Reconnecting America graded every one of the 366 metro areas based on how they measure up to our vision of complete communities:
Reconnecting America collected data to understand the existing condition of our regions and track progress at the regional level in all 366 Metropolitan Statistical Areas (MSAs) in the country.
Why these particular indicators? We researched and debated and narrowed our original list of indicators from hundreds down to 33 individual data points. There are other elements of complete communities that we would have liked to have included, but did not, for a couple of reasons.
In some cases, we couldn’t find indicators at the right scale, or what we could find only measured some of the 366 metropolitan regions that we analyzed. We did make a few exceptions to this rule, because we wanted to include work that others had done for the top 100 metros. School quality was one indicator that we knew would be difficult to quantify at the regional scale and that we hope will be studied more in the future. Neighborhood safety and security are also difficult to define regionally but are key to supporting infill growth. We want this conversation to continue. Let us know what indicators you would like to see in the future.
Why the region? We chose to grade places at the regional scale, rather than the city or county because, ultimately, efforts to improve individual neighborhoods must trickle up to change regional performance. We believe that successful coordination of transportation and land use happens at the regional scale, and we also wanted to make sure that we recognized the important role that suburbs will continue to play in our metropolitan areas. To be technical, we used the census-defined “Metropolitan Statistical Areas.”
Transit access: Several indicators are about having people, or jobs, etc. “near fixed-guideway transit.” The TOD database (CTOD) is one source of information for these data points, which we used in this report. We also calculated these data points ourselves in some cases. To do that, we utilized a database of all existing fixed-guideway transit stations (including various forms of rail, bus rapid transit and ferry service) collected by CTOD. “Near transit” is defined as within a half-mile.
Opportunity areas were calculated by combining information on block size and intensity (total number of residents and workers) in a census tract. National and international research shows that the density (or intensity) needed to support the most basic transit service is about seven dwelling units an acre, or about 14 people an acre. Higher densities support more frequent, higher quality transit service. Similarly, research shows that when blocks are about six acres in size or less, people are more willing to walk and bike.
These inputs were combined to create an index that identified which tracts in metropolitan areas would be classified as opportunity areas. For a tract to qualify, it needed to have a ratio of intensity to block size of 2.0 or less. In practical terms, this means that a tract with larger blocks, but more people, would qualify because the intensity of people living there could make transit service possible. Likewise, a tract with fewer people but very small blocks would also qualify because the small blocks would make it easier for people to choose to walk or bike.
Percent of households near fixed-guideway transit: A combination of the updated TOD database created by CTOD and GIS analysis. The GIS analysis utilized the CTOD database of all existing fixed-guideway transit stations and household data from the U.S. Census American community Survey 2005-2009.
Percent of households in opportunity areas: Using the tracts defined as opportunity areas and the American community Survey 2005-2009, the number of households living in each opportunity area in the region was calculated.
Percent of households near fixed-guideway transit who are low income: low income was defined as 80 percent of the Area Median Income (AMI), or the median income of the MSA. Using demographic data from the American community Survey 2005-2009, we calculated the share of households making 80 percent AMI or below and living within a half-mile of a fixed-guideway transit.
Percent of households in opportunity areas who are low income: Same definition of low income as above, and the opportunity area geography.
Percent of Section 8/202 units near fixed-guideway transit: The location of Section 8 and Section 202 units was obtained from HUDUSER, HUD’s data sharing website. These locations were geocoded in GIS and the units within a half-mile of fixed-guideway transit calculated.
Percent of Section 8/202 units in opportunity areas: The location of Section 8 and Section 202 units was obtained from HUDUSER, and those units in opportunity areas calculated in GIS.
Growth in opportunity areas compared to the region: Using census 2000 and American community Survey 2005-2009 household information, the population growth in opportunity areas was compared to the population growth in each MSA overall. A “location quotient” was calculated to identify the regions growing at different rates in opportunity areas compared to the MSA, and regions were ranked based on that number.
Percent of jobs near existing fixed-guideway transit: Using data provided by the U.S. census through the longitudinal employer-household dynamics (2010), Reconnecting America calculated the share of jobs near existing fixed-guideway stations (CTOD’s transit station database.)
Percent of jobs near planned fixed-guideway transit: In the 2011 report “Transit Space Race”, Reconnecting America identified regions planning new transit investments and geocoded the locations of stations when that information was available. Then the jobs near these proposed stations (excluding those not already near existing stations) were calculated using the longitudinal employer-household dynamics (2010).
Percent of jobs accessible by transit (within a 45 minute commute): This metric was taken from the Brookings Institution’s “Missed Opportunities” report, which calculated the share of jobs accessible by transit within a 45 minute commute.
