Data and Methods

Equitable Growth Indicators Database

The Atlas draws its data from a unique equitable growth indicators database developed by PolicyLink and PERE. This database incorporates hundreds of data points from public and private data sources for the 100 largest cities, the 150 largest metropolitan regions, all 50 states, and the United States. It includes historical data for several economic indicators as well as demographic projections through 2040. Our database has several defining attributes: it incorporates measures of economic growth and social equity, it provides several decades of data for cities and metropolitan regions that are geographically consistent over time, and it includes data disaggregated by race/ethnicity for most indicators.

Our data sources include the Integrated Public Use Microdata System (IPUMS)U.S. Census BureauGeolytics; Woods & Poole EconomicsU.S. Bureau of Economic AnalysisU.S. Bureau of Labor StatisticsCenters for Disease Control and Prevention, and the National Center for Education Statistics. We also include the Georgetown Center on Education and the Workforce’s state-level projections of the educational requirements of jobs in 2020 (and thank Tony Carnevale and Nicole Smith for graciously sharing their data).

Equity Indicators Framework

The Atlas uses an indicators framework we’ve developed for measuring equitable growth in regions. We define an equitable region as one where all residents — regardless of their race/ethnicity or nativity, neighborhood of residence, or other characteristics — are fully able to participate in their region’s economic vitality, contribute to their region’s readiness for the future, and connect to their region’s assets and resources. Our framework includes three types of indicators.

  • Demographics describe who lives in the region and how this is changing.
  • Equity indicators are broken out into three categories:
    • Economic vitality: Is the economy growing in a way that is inclusive and sustainable? (Current indicators include GDP and job growth, unemployment, wages, inequality, and income growth)
    • Readiness: Is the region ready for the future, with a skilled, prepared workforce; educated young population; and healthy residents? (Indicators include educational attainment in relation to job skills requirements in 2020, disconnected youth, and overweight/obesity)
    • Connectedness: Can residents access the essential ingredients to live healthy and productive lives in their own neighborhoods, reach opportunities located throughout the region, and interact with other diverse residents? (Indicators include housing burden, vehicle access, and neighborhood poverty)
  • Economic benefits of equity indicators quantify the benefits of racial and economic inclusion to the broader economy. (Current indicators include the potential GDP and income gains from closing the racial income gap)

Frequently Asked Questions

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:

  • For policy briefs/websites/blogs/popular press: PolicyLink/PERE, National Equity Atlas, www.nationalequityatlas.org.
  • For journal articles/academic papers: PolicyLink and the USC Program for Environmental and Regional Equity; National Equity Atlas, www.nationalequityatlas.org, 2016.


Why does the Atlas focus on race/ethnicity/nativity? 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.

Which racial/ethnic groups are included in the Atlas?

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.

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 four points in time: 1980, 1990, 2000, and 2008 through 2012 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.

Who can I contact with technical questions about the data and methodology?

Our comprehensive data and methods technical documentation can be found here. If you have additional questions about the data or methods, please contact Justin Scoggins, Data Manager at PERE, at info@nationalequityatlas.org.

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 will also add new indicators periodically. Once added, they will follow a similar updating schedule.

Can I download the underlying data?

Our aim is to democratize data and make it available to you to explore and use. As we produce analyses of the indicators in the Atlas, we will share the underlying data spreadsheets. Currently, you can download the data from our Equity Solution brief here. If you would like access to other data, please email us at info@nationalequityatlas.org detailing your request and plans for use, and we will try to package it for you.

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 (see Census definition here). A list of the counties included in each CBSA can be found here.

Will you add more geographies (smaller regions, cities, counties, census tracts, etc.)?

We know that local advocates often need data at smaller geographic levels, including cities and neighborhoods, to describe their demographic and economic realities. We will try to add these smaller geographies to the Atlas over time when possible. We are currently in the process of gathering city and county data for some number of indicators, and plan to add census-tract level maps illustrating differences across the neighborhoods within regions for several indicators. But please note that data is not available for sub-regional geographies for many of the economic indicators in the Atlas that are based on the American Community Survey Public Use Microdata (PUMS).

