All people need high-quality, reliable, and safe transportation to reach jobs, resources, and services. But that kind of transportation is not equally accessible to all.
In many cities, white, highly educated, and high-income residents have greater access to public transportation, and wealth differences by race and ethnicity make it easier for white residents to purchase a car, allowing for increased access to jobs. Public transit that is inaccessible for elderly people and people with disabilities can leave transit-dependent residents stranded. And a lack of transit options, particularly at off-peak hours, means that people who work irregular schedules often have no safe or affordable way to get to work.
Policymakers can reduce disparities in access to opportunity through targeted investments, but many decisionmakers lack clear definitions and measures of equity needed to make these choices. To inform stakeholders making transportation decisions, we created a set of metrics analyzing transportation equity for neighborhoods — which we approximate with census block groups — within four metropolitan regions: Baltimore, Maryland; Lansing, Michigan; Nashville, Tennessee; and Seattle, Washington. These regions represent four distinct types in terms of sprawl, fiscal health, transportation infrastructure, population growth, and housing costs.
For each, we calculated the time it takes residents across the metro area to get to opportunities such as jobs, schools, libraries, and hospitals via both public transit and automobile, and we used those times to create an access to opportunity measure. With these new metrics, we’ve highlighted disparities in access to jobs and analyzed how these opportunities differ by race and ethnicity and for night-shift workers.
Access to jobs varies by neighborhood
In the four metropolitan regions we studied, we found evidence of a mismatch between where low-wage workers live and which jobs they have access to via transportation, making it difficult for job seekers to find jobs and for employers to find employees (PDF). In the maps below, darker colors represent higher levels of spatial mismatch for low-wage job seekers, meaning that those neighborhoods have more low-wage workers and worse access to jobs than other neighborhoods in our analysis. These data, collected prior to COVID-19 related shutdowns, can help policymakers target resources to neighborhoods with the greatest need and identify which transit lines to reopen first to maximize equity as we recover from the pandemic.
In Seattle and Nashville, metro regions with high population growth, spatial mismatch for low-wage workers is most prevalent in the suburbs. In these type of cities, an influx of relatively high-income earners has led to a residential and employment resurgence and the gentrification of many historically low-income neighborhoods in the central city. Incumbent residents, especially low-income renters, have moved elsewhere in search of affordable housing, increasing typical commute times for low-income workers.
In metro regions such as Baltimore and Lansing, decades of population decline, suburban flight, and the loss of the manufacturing industry have led to the opposite problem: disinvestment in the urban core and a concentration of higher-income residents in the suburbs. This economic segregation, plus declining property values and construction obstacles, has impeded revitalization in these cities. As a result, the central city, which often bears the burden of funding transit, lacks the tax base to support an equitable transportation infrastructure.
In all four regions, more low-wage workers live in the suburbs than in the urban core. In Baltimore and Lansing, similar rates of job accessibility in the central city and the suburbs could explain this trend. But in Nashville and Seattle, even though job accessibility is much higher in the city core, more low-wage workers live in the suburbs, likely because of the high cost of living in the central city. As a result, all four cities have higher spatial mismatch in the suburbs than in the urban core.
Although Baltimore’s average mismatch rates are lower in the central city on average, significant disparities within the city exist. These disparities align with Baltimore’s “black butterfly,” the shape that segregated Black communities in Baltimore take across the eastern and western part of the city. Capital flow patterns that mirror the “black butterfly” could be partly to blame for the high rates of mismatch in these neighborhoods. Aggregate measures can conceal these neighborhood-level disparities, illustrating the importance of localized data for decisionmaking.
Equitable and high-quality transportation systems can help address these disparities and increase residents’ upward economic mobility. But transportation planners must consider that investments in transportation can sometimes cause increases in housing prices and gentrification, which can displace low-income communities. As such, leaders should enact land use and housing policies in tandem with transportation investments that ensure residents are able to remain in place.
A lack of public transit access hinders transit dependent workers’ ability to commute
Many Americans rely on public transit to get to work or other services, but neighborhoods throughout the country lack access to public transit, even at peak hours. And over 790,000 late-shift workers, who are disproportionately low-income people of color, rely on public transportation to get to work but have far fewer options. Average commute times for late-shift workers who take public transit are twice as long as those for workers with car access.
For workers in Lansing and Nashville, car-centric cultures have helped limit job accessibility via public transit. Even though the Capital Area Transportation Authority in Lansing offers bus routes and paratransit throughout the urban and rural areas of the metro region and the city was the first to adopt a non-motorized plan, suburban low-wage workers without a car still lack access to jobs concentrated in the central city. In Nashville, rapid population growth has increased traffic congestion, but a local belief that public transportation is unsafe has made new investments challenging.
Transit-dependent workers in Seattle and Baltimore have relatively high access to jobs via public transit. The Seattle region has one of the largest public transit systems in the country and therefore has relatively high access to jobs for low-wage workers via transit both during the day and at night, but region-specific challenges still pose issues for low-wage workers. In Seattle, a surge in its high-income population has created a lack of housing affordability near transit-rich areas, and in Baltimore, residential racial and income segregation makes connecting residents to amenities and opportunity points a challenge.
Some municipalities are considering new mobility technologies like ride sharing for flexible transportation services to serve low-income, transit-dependent late-shift workers. Others have expanded routes to serve late night and early morning workers, like King County and Seattle who partnered to create the “Night Owl bus service.” Although each region’s characteristics will define what improvements are needed, more services like these can ensure that late-shift workers have a safe, reliable way to get to work.