Percent of jobs in opportunity areas: Using the opportunity area geographies and the longitudinal employer-household dynamics (2010), Reconnecting America calculated the share of jobs within each MSA that are located in opportunity areas.
Weighted employment density: The Public Policy Institute of California (PPIC) calculated the employment density of most metropolitan regions within the U.S. For more information on PPIC’s research on the connection between jobs and transit, read their February 2011 report, “Making the Most of Transit: density, employment growth, and Ridership around new Stations.”
Percent of 18- to 34-year-olds with a college degree: Using American community Survey 2005-2009 data, Reconnecting America calculated the share of 18- to 34-year-olds who have obtained a degree from a four-year college.
Percent of low- and moderate-income jobs accessible on transit (within a 90 minute commute): Again, the Brookings Institution’s “Missed Opportunities” report provided this indicator, the share of low and moderate-income jobs accessible within a 90- minute commute.
Number of fixed-guideway transit stations: The number of existing transit stations was taken from the database of all fixed-guideway transit stations maintained by CTOD.
Number of future fixed-guideway transit stations: Future transit stations were identified in the 2011 “Transit Space Race” report by Reconnecting America.
Percent of fixed-guideway transit stations in opportunity areas: calculated using GIS and identifying how many existing fixed-guideway transit stations are located in opportunity areas in each MSA.
Percent of commuters who take transit: American community Survey 2005-2009 by MSA.
Change in number of commuters who take transit: comparing census 2000 to American community Survey 2005-2009 data.
Pedestrian danger Index: Transportation for America created a Pedestrian danger Index as part of its “dangerous by design” report.
Percent of commuters who walk or bike: American community Survey 2005-2009 by MSA.
Percent of blocks smaller than 6 acres: Reconnecting America using U.S. census Tiger files and calculated the area of each block in each MSA using GIS. The share of blocks smaller than six acres was then calculated.
Average vehicle miles traveled per household: The center for neighborhood Technology’s H+T Index also includes information on the average number of vehicle miles traveled per household.
Both the percent of low-income households more than a mile from a grocery store and the percent of households with no car more than a mile from a grocery store were taken from the USDA’s Food environment Atlas.
Percent of opportunity areas in food deserts: The USDA has created a Food desert locator and makes the tracts they have identified as food deserts available on their website. Reconnecting America compared these tracts to the opportunity areas and identified where there was overlap.
Number of fast food establishments for every healthy one: The USDA Food Atlas provided this data.
Percent of population getting no regular physical activity: The centers for disease control and Prevention collects survey data on the amount of activity residents in counties across the U.S. are receiving. The “inactivity rate” is based on those who respond to the survey saying they get no activity outside of work during the week.
Percent of households who live near parks: calculated in GIS using American community Survey 2005-2009 data. “Near” a park is defined as being within a half-mile.
Percent of the households near parks who are low income: Using 80 percent AMI as the definition of low income, Reconnecting America used GIS to calculate the share of low-income households within a half-mile of a park.
Acres of parks for every household (in opportunity areas): Reconnecting America used GIS to calculate the acreage of parks in or bordering opportunity areas and then calculated the ratio or households living in opportunity areas to the acres of parks.
Employees in Arts and entertainment Jobs: Using U.S. census county business Patterns data, Reconnecting America calculated the number of jobs in artistic industries in each MSA per 1,000 people.
Gallup Healthways Well-being Index: Gallup’s Well-being index provided this ranking of the top 100 metro regions.
The grades are a composite of these indicators. First, Reconnecting America divided regions into three categories by size (under 500,000, between 500,000 and 3 million, and over 3 million.) This was done so regions would be graded compared to the performance of their peers.
Then, each metric was ranked within its size category. Regions in the top quartile (top 25%) received four points for that indicator, in the second quartile, three points, in the third quartile, two points, and in the first quartile, one point. A region could get zero points for an indicator if it had absolutely no progress to show. For example, regions with no opportunity areas received a zero for households living in opportunity areas.
A region could also be exempt from a particular indicator (and not penalized by receiving a zero), if there was data missing. (For example, the Brookings Institution’s “Missed Opportunities” report only analyzed the top 100 metro regions – not all 366.) A region could also be exempt from receiving a zero if it already received a zero for a related indicator. (For example, if a region had no households near opportunity areas, it was not also penalized for having no low-income households near opportunity areas.) Regions with “exempt” indicators received an “N/A” which was not calculated into the overall average.
In some cases, the indicators shared similar components. (For example, share of existing jobs near transit, share of future jobs near transit, and share of jobs accessible by transit within a 90 minute commute). In these cases, Reconnecting America averaged those similar indicators first, and then combined them with the independent indicators in the next step.
Once every indicator had been assigned a score, the scores were averaged together to give a composite score ranging from 0 to 4. The regions with the highest scores got an A, the regions with the lowest scores a D.