able to meet the private-market standards of paying rent and utilities on time. For many experimental and Section 8 group families, these standards were a first-time experience, and our analysis indicates that participants, particularly the experimental group families, appeared to be making tradeoffs between keeping up with rent payments and paying utilities. This pattern is consistent with findings from MTO families collected after the interim impacts evaluation (Briggs, Comey, and Weisman, 2010) and research on HOPE VI relocatees who move from distressed public housing to the private market (Levy and Woodley, 2007; Popkin et al., 2002; Popkin, Levy, and Buron, 2009).
Exhibit 9 shows that participants in both the experimental and Section 8 groups were less likely to be more than 15 days late in paying their rent or mortgage than were participants in the control Exhibit 8 shows the rental vacancy rates at the city level. The trends for the metropolitan statistical areas are similar.
group (6 and 7 percentage points, respectively). No differences emerged in eviction rates between the experimental and control groups, however. The Section 8 group was only slightly less likely than the control group to be evicted (significant at the p.10 threshold). Experimental group participants, however, were significantly more likely to report both making late utility payments and having their utilities shut off. For instance, experimental group participants were 5 percentage points more likely to be 15 days late paying their utilities, 5 percentage points more likely to have received shutoff notices for their utilities, and 2 percentage points more likely to have had their utilities shut off for nonpayment compared with control group participants.
Cityscape 103Comey, Popkin, and Franks
Conclusion At its core, MTO was a housing intervention offering options to families living in some of the worst public housing developments in the nation. MTO demonstrated that giving low-income families vouchers results in higher quality housing compared with lower quality public housing or projectbased assisted housing in both the short term (as evidenced by the TOT effect at the time of the survey for the interim impacts evaluation) and the long term (the effects were sustained by the time of the survey for the final impacts evaluation, particularly for the experimental group). This result is supported by studies of other similar populations (Popkin, Levy, and Buron, 2009).
These housing quality improvements could have acted as mediators contributing to the significant gains for MTO participants in mental and physical health outcomes (Sanbonmatsu et al., 2011).
The health improvements could either be in response to physical improvements, such as a lack of vermin and mold, or through stress reduction and a general improvement in quality of life. Either way, the importance of these gains for families’ well-being cannot be overstated.
The MTO demonstration proved not to have much effect on many of the other housing outcomes tracked. A surprisingly large share of MTO participants continued to rely on housing assistance 10 to 15 years after the start of the demonstration. The Section 8 group experienced more instances of doubling up with friends and family than the control group did, which may indicate that being offered vouchers somehow contributes to housing instability, although this higher instance of doubling up was not found for the experimental group. The MTO demonstration did not affect homelessness (for example, living in a shelter or on the street), and whether the overall MTO participants’ share of homelessness at the time of the final impacts evaluation is more or less than expected is unknown. This area could be explored further.
In addition, even with such high shares of families continuing to use housing assistance, housing costs continue to be very high for all MTO participants, even those still receiving subsidies. One possible explanation is that the nation went through a housing boom that could have resulted in more low-poverty and traditional voucher holders staying in place and paying more out of pocket for rent.
Finally, some evidence suggests that MTO did result in more challenges for the experimental group in navigating the private market. Although families in the experimental group were more likely than families in the control group to pay rent on time, they were also more likely to make a tradeoff in paying their utilities late or not at all, which resulted in having the utilities turned off.
Again, this finding is consistent with other research on families moving from public housing to the private market and suggests a need for greater attention to helping voucher holders meet the costs of utilities in private-market units.
Authors Jennifer Comey is a senior research associate at the Urban Institute.
Susan J. Popkin is a senior fellow at the Urban Institute.
Kaitlin Franks is a research associate II at the Urban Institute.
References Briggs, Xavier de Souza, Jennifer Comey, and Gretchen Weisman. 2010. “Struggling To Stay Out of High-Poverty Neighborhoods: Housing Choice and Locations in Moving to Opportunity’s First Decade,” Housing Policy Debate 20 (3): 383–427.
Briggs, Xavier de Souza, Susan J. Popkin, and John Goering. 2010. Moving to Opportunity: The Story of an American Experiment To Fight Ghetto Poverty. New York: Oxford University Press.
Comey, Jennifer. 2004. An Improved Living Environment? Housing Quality Outcomes for HOPE VI Relocatees. Washington, DC: Urban Institute. Also available at http://www.urban.org/UploadedPDF/ 311058_Roof_2.pdf.
Evans, Gary W., Heidi Saltzman, and Janna L. Cooperman. 2001. “Housing Quality and Children’s Socioemotional Health,” Environment and Behavior 22 (3): 389–399.
Evans, Gary W., Nancy Wells, and Annie Moch. 2003. “Housing and Mental Health: A Review
of the Evidence and a Methodological and Conceptual Critique,” Journal of Social Issues 59 (3):
Finkel, Meryle, and Larry Buron. 2001. Study on Section 8 Voucher Success Rates. Vol. 1, Quantitative Study of Success Rates in Metropolitan Areas. Cambridge, MA: Abt Associates Inc.
Hunt, Sonja. 1993. “Damp and Mouldy Housing: A Holistic Approach.” In Unhealthy Housing, edited by Roger Burridge and David Ormandy. London, United Kingdom: Chapman and Hall: 69–93.