How do I cite the National Equity Atlas?
We encourage you to use the data and graphics from the National Equity Atlas, and ask that you cite the Atlas as your source. Here are recommended citations:
How do you define race/ethnicity? Can the data be further disaggregated for additional ethnic subgroups?
How do you define race/ethnicity? In the Atlas, categorization of people by race/ethnicity is generally based on individual responses to various census surveys. For most indicators, people are categorized into six mutually exclusive groups based on their response to two separate questions on race and Hispanic origin, plus one more category for all people of color combined. Further detail about each category is listed on our Methodology page.
There are some inherent challenges to examining indicators by race. We use self-reported racial and ethnic identifications from the U.S. Census. When possible, we provide data for the six major racial/ethnic categories within the Census (White, Black/African American, Hispanic/Latino, Asian/Pacific Islander, Native American, and Mixed/other race), creating mutually exclusive categories by grouping everyone who identifies as being of Hispanic origin in the Hispanic/Latino category. We also present data by nativity and racial/ethnic subgroups defined by ancestry for some indicators when the sample size is large enough (we do not present data when the sample size is less than 100). We sometimes consolidate all people of color into a single category (individuals who do not identify as non-Hispanic White) for specific data points or in cases where the sample size is not large enough to disaggregate the data for major racial/ethnic groups. An additional challenge we face is that the Census historically undercounts people of color—something that is important to recognize but not something we are able to effectively address.
Can the data be further disaggregated for additional ethnic subgroups? The short answer is yes—but it depends on the underlying sample size in the survey from which data is being drawn, and in the particular geography for which data is being reported. In May 2016, we began adding data for racial/ethnic subgroups defined by self-reported ancestry to some indicators. The addition of racial/ethnic subgroup data was driven by the lack of easily accessible data describing the socio-economic diversity within the Asian or Pacific Islander community, which has long been subject to a "model minority" stereotype that does not accurately describe the experience of many groups within the community. However, to provide a comprehensive picture of the diversity that exists within each of the major racial/ethnic categories that are included in the Atlas, we disaggregated the data by ancestry for five of them (all except for the Mixed/other category, for which we think a more appropriate disaggregation would be by the various racial/ethnic groups people identify with rather than by ancestry).
The data for racial/ethnic subgroups allows a user, for example, to examine data on equity indicators for the large Southeast Asian population in Fresno or the large Middle Eastern/North African population in Detroit—groups that are typically buried in the broader “Asian” and “White” Census categories, respectively. It is important to note, however, that due to sample size limitations, the detailed racial/ethnic subgroup data is only available for geographies with large enough populations of the subgroups being disaggregated.
Current indicators with data by ancestry include median wage, unemployment, the percentage of workers making $15/hour, working poor, disconnected youth, homeownership, and educational attainment.
Why does the Atlas focus on race/ethnicity? What about the other dimensions of inequity?
The Atlas provides extensive data about racial equity and inclusion to allow users to examine how well diverse groups can access the resources and opportunities they need to participate and prosper. Race is a social construct, not a biological one, and in an equitable society, there would not be major differences across racial groups. The differences we do see are primarily due to historical and ongoing policies, decisions, and institutional practices that have racially discriminatory impacts, whether intended or unintended.
We recognize that inequities exist across many characteristics in addition to race/ethnicity and nativity, including income, gender, age, ability, sexual orientation, and neighborhood. Unfortunately, because we are working with survey data and seek to provide data for metropolitan regions, we are limited to the extent to which we can disaggregate the data. We will seek to add additional layers of data to examine other dimensions of inequity as the Atlas evolves.
Where can I find data by ancestry? By gender?
Where can I find data by ancestry? Data by ancestry is available for the following indicators: Disconnected youth, Educational attainment, Homeownership, Median age, Unemployment, Wages: Median, Wages: $15/hour, and Working poor. The availability of data by ancestry depends on the underlying sample size in the survey from which data is being drawn, and in the particular geography for which data is being reported. For more information about how we categorize people by ancestry, see our Methodology.
By gender? Data by race and gender is available for the following indicators: Wages: $15/hr, Unemployment, Wages: Median, Working poor, Educational attainment, Disconnected youth, Car access, and Housing burden. Note that these data sources do not provide complete data on gender identity: the surveys only allow for male/female gender identity and do not allow respondents to identify themselves as non-binary or transgender.
Most indicators on the Atlas are measures of central tendency (e.g. means and medians) based on survey data, and are subject to a margin of error. While we do not report margins of error, we do make efforts to avoid reporting highly unreliable estimates. Unless otherwise noted, for all indicators derived from the Census and ACS summary files, we do not report values that are based on fewer than 100 (weighted) observations in the denominator/universe.