Why does most data for 2012 represent a 2008-2012 average?

Many of the data points for 2012 are based on a pooled sample of five years of annual survey data (2008 through 2012) 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, and 2000) which are based on the “long form” of the decennial census.

Technical Documentation

Additional information about the estimation techniques and adjustments made in creating the underlying database can be found in this Data and Methods document.

The 100 Largest Cities

Below are the cities currently included in the Atlas, as defined by the 2010 Census.

Albuquerque City, NM
Anaheim City, CA
Anchorage Municipality, AK
Arlington City, TX
Atlanta City, GA
Aurora City, CO
Austin City, TX
Bakersfield City, CA
Baltimore City, MD
Baton Rouge City, LA
Birmingham City, AL
Boston City, MA
Buffalo City, NY
Chandler City, AZ
Charlotte City, NC
Chesapeake City, VA
Chicago City, IL
Chula Vista City, CA
Cincinnati City, OH
City and County of Honolulu, HI
Cleveland City, OH
Colorado Springs City, CO
Columbus City, OH
Corpus Christi City, TX
Dallas City, TX
Denver City, CO
Detroit City, MI
Durham City, NC
El Paso City, TX
Fort Wayne City, IN
Fort Worth City, TX
Fremont City, CA
Fresno City, CA
Garland City, TX
Glendale City, AZ
Greensboro City, NC
Henderson City, NV
Hialeah City, FL
Houston City, TX
Indianapolis City (balance), IN
Irvine City, CA
Irving City, TX
Jacksonville City, FL
Jersey City City, NJ
Kansas City City, MO
Laredo City, TX
Las Vegas City, NV
Lexington-Fayette urban county, KY
Lincoln City, NE
Long Beach City, CA
Los Angeles City, CA
Louisville/Jefferson County metro government (balance), KY
Lubbock City, TX
Madison City, WI
Memphis City, TN
Mesa City, AZ
Miami City, FL
Milwaukee City, WI
Minneapolis City, MN
Nashville-Davidson (balance), TN
New Orleans City, LA
New York City, NY
Newark City, NJ
Norfolk City, VA
North Las Vegas City, NV
Oakland City, CA
Oklahoma City City, OK
Omaha City, NE
Orlando City, FL
Philadelphia City, PA
Phoenix City, AZ
Pittsburgh City, PA
Plano City, TX
Portland City, OR
Raleigh City, NC
Reno City, NV
Riverside City, CA
Rochester City, NY
Sacramento City, CA
San Antonio City, TX
San Bernardino City, CA
San Diego City, CA
San Francisco City, CA
San Jose City, CA
Santa Ana City, CA
Scottsdale City, AZ
Seattle City, WA
Spokane City, WA
St. Louis City, MO
St. Paul City, MN
St. Petersburg City, FL
Stockton City, CA
Tampa City, FL
Toledo City, OH
Tucson City, AZ
Tulsa City, OK
Virginia Beach City, VA
Washington, DC
Wichita City, KS
Winston-Salem City, NC

The 150 Largest Metropolitan Regions

Below are the metros currently included in the Atlas, with their component counties, parishes, municipalities, or boroughs, as defined defined by the Office of Management and Budget (2003) here.

