Mapping Pathways to Building Collective Black Wealth
By: Miriam Van Dyke, PhD & Alex Camardelle, PhD
At Kindred Futures, we are focused on creating innovative community wealth-building solutions to uplift the Talented 90th, a broad base of Black households, including the nearly 2 million Black households in the American South with zero or negative net worth. This means advocating for the scalability of innovative and reparative initiatives for Black families. To understand which solutions are the most impactful, it is important to first understand the underlying historical and present-day determinants and drivers impacting the ability of Black communities to create, protect, and sustain wealth.
To do this, Kindred Futures worked with PolicyMap to build the Mapping Black Wealth Pathways tool, showing how economic policies (e.g., state minimum wage laws) and opportunities (e.g., jobs and wages), and environmental (e.g., climate burden), health (e.g., healthcare access), and living (e.g., housing affordability) conditions are spread across communities and providing or extracting opportunities to build wealth. While many of these data points describe negative conditions, we see them as an opportunity to identify and tailor solutions to support Black communities on their pathway to building collective wealth.
Click on INDICATORS and get started exploring your community today.
To get the scoop on how Kindred Futures selected these data points, read on!
Pro tip: zoom in and out to view data indicators across various geographic levels (e.g., state, county, zip code tabulation area, and census tract).
Kindred Futures R3 Framework: Revenue, Resilience, and Repair
Data points for the Mapping Black Wealth Pathways Tool were selected to reflect the Kindred Futures R3 Framework: Revenue, Resilience, and Repair.
At Kindred Futures, the R3 framework—Revenue, Resilience, and Repair—grew out of both rigorous research and intentional community listening. In conversations with Black families across the South, we consistently heard that wealth is not simply about assets, but about freedom: the freedom to choose, to secure a future for one’s children, and to thrive without fear of exploitation or loss. Sitting with this wisdom alongside the data, we came to understand that achieving Black prosperity requires a framework broad enough to confront the structural determinants of wealth. R3 reflects that understanding: we must generate new income and assets through Revenue, safeguard those gains through Resilience, and pursue systemic Repair for the harms of dispossession and exclusion. Together, these pillars embody both the urgency of redress and the promise of building lasting, liberatory wealth for Black communities.
The Revenue Pillar focuses on Creating Pathways for Growth and Income to Build Black Economic Power.
- The Revenue pillar of the R3 strategy is about creating robust pathways for economic growth, asset-building, and income generation in Black communities. This means investing in Black-owned businesses, entrepreneurship, homeownership, and good jobs as engines of wealth creation. Kindred Futures advances research and policies that expand access to capital for Black entrepreneurs, support Black business development, and reduce barriers that have historically stifled Black enterprise. For example, it backs initiatives like Black business incubators, equitable entrepreneurship training, and special-purpose credit programs that provide financing to Black start-ups. By promoting worker justice (supporting good wages, benefits, and collective bargaining), ensures that Black workers share in economic growth. All these efforts align with Kindred Futures’ priority of expanding Black incomes and assets, measured by indicators like rising Black business ownership rates, higher earnings from work, etc.
The Resilience Pillar focuses on protecting and preserving Black wealth, including safeguarding homes, communities, and assets.
- The Resilience pillar of the R3 strategy is about research and policies that center on protecting existing Black wealth from systemic threats, displacement, and financial exploitation. LEAD’s strategy here is about fortifying the defenses around Black-owned homes, land, businesses, and savings so that hard-won gains are not eroded. This involves advocating for strong anti-displacement policies – for instance, tenant protections and anti-eviction measures to keep Black renters from unjust removal, rent control policies to prevent profiteering in gentrifying neighborhoods, and heirs’ property reforms to help Black families secure clear title to ancestral land and homes. The resilience work also tackles predatory financial practices: pushing for consumer financial protections and regulation of payday lenders, mortgage fraud, and other exploitative schemes that often target Black households. Additionally, this pillar embraces climate resilience strategies – recognizing that environmental threats (floods, hurricanes, extreme heat) disproportionately impact Black families and can literally wash away Black wealth. By promoting equitable climate adaptation (like infrastructure investments and insurance support in Black communities) alongside social safety nets and healthcare access.
The Repair Pillar focuses on addressing historical injustices and closing the wealth divide, allowing for a reckoning with the past to invest in the future.
