Affordable housing vouchers are intended to help families who need housing assistance have more choice in where they live. However, due to myriad factors including the state of the national rental market, Housing Choice Voucher (HCV) participants are more often than not concentrated in areas of high poverty. Furthermore, without access to data and the means to analyze it, the local housing authorities who administer these programs have little insight into the neighborhoods where their recipients live.
In early 2018, the U.S. Department of Housing and Urban Development (HUD) chose 24 housing authorities to use Small Area Fair Market Rents (SAFMR) for determining the payment standards for their voucher programs. Fair market rent designations—calculations of what is considered a reasonable rent in a designated area, based on market data—historically were based on a housing authority’s entire jurisdiction. This jurisdiction could be a county, a large city or a metropolitan area.
SAFMRs use ZIP codes to define smaller geographic areas. This allows for much more specificity in determining appropriate benefit levels for a given area.
SAFMRs were developed to make it possible for households using vouchers to move to more expensive “opportunity areas”—neighborhoods that have a higher median income, lower crime and higher quality schools, among other characteristics. Using more precise payment standards, the thinking went, housing vouchers could better equip families to find, and afford, quality housing. SAFMRs are one of several policy changes meant to promote mobility.
For such mobility programs to be effective, however, housing authorities must do more than change their payment standards. Designing mobility programs should involve a detailed assessment of where residents live and why. Housing authorities also need tools to assess program effectiveness and measure progress once policies are in place. Typically, while housing authorities have dozens of data points on each household, often the only tool available for data analysis is a spreadsheet.
Housing authorities can increase residents’ success in moving to opportunity neighborhoods by doing an in-depth analysis of their jurisdiction to identify neighborhoods that would provide the best environment for different populations. For example, seniors often prefer central neighborhoods near amenities and transportation, while families with young children often desire neighborhoods with good schools, low crime and greenspace.
While SAFMRs seek to approximate the quality of neighborhoods based on rental price, this factor alone does not indicate what constitutes a quality neighborhood for a resident. Because housing program participants have been concentrated in high poverty neighborhoods for so long, housing authorities may need to provide some guidance on which neighborhoods might best serve the particular needs of residents.
Based on our long-standing work in affordable housing, CGI has developed a data mapping software application to help housing authorities in these endeavors. The program imports all resident information from the HUD Form 50058, such as household size and income, and maps every unit in the HCV program against other data the housing authority chooses: for instance, amenities, school performance, crime rates, median income, and transportation. It allows housing authorities to make a visual analysis of both the concentration of their residents and the quality of the potential neighborhoods for mobility.
Over time, a housing authority also can use the program to see where residents have moved. It is a powerful tool for understanding resident concentration, mobility patterns and the effectiveness of policy changes, such as using SAFMRs.
My colleague Panos Kyprianou has recently written about the value of data in housing administration here. Read his blog for another perspective.