Akron, OH: Portage, Summit
Albany-Schenectady-Troy, NY: Albany, Rensselaer, Saratoga, Schenectady, Schoharie
Albuquerque, NM: Bernalillo, Sandoval, Torrance, Valencia
Allentown-Bethlehem-Easton, PA-NJ: Carbon, Lehigh, Northampton, Warren (NJ)
Anchorage, AK: Anchorage Municipality, Matanuska-Susitna Borough
Ann Arbor, MI: Washtenaw
Asheville, NC: Buncombe, Haywood, Henderson, Madison
Atlanta-Sandy Springs-Marietta, GA: Barrow, Bartow, Butts, Carroll, Cherokee, Clayton, Cobb, Coweta, Dawson, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Haralson, Heard, Henry, Jasper, Lamar, Meriwether, Newton, Paulding, Pickens, Pike, Rockdale, Spalding, Walton
Augusta-Richmond County, GA-SC: Burke, Columbia, McDuffie, Richmond, Aiken (SC), Edgefield (SC)
Austin-Round Rock, TX: Bastrop, Caldwell, Hays, Travis, Williamson
Bakersfield, CA: Kern
Baltimore-Towson, MD: Anne Arundel, Baltimore, Carroll, Harford, Howard, Queen Anne, Baltimore City
Baton Rouge, LA: Ascension, East Baton Rouge, East Feliciana, Iberville, Livingston, Pointe Coupee, St. Helena, West Baton Rouge, West Feliciana
Beaumont-Port Arthur, TX: Hardin, Jefferson, Orange
Birmingham-Hoover, AL: Bibb, Blount, Chilton, Jefferson, St. Clair, Shelby, Walker
Boise City-Nampa, ID: Ada, Boise, Canyon, Gem, Owyhee
Boston-Cambridge-Quincy, MA-NH: Norfolk, Plymouth, Suffolk, Middlesex, Essex, Rockingham (NH), Strafford (NH)
Bridgeport-Stamford-Norwalk, CT: Fairfield
Brownsville-Harlingen, TX: Cameron
Buffalo-Niagara Falls, NY: Erie, Niagara
Canton-Massillon, OH: Carroll, Stark
Cape Coral-Fort Myers, FL: Lee
Charleston-North Charleston, SC: Berkeley, Charleston, Dorchester
Charlotte-Gastonia-Concord, NC-SC: Anson, Cabarrus, Gaston, Mecklenburg, Union, York (SC)
Chattanooga, TN-GA: Hamilton, Marion, Sequatchie, Catoosa (GA), Dade (GA), Walker (GA)
Chicago-Naperville-Joliet, IL-IN-WI: Cook, DeKalb, DuPage, Grundy, Kane, Kendall, Lake, McHenry, Will, Jasper (IN), Lake (IN), Newton (IN), Porter (IN), Kenosha (WI)
Cincinnati-Middletown, OH-KY-IN: Brown, Butler, Clermont, Hamilton, Warren, Dearborn (IN), Franklin (IN), Ohio (IN), Boone (KY), Bracken (KY), Campbell (KY), Gallatin (KY), Grant (KY), Kenton (KY), Pendleton (KY)
Cleveland-Elyria-Mentor, OH: Cuyahoga, Geauga, Lake, Lorain, Medina
Colorado Springs, CO: El Paso, Teller
Columbia, SC: Calhoun, Fairfield, Kershaw, Lexington, Richland, Saluda
Columbus, OH: Delaware, Fairfield, Franklin, Licking, Madison, Morrow, Pickaway, Union
Corpus Christi, TX: Aransas, Nueces, San Patricio
Dallas-Fort Worth-Arlington, TX: Collin, Dallas, Delta, Denton, Ellis, Hunt, Kaufman, Rockwall, Johnson, Parker, Tarrant, Wise
Davenport-Moline-Rock Island, IA-IL: Henry, Mercer, Rock Island, Scott
Dayton, OH: Greene, Miami, Montgomery, Preble
Deltona-Daytona Beach-Ormond Beach, FL: Volusia
Denver-Aurora, CO: Adams, Arapahoe, Broomfield, Clear Creek, Denver, Douglas, Elbert, Gilpin, Jefferson, Park
Des Moines, IA: Dallas, Guthrie, Madison, Polk, Warren
Detroit-Warren-Livonia, MI: Wayne, Lapeer, Livingston, Macomb, Oakland, St. Clair
Durham, NC: Chatham, Durham, Orange, Person
El Paso, TX: El Paso
Eugene-Springfield, OR: Lane
Evansville, IN-KY: Gibson, Posey, Vanderburgh, Warrick, Henderson (KY), Webster (KY)
Fayetteville, NC: Cumberland, Hoke
Fayetteville-Springdale-Rogers, AR-MO: Benton, Madison, Washington, McDonald (MO)
Flint, MI: Genesee
Fort Wayne, IN: Allen, Wells, Whitley
Fresno, CA: Fresno
Grand Rapids-Wyoming, MI: Barry, Ionia, Kent, Newaygo
Greensboro-High Point, NC: Guilford, Randolph, Rockingham