Our region is growing so fast... It’s a car culture so there’s a reluctance to pay more in taxes even though we are one of the lowest taxed areas, for our population, in the country.
Increasing access to public transit is also important for people with disabilities, who are often transit dependent. Adults with disabilities are twice as likely to have inadequate transportation as adults without disabilities, and transportation challenges cause over half a million people with disabilities to never leave their homes.
Across our four metro regions, very few transit agencies reported any information on wheelchair accessibility, and planners in each region reported that paratransit users felt restricted by the prescheduled pickups and wait times. More information is needed on the accessibility of transit systems because without it, local stakeholders will struggle to identify where investments are most needed.
People of color have less access to safe and affordable transportation
A history of racist planning and policy has shaped the contemporary US transportation landscape, starting with the rise of automobile ownership and the mass construction of federally funded interstate highways beginning in the 1950s. The federal government also subsidized the creation of the suburbs around that time, allowing white households to drive to jobs in the city, while income disparities and racially discriminative lending practices, such as redlining and racially restrictive covenants, restricted home purchase choices for many Black Americans.
Highway construction and ongoing urban renewal efforts from the 1930s to 1970s destroyed and displaced many Black neighborhoods, increasing segregation, isolation, crowding, and clustering of communities of color. In the early 2000s, the gentrification and influx of high-income residents back into many city centers subsequently pushed many low-income residents into car-dependent suburbs.
The residential patterns defined by structural racism are still prevalent today, and the wealth differences between people of color and white, non-Hispanic people give white residents increased housing choice, the ability to live in neighborhoods with higher-quality schools and resources, and a higher likelihood of car ownership. To understand how these disparities affect transportation equity, we looked at gaps in access to jobs for each of the four metropolitan regions broken down by race and ethnicity.
In Seattle and Baltimore, white, non-Hispanic residents are underrepresented in neighborhoods with high spatial mismatch, while Black and Hispanic residents are overrepresented. Displacement of communities of color to the suburbs in Seattle and patterns of racial segregation in the urban core of Baltimore could drive these disparities.
In Nashville and Lansing, the racial composition of high spatial mismatch neighborhoods largely reflect that of the region. Nashville’s large concentration of people of color in the central city where mismatch is the lowest may drive this uniformity by counteracting other factors that lead to worse access generally, whereas Lansing’s representativeness across neighborhoods may be driven by lower rates of racial segregation than most other cities.
Better data are needed to help increase transportation equity and access to opportunity
Civic and community leaders across each of our case study regions told us that equity is rarely at the forefront of decisionmaking; when it is, there is a lack of data to support policies that challenge the status quo. Without quality equity data, local leaders often end up prioritizing routes with high ridership instead of ensuring equitable service for all. Local leaders need data to help make difficult service decisions, and organizers and advocates need data to hold those leaders accountable to improvements in equity.
But data should not be the only input into decisionmaking. Metro-area leaders should make transportation and land use decisions through deep and meaningful community engagement, consulting historically overlooked communities of color, immigrants, and low-income households long before policies are proposed and at every stage of decisionmaking after a policy’s inception.
To some communities, particularly those who have been historically victimized by the transportation planning and decisionmaking process, the transportation system can be viewed as a weapon pointed directly at them.
Transportation policies can help reduce disparities in access to opportunity, but only if they are implemented with equity at the forefront. With these data and with meaningful engagement, communities can hold their leaders accountable and ensure that they center equity in transportation and land use decision making.
This feature uses transit data from the Transitland feed registry and road grid data from OpenStreetMap to calculate the drive and public transit times between all sets of block groups in our analysis using the open-source routing software OpenTripPlanner. We use INRIX’s 2019 Global Traffic Scorecard to incorporate traffic times and congestion data in our measurement of drive times.
We use census block group–level total jobs by job location and worker location aggregated from 2017 census block–level LEHD Origin-Destination Employment Statistics (LODES) residence area characteristics and workplace area characteristics files. For both files, we define low-wage jobs/workers as those with monthly earnings of $3,333 or less, a combination of the bottom two monthly earnings categories available in the data.
For demographic information, we use data from the 2014–18 American Community Survey (ACS) five-year estimates at the census block group level. Racial and ethnic groups are defined as Asian (both Hispanic and non-Hispanic); Black (both Hispanic and non-Hispanic); Hispanic; white (non-Hispanic); and other race (both Hispanic and non-Hispanic). Other race includes both Hispanic and non-Hispanic people who identify as American Indian and Alaska Native, Native Hawaiian and Other Pacific Islander, some other race, and two or more races as asked by the Census. This feature uses “Hispanic” to align with the language used in the ACS. We acknowledge this term may not be the preferred identifier, and we remain committed to employing inclusive language whenever possible.
For help using this tool or measuring transportation equity in your region, please contact [email protected] or [email protected].
For more information, please see our technical appendix.
This feature was funded in collaboration with the Mastercard Center for Inclusive Growth. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of our experts.
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RESEARCH Christina Stacy, Alena Stern, Kristin Blagg, Yipeng Su, Eleanor Noble, Macy Rainer, and Richard Ezike
DESIGN Christina Baird
DEVELOPMENT JoElla Carman and Jerry Ta
EDITING Fiona Blackshaw
WRITING Wesley Jenkins