By Michael Brenneis
Housing and transportation are the two biggest expenses for average households in the United States, and geographic location has a significant impact on these costs. But living in areas with affordable housing and transportation is not enough to assure that children will thrive. They must also have access to opportunity. A recent article on Harvard’s Data-Smart City Solutions blog drew our attention to a mapping project by Brandeis University researchers that began in 2016 with the purpose of examining the cost of opportunity and its spatial inequity for children of different racial and ethnic groups. Opportunity here refers to 19 indicators (p.19) of a neighborhood’s well-being such as poverty rate, unemployment rate, high school graduation rate, student proficiency, proximity to quality early childhood education centers, proximity to toxins, and several more.
The interactive maps proffer three indices that reflect cost, opportunity, and a cost-opportunity balance at the census tract level for 16 major metropolitan areas in the United States. On subsequent tabs the cost-opportunity balance score can be compared to the spatial distribution of children 18 years or younger from several racial and ethnic categories using the 2010 census.
The Location Affordability Index (LAI) was developed by the U.S. Department of Housing and Urban Development and U.S. Department of Transportation to combine housing and transportation costs into one index that could be used to “help consumers, policymakers, and developers make more informed decisions about where to live, work, and invest.” More detail regarding this index can be found in this report.
The Child Opportunity Index (COI) was developed collaboratively by Heller School for Social Policy and Management at Brandeis University and the Kirwan Institute for the Study of Race and Ethnicity. It uses indicators in three domains: educational opportunity; health and environmental opportunity; and social and economic opportunity. More detail about the various indicators, and the methodology for the calculation of the COI, can be found in this report.
The Cost-Opportunity Balance Score (COB) subtracts the COI from the LAI, based on this methodology.
The researchers also summarized the COB score for the 100 largest U.S. metropolitan areas. As shown in figure 1, generalized across these metro areas, only the Asian demographic group finds itself living where opportunity outweighs cost, all the others are located where cost outweighs opportunity, with the Black demographic group experiencing the largest imbalance, the White demographic group experiencing the smallest imbalance, and the Hispanic group located between the two.
There are limitations to the data used in the Brandeis maps. The LAI data represents three-member, single-parent, renter households with one commuter and incomes of 50 percent of the metro area median income. According to the researchers, “The tool is designed and intended for the purposes of describing regional (in)equity patterns in the affordability of neighborhood opportunity for children, and for communicating findings to interested audiences and stakeholders.” The picture represented in the maps may change somewhat should different household profiles be used. Also, the LAI and COI indices are based on data from 2007-2013 and represent a snapshot taken during this period. The census tract geography here is considered to be equivalent to neighborhoods, giving a regional picture, but is not fine-grained enough to make small-scale observations. A recent map published online by the National Geographic Society examines the racial make-up of the U.S. at a more detailed, census block level.
Residing in areas of high opportunity can be costly. But living at a distance from jobs and other necessities of life can have costs as well. Long commutes and remote amenities can reduce housing costs while increasing transportation costs. And for underserved populations the difference, as shown on many of these maps, is striking.
Story maps and choropleths are useful tools to bring data to decision makers and the general public who may or may not have the skills to digest tables and statistics. For many, meaning can easily be extracted from spatial data when skillfully laid out on interactive maps such as these.
Michael Brenneis is an Associate Researcher at SSTI.
By Michael Brenneis