Greenville, SC: Greenville, Laurens, Pickens
Harrisburg-Carlisle, PA: Cumberland, Dauphin, Perry
Hartford-West Hartford-East Hartford, CT: Hartford, Middlesex, Tolland
Hickory-Lenoir-Morganton, NC: Alexander, Burke, Caldwell, Catawba
Honolulu, HI: Honolulu
Houston-Baytown-Sugar Land, TX: Austin, Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, San Jacinto, Waller
Huntsville, AL: Limestone, Madison
Indianapolis, IN: Boone, Brown, Hamilton, Hancock, Hendricks, Johnson, Marion, Morgan, Putnam, Shelby
Jackson, MS: Copiah, Hinds, Madison, Rankin, Simpson
Jacksonville, FL: Baker, Clay, Duval, Nassau, St. Johns
Kalamazoo-Portage, MI: Kalamazoo, Van Buren
Kansas City, MO-KS: Bates, Caldwell, Cass, Clay, Clinton, Jackson, Lafayette, Platte, Ray, Franklin (KS), Johnson (KS), Leavenworth (KS), Linn (KS), Miami (KS), Wyandotte (KS)
Killeen-Temple-Fort Hood, TX: Bell, Coryell, Lampasas
Knoxville, TN: Anderson, Blount, Knox, Loudon, Union
Lakeland, FL: Polk
Lancaster, PA: Lancaster
Lansing-East Lansing, MI: Clinton, Eaton, Ingham
Las Vegas-Paradise, NV: Clark
Lexington-Fayette, KY: Bourbon, Clark, Fayette, Jessamine, Scott, Woodford
Little Rock-North Little Rock, AR: Faulkner, Grant, Lonoke, Perry, Pulaski, Saline
Los Angeles-Long Beach-Santa Ana, CA: Los Angeles, Orange County
Louisville, KY-IN: Bullitt, Henry, Jefferson, Meade, Nelson, Oldham, Shelby, Spencer, Trimble, Clark (IN), Floyd (IN), Harrison (IN), Washington (IN)
Madison, WI: Columbia, Dane, Iowa
Manchester-Nashua, NH: Hillsborough
McAllen-Edinburg-Pharr, TX: Hidalgo
Memphis, TN-MS-AR: Fayette, Shelby, Tipton, Crittenden (AR), DeSoto (MS), Marshall (MS), Tate (MS), Tunica (MS)
Miami-Fort Lauderdale-Miami Beach, FL: Broward, Miami-Dade, Palm Beach
Milwaukee-Waukesha-West Allis, WI: Milwaukee, Ozaukee, Washington, Waukesha
Minneapolis-St. Paul-Bloomington, MN-WI: Anoka, Carver, Chisago, Dakota, Hennepin, Isanti, Ramsey, Scott, Sherburne, Washington, Wright, Pierce (WI), St. Croix (WI)
Mobile, AL: Mobile
Modesto, CA: Stanislaus
Montgomery, AL: Autauga, Elmore, Lowndes, Montgomery
Naples-Marco Island, FL: Collier
Nashville-Davidson-Murfreesboro, TN: Cannon, Cheatham, Davidson, Dickson, Hickman, Macon, Robertson, Rutherford, Smith, Sumner, Trousdale, Williamson, Wilson
New Haven-Milford, CT: New Haven
New Orleans-Metairie-Kenner, LA: Jefferson, Orleans, Plaquemines, St. Bernard, St. Charles, St. John the Baptist, St. Tammany
New York-Northern New Jersey-Long Island, NY-NJ-PA: Bronx, Kings, New York, Putnam, Queens, Richmond, Rockland, Westchester, Middlesex, Monmouth, Ocean, Somerset, Nassau, Suffolk, Bergen (NJ), Hudson (NJ), Passaic (NJ), Essex (NJ), Hunterdon (NJ), Morris (NJ), Sussex (NJ), Union (NJ), Pike (PA)
Ocala, FL: Marion
Ogden-Clearfield, UT: Davis, Morgan, Weber
Oklahoma City, OK: Canadian, Cleveland, Grady, Lincoln, Logan, McClain, Oklahoma
Omaha-Council Bluffs, NE-IA: Harrison, Mills, Pottawattamie, Cass (NE), Douglas (NE), Sarpy (NE), Saunders (NE), Washington (NE)
Orlando, FL: Lake, Orange, Osceola, Seminole
Oxnard-Thousand Oaks-Ventura, CA: Ventura
Palm Bay-Melbourne-Titusville, FL: Brevard
Pensacola-Ferry Pass-Brent, FL: Escambia, Santa Rosa
Peoria, IL: Marshall, Peoria, Stark, Tazewell, Woodford
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD: Burlington, Camden, Gloucester, Bucks, Chester, Delaware, Montgomery, Philadelphia, New Castle (DE), Cecil (MD), Salem (NJ)
Phoenix-Mesa-Scottsdale, AZ: Maricopa, Pinal
Pittsburgh, PA: Allegheny, Armstrong, Beaver, Butler, Fayette, Washington, Westmoreland