Why is data missing for certain race/ethnic groups in some regions?
While our equitable growth indicators database incorporates a variety of data sources, much of our analysis is based on a unique dataset created using microdata samples (i.e., “individual-level” data) from the Integrated Public Use Microdata Series (IPUMS) for five points in time: 1980, 1990, 2000, 2010, and 2013 through 2017 pooled together. The IPUMS microdata allows for the tabulation of detailed population characteristics, but because such tabulations are based on samples, they are subject to a margin of error and should be regarded as estimates—particularly in smaller regions and for smaller demographic subgroups. In an effort to avoid reporting highly unreliable estimates, we do not report any estimates that are based on a universe of fewer than 100 individual survey respondents.
Where can I find data on: the Native American population? People with disabilities? The LGBTQ community?
Where can I find data on the Native American population? Data on the Native American population is available for several indicators. For more information see our Tribal Nations section.
Do you have data on disability? We don't currently have any data for disabled people. We know that local advocates often need data to describe their demographic and economic realities. We will try to add more indicators to the Atlas overtime when possible.
Do you have any data for the LGBTQ community? We do not currently have any data for the LGBTQ community in the Atlas because this data is not collected in the data sources that we use. Per the above note on gender, this is an important correction needed and we advocate for including non-binary gender categories in surveys. We will add additional indicators to the Atlas over time and are looking for data by sexual orientation and gender identity, particularly for the transgender community. Please share suggestions for data sources with us at firstname.lastname@example.org.
Who can I contact with technical questions about the data and methodology?
We provide an overview of our overall methodological approach on our Methodology page, as well as a detailed methodological breakdown for each indicator on our Demographics, Economic Vitality, Readiness, Connectedness, Economic Benefits, and Equity Index Methodology pages. If you have additional questions about the data or methods, please contact Justin Scoggins, Data Manager at the Equity Research Institute, at email@example.com.
How often will the data be updated? Will you add more geographies (smaller regions, counties, census tracts, etc.)?
How often will the data be updated? Most of the datasets underlying the indicators in the National Equity Atlas are updated annually, so most of the indicators will be updated annually as well. We also add new indicators periodically. Once added, they will follow a similar updating schedule.
Will you add more geographies (smaller regions, counties, census tracts, etc.)? We know that local advocates often need data at smaller geographic levels, including counties and neighborhoods, to describe their demographic and economic realities. We are planning to add 400 large counties to the Atlas in 2020. Unfortunately, data is not available for sub-regional geographies for many of the economic indicators in the Atlas that are based on the decennial census and American Community Survey Public Use Microdata Samples (PUMS files, from IPUMS USA).
Can I download the underlying data?
Yes, you can. Our aim is to democratize data and make it available to you to explore and use. If you click on the downward facing arrow on each breakdown, you will find the option to download an excel sheet with the underlying data for the breakdown along with options to download an image or a Powerpoint presentation. If you would like access to other data, please email us at firstname.lastname@example.org detailing your request and plans for use, and we will try to package it for you.
Why does most data for 2019 represent a 2015-2019 average?
Many of the data points for 2019 are based on a pooled sample of five years of annual survey data (2015 through 2019) from the American Community Survey. Because a single year of the ACS data only covers about one percent of the U.S. population, five years of ACS data were pooled together to improve statistical reliability and to achieve a sample size that is comparable to that available in previous years (1980, 1990, 2000, 2010) which are based on the “long form” of the decennial census.
How are regions defined?
The Atlas currently includes the 150 largest metropolitan areas, or metros, based on their 2010 population. Metropolitan areas are based on the U.S. Office of Management and Budget’s December 2003 Core Based Statistical Area (CBSA) definitions. CBSAs include the county or counties or equivalent entities associated with at least one core urban area, plus adjacent counties having a high degree of social and economic integration with the core.
Why are there only 430 selectable counties?
When adding counties as selectable geography in the geographic drop-down menu for each indicator, our goal was to make sure that we could provide the same level of deeply disaggregated data (e.g. by race/ethnicity, gender, nativity and ancestry) that is available for all other selectable geographies on the Atlas. Given that most of this data stems from the decennial census and American Community Survey (ACS) microdata files from IPUMS USA, we only include counties that were identifiable 2019 5-year ACS microdata—the most recent data at the time counties were added. There are 430 such counties, all with larger populations of at least 100,000 people in 2010. While not all 430 counties are identifiable in earlier years of the microdata, and thus may be missing indicator data, they all had data in 2019 and we anticipate being able to update their data in the future. The 430 large counties are not exactly the most populous in the nation, they do include 89 of the 100 most populous in 2010 (those with at least 620,000 people) and account for 75 percent of all counties with at least 100,000 people in 2010.