Port St. Lucie-Fort Pierce, FL: Martin, St. Lucie
Portland-South Portland-Biddeford, ME: Cumberland, Sagadahoc, York County
Portland-Vancouver-Beaverton, OR-WA: Clackamas, Columbia, Multnomah, Washington, Yamhill, Clark (WA), Skamania (WA)
Poughkeepsie-Newburgh-Middletown, NY: Dutchess, Orange
Providence-New Bedford-Fall River, RI-MA: Bristol (MA), Bristol, Kent, Newport, Providence, Washington
Provo-Orem, UT: Juab, Utah
Raleigh-Cary, NC: Franklin, Johnston, Wake
Reading, PA: Berks
Reno-Sparks, NV: Storey, Washoe
Richmond, VA: Amelia, Caroline, Charles City, Chesterfield, Cumberland, Dinwiddie, Goochland, Hanover, Henrico, King and Queen, King William, Louisa, New Kent, Powhatan, Prince George, Sussex, Colonial Heights city, Hopewell city, Petersburg city, Richmond city
Riverside-San Bernardino-Ontario, CA: Riverside, San Bernardino
Rochester, NY: Livingston, Monroe, Ontario, Orleans, Wayne
Rockford, IL: Boone, Winnebago
Sacramento-Arden-Arcade-Roseville, CA: El Dorado, Placer, Sacramento, Yolo
Salem, OR: Marion, Polk
Salinas, CA: Monterey
Salt Lake City, UT: Salt Lake, Summit, Tooele
San Antonio, TX: Atascosa, Bandera, Bexar, Comal, Guadalupe, Kendall, Medina, Wilson
San Diego-Carlsbad-San Marcos, CA: San Diego
San Francisco-Oakland-Fremont, CA: Alameda, Contra Costa, Marin, San Francisco, San Mateo
San Jose-Sunnyvale-Santa Clara, CA: San Benito, Santa Clara
Santa Barbara-Santa Maria-Goleta, CA: Santa Barbara
Santa Rosa-Petaluma, CA: Sonoma County
Sarasota-Bradenton-Venice, FL: Manatee, Sarasota
Savannah, GA: Bryan, Chatham, Effingham
Scranton-Wilkes-Barre, PA: Lackawanna, Luzerne, Wyoming
Seattle-Tacoma-Bellevue, WA: King County, Snohomish, Pierce
Shreveport-Bossier City, LA: Bossier, Caddo, De Soto
South Bend-Mishawaka, IN-MI: St. Joseph, Cass (MI)
Spokane, WA: Spokane
Springfield, MA: Franklin, Hampden, Hampshire
Springfield, MO: Christian, Dallas, Greene, Polk, Webster
St. Louis, MO-IL: Crawford (partial: Sullivan City), Franklin, Jefferson, Lincoln, St. Charles, St. Louis, Warren, Washington, St. Louis city, Bond (IL), Calhoun (IL), Clinton (IL), Jersey (IL), Macoupin (IL), Madison (IL), Monroe (IL), St. Clair (IL)
Stockton, CA: San Joaquin
Syracuse, NY: Madison, Onondaga, Oswego
Tallahassee, FL: Gadsden, Jefferson, Leon, Wakulla
Tampa-St. Petersburg-Clearwater, FL: Hernando, Hillsborough, Pasco, Pinellas
Toledo, OH: Fulton, Lucas, Ottawa, Wood
Trenton-Ewing, NJ: Mercer
Tucson, AZ: Pima
Tulsa, OK: Creek, Okmulgee, Osage, Pawnee, Rogers, Tulsa, Wagoner
Vallejo-Fairfield, CA: Solano
Virginia Beach-Norfolk-Newport News, VA-NC: Currituck, Gloucester, Isle of Wight, James City, Mathews, Surry, York , Chesapeake city, Hampton city, Newport News city, Norfolk city, Poquoson city, Portsmouth city, Suffolk city, Virginia Beach city, Williamsburg city
Visalia-Porterville, CA: Tulare
Washington-Arlington-Alexandria, DC-VA-MD-WV: District of Columbia, Frederick (MD), Montgomery (MD), Calvert County (MD), Charles County (MD), Prince George's (MD), Arlington (VA), Clarke (VA), Fairfax (VA), Fauquier (VA), Loudoun (VA), Prince William (VA), Spotsylvania (VA), Stafford (VA), Warren (VA), Alexandria city, (VA), Fairfax city (VA), Falls Church city (VA), Fredericksburg city (VA), Manassas city (VA), Manassas Park city, (VA), Jefferson (WV)
Wichita, KS: Butler, Harvey, Sedgwick, Sumner
Wilmington, NC: Brunswick, New Hanover, Pender
Winston-Salem, NC: Davie, Forsyth, Stokes, Yadkin
Worcester, MA: Worcester
York-Hanover, PA: York
Youngstown-Warren-Boardman, OH-PA: Mahoning, Trumbull, Mercer (PA) 

Indicators in the National Equity Atlas

Demographics

  • Detailed race/ethnicity
  • People of color
  • Race/ethnicity
  • Population growth rates
  • Contribution to growth: Immigrants (added March 6, 2014)
  • Contribution to growth: People of color
  • Racial generation gap
  • Diversity Index (added March 6, 2014)
  • Median age (added April 29, 2015)

Economic Vitality

  • Poverty (added June 28, 2016)
  • Working poor (added June 28, 2016)
  • Unemployment
  • Wages: Median
  • Wages: $15/hr (added March 6, 2014)
  • Income growth
  • Job and wage growth
  • Job and GDP growth
  • Income inequality: Gini
  • Income inequality: 95/20 ratio (added March 6, 2014)
  • Homeownership

Readiness

  • School poverty (added February 26, 2016)
  • Air pollution: Exposure index (added March 4, 2016)
  • Air pollution: Unequal burden (added March 4, 2016)
  • Education levels and job requirements
  • Disconnected youth
  • Overweight and obese
  • Asthma (added April 29, 2015)
  • Diabetes (added April 29, 2015)

Connectedness

  • Neighborhood poverty
  • Housing burden
  • Car access
  • Commute time (added April 29, 2015)

Economic Benefits

  • GDP gains with racial equity
  • Income gains with racial equity (added November 17, 2014)

Updates and Revisions Made to National Equity Atlas Indicators

June 22, 2017

Indicator(s) affected: Job and wage growth.

Description of revision: Indicator was updated to the most recent data available including 2015 data from the U.S. Bureau of Labor Statistics and the 2016 Complete Economic and Demographic Data Source from Woods & Poole Economics, Inc.

January 28, 2017

Indicator(s) affected: People of color; Race/ethnicity; Population growth rates; Contribution to growth: People of color.

Description of revision: Indicators were updated to reflect more recent demographic projections data. Updated data sources include the 2014 National Population Projections from the U.S. Census Bureau, adjusted to match Census race classifications using information from the 2015 American Community Survey 1-year summary file and the 2015 Population Estimates, also from the U.S. Census Bureau, as well as the 2016 Complete Economic and Demographic Data Source from Woods & Poole Economics, Inc. Demographic projections for these indicators now extend to 2050 (rather than 2040). 

December 22, 2016

Indicator(s) affected: Wages: $15/hour; Contribution to growth: Immigrants; Racial generation gap; Diversity index; GDP gains with racial equity; Income gains with racial equity.

Description of revision: Indicators were updated to the most recent data available including the 2014 5-year IPUMS ACS, the 2014 5-year ACS Summary File, and 2014 data from the U.S. Bureau of Economic Analysis.

Please note: when updating the income gains with racial equity indicator to use data from the 2014 5-year IPUMS ACS, Asian subgroups that had previously been excluded from both the "Income" and "Income gains" breakdowns were added back in. This change affects the income gains with racial equity estimates for the Asian or Pacific Islander and People of color racial/ethnic categories, and means that they are not comparable to previous gains estimates reported using data from the 2012 5-year IPUMS ACS. Previously, the indicator data for these two racial ethnic categories excluded Asian or Pacific Islander subgroups with higher average income levels than non-Hispanic Whites in each Atlas geography and thus the average income levels were relatively lower and the projected income gains were relatively higher. With this update, all data reported for Asian or Pacific Islanders and People of color are inclusive of the entire racial/ethnic populations, and Asian subgroups with higher average income levels than non-Hispanic Whites in each Atlas geography (if any) are assumed to experience no gains or losses in income under the racial equity scenario. The "Source of gains" breakdown is not affected by this change.

November 28, 2016

Indicator(s) affected: Detailed race/ethnicity; Median age; Wages: Median; Working Poor; Poverty; Income Growth; Income Inequality: GINI; Income Inequality:95/20 ratio; Homeownership, Job and GDP growth; Unemployment; Disconnected youth; Education levels and job requirements; Housing burden; Car access; Commute time; Neighborhood poverty.

Description of revision: Indicators were updated to the most recent data available including the 2014 5-year IPUMS ACS, the 2014 5-year ACS Summary File, and 2014 data from the U.S. Bureau of Economic Analysis. 

October 24, 2016

Indicator(s) affected: People of color; Race/ethnicity; Unemployment; Disconnected youth.

Description of revision: New "Map" breakdowns were added to each indicator.

August 23, 2016

Indicator(s) affected: Working poor; Disconnected youth; Education levels and job requirements. 

Description of revision: New "by Gender" breakdowns were added to each indicator.

July 25, 2016

Indicator(s) affected: Wages: Median; Wages: $15/hr; Unemployment; Homeownership; Disconnected youth; Education levels and job requirements; Poverty; Working poor.

Description of revision: New “by Nativity” breakdowns were added to each indicator, and a new "Nativity" filter was added to the "By ancestry" breakdown for each indicator.

May 23, 2016

Indicator(s) affected: Wages: Median; Wages: $15/hr; Unemployment; Homeownership; Disconnected youth; Education levels and job requirements.

Description of revision: New “by Ancestry” breakdowns were added to each indicator. Also, a correction of CPI-U adjustment values in the underlying IPUMS multi-year ACS samples caused slight changes to data reported for the following indicators in years after 2000: Wages: Median and Wages: $15/hr. IPUMS reports that the corrected values do not differ from the previously released data by more than 1 or 2 dollars.

May 2, 2016

Indicator(s) affected: Detailed race/ethnicity.

Description of revision: The indicator was renamed from “Race/ethnicity/nativity” to “Detailed race/ethnicity” and two new breakdowns were added: “By ancestry,” and “By nativity and ancestry.”

January 21, 2016

Indicator(s) affected: Unemployment. 

Description of revision: New "by Gender" breakdown was added to indicator.

December 17, 2015

Indicator(s) affected: Wages: Median; Wages: $15/hr. 

Description of revision: New "by Gender" breakdowns were added to each indicator.

November 24, 2015

Indicator(s) affected: Contribution to growth: People of color (largest 100 cities only).

Description of revision: The indicator was showing incorrect data on projected population changes over the 2010-2020 period for the 100 largest cities. In fact, no population projections are available in the underlying data for the largest 100 cities, so the indicator was corrected by setting the data to missing.

September 30, 2015

Indicator(s) affected: Race/ethnicity; Population growth rates; Contribution to growth: People of color; Race/ethnicity/nativity; Racial generation gap; Contribution to growth: Immigrants; Diversity Index; Median age; Wages: Median; Income inequality: Gini; Income growth; Unemployment; Homeownership; Income inequality: 95/20 ratio; Wages: $15/hr; Education levels and job requirements; Disconnected youth; Housing burden; Neighborhood poverty; Car access; Commute time; Income gains with racial equity; Education levels and job requirements.

Description of revision: Added data for the 100 largest cities to these indicators.

May 19, 2015

Indicator(s) affected: People of color; Race/ethnicity; Population growth rates; Contribution to growth: People of color.

Description of revision: National demographic projections that are used in generating projected data for years 2020-2040 were updated to be based upon the 2014 National Population Projections from the U.S. Census Bureau, adjusted to match Census race classifications using information from the 2013 American Community Survey 1-year summary file and the 2013 Population Estimates, also from the U.S. Census Bureau.

April 29, 2015

Indicator(s) affected: Overweight and obese.

Description of revision: Because not all counties are identified in the Behavioral Risk Factor Surveillance System database, a restriction was applied for the reporting of estimates at the metropolitan area level, which are based on aggregation of data across identified counties. Specifically, we do not report estimates for metropolitan areas in which counties identified in the BRFSS account for less than 95 percent of the total adult (age 18 or older) metropolitan area population, based on analysis of county-level adult population counts from the 2012 American Community Survey 5-year summary file. Metropolitan areas affected by this update include:

  • Anchorage, AK Metropolitan Statistical Area
  • Peoria, IL Metropolitan Statistical Area

November 3, 2014

Indicator(s) affected: Education levels and job requirements.

Description of revision: Assignments of state-level job projections data to metropolitan areas that cover more than one state was revised. Initially, each region was assigned data for the state containing the largest share its 2000 population. The application of state-level job projections data by educational requirements in 2020 to regions that cover more than one state was revised to reflect a weighted average of the job projections data across states covered by each region, using 2012 BEA data on total jobs in the region by state as weight. Metropolitan areas affected by this update include:

  • Allentown-Bethlehem-Easton, PA-NJ
  • Augusta-Richmond County, GA-SC
  • Boston-Cambridge-Quincy, MA-NH
  • Charlotte-Gastonia-Concord, NC-SC
  • Chattanooga, TN-GA
  • Chicago-Naperville-Joliet, IL-IN-WI
  • Cincinnati-Middletown, OH-KY-IN
  • Davenport-Moline-Rock Island, IA-IL
  • Evansville, IN-KY
  • Fayetteville-Springdale-Rogers, AR-MO
  • Kansas City, MO-KS
  • Louisville, KY-IN
  • Memphis, TN-MS-AR
  • Minneapolis-St. Paul-Bloomington, MN-WI
  • New York-Northern New Jersey-Long Island, NY-NJ-PA
  • Omaha-Council Bluffs, NE-IA
  • Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
  • Portland-Vancouver-Beaverton, OR-WA
  • Providence-New Bedford-Fall River, RI-MA
  • South Bend-Mishawaka, IN-MI
  • St. Louis, MO-IL
  • Virginia Beach-Norfolk-Newport News, VA-NC
  • Washington-Arlington-Alexandria, DC-VA-MD-WV
  • Youngstown-Warren-Boardman, OH-PA