- The Repair pillar of Kindred Futures’ R3 strategy directly confronts the legacy of racial injustice that has stripped wealth from Black Americans for generations and pursues reparative investments to rectify those disparities. This means pushing beyond incremental progress and seeking transformative change that returns wealth and resources to Black communities. The R3 strategy promotes formal reparations programs at the national, state, and local levels – policies that would provide compensation or restitution for the enormous economic harms of slavery, segregation, redlining, and other racist policies. Such reparations could take the form of direct payments, housing grants, educational scholarships, or community investments targeted to descendants of those who suffered economic losses. In addition, this includes the impact of land and property reclamation initiatives: efforts to restore land ownership or property rights to Black families who were dispossessed. This includes everything from securing the return of stolen land (for example, recent cases where cities have returned property taken from Black owners generations ago) to reforming laws so Black landowners (like heirs’ property holders in the South) can reclaim and keep their land. Another key area of Repair is debt forgiveness – advocating for canceling or alleviating debts that disproportionately burden Black households. Lastly, Repair represents Kindred Futures’ leading research and advocacy on baby bonds and children trust accounts in the South, which we promote as universal investment vehicles that are reparative.
Mapping Black Wealth Pathways Tool in Action
The Mapping Black Wealth Pathways Tool opens with the percent of households with a Black householder that are unbanked using data from 2019-2023 across 9 American South states. However, we know that it is not that straightforward. Historical exclusionary policies, practices, and legislation have placed Black communities at an economic disadvantage and have created barriers to banking and accessing credit with favorable terms. For example, majority Black neighborhoods (census tracts) are less likely to have a bank branch than non-majority Black neighborhoods. Conversely, Kindred Futures has found a higher density of predatory financial institutions (e.g., payday lenders and title pawn retailers) in Atlanta’s predominantly Black neighborhoods which offer alternative financial services, including high-interest loans and substandard products that trap Black families in cycles of debt and extract wealth.
Zooming in, you are able to explore the complex dynamics influencing the ability of communities at different levels (e.g., census tract, county, zip code) to build wealth and economically prosper. For example, in Atlanta, GA, the story of historical exclusion and its present-day impacts are evident when exploring grades assigned to neighborhoods by the Home Owners Loan Corporation (HOLC) between 1935-1940 (see Repair tab) (more info on HOLC grades indicator). These grades reflected “mortgage security” and influenced the likelihood of banks and other mortgage lenders to provide loans and determined investment safety. To say the least, these grades were racially discriminatory as they used the racial composition of neighborhoods in grade calculations, giving lower grades to areas with greater concentrations of Black and immigrant residents. While the City of Atlanta is facing gentrification pressures, disproportionately displacing Black residents, it is evident that Black residents still largely reside in historically redlined areas and may continue to face limited access to credit (see Demographics tab).
Historical redlining has helped to reinforce the deep racial wealth divide, creating a present-day paradoxical situation in some redlined communities where the historical building of wealth from homeownership has been limited, and yet these communities also hold relatively more affordable housing and provide an opportunity for entry to homeownership. The map below shows the median value of owner-occupied homes in areas (see the Repair tab). Explore the Resilience tab to also see the spatial distribution of homes that are likely affordable for a 4-person family earning 50% of the area median income.
However, communities with relatively more affordable housing need proactive protections and supports for residents with lower incomes and business owners at risk of displacement. Communities also need more than just affordable housing to thrive. They need access to good jobs and other economic opportunities and supports. For example, the lower job opportunity and greater average travel time to jobs (mapped below, see Revenue tab) are yet another symptom of chronic economic disinvestment in some of Atlanta’s majority Black neighborhoods.
Revenue Data Indicators
U.S. Department of Labor
Domain: Income
Data Label: State minimum wage as of January 1, 2022
Data Definition: State minimum wage as of January 1, 2022. The federal minimum wage is $7.25. Some states have legislated higher minimum wages, and some have lower minimum wages. Where the state minimum wage is lower than the federal minimum wage, the state’s is superseded by the federal, which is shown here. Where the state minimum wage is higher than the federal, the state’s minimum wage supersedes the federal. Some municipalities and counties have a minimum wage higher than the state’s; these are not seen here. Minimum wages seen here apply to nonsupervisory, nonfarm, private sector employment. (see data dictionary)
IRS
Domain: Retirement
Data Label: Average amount of IRAs, pensions, or annuities on income tax returns in 2021
Data Definition: Average amount of IRAs, pensions, or annuities on income tax returns in 2021. Average amount of IRAs, pensions, or annuities reported on 1040, 1040A, and 1040EZ forms filed with the IRS for the tax year 2021. Average includes only returns with IRAs, pensions, or annuities. The average is suppressed where fewer than 10 returns are filed with IRAs, pensions, or annuities. (see data dictionary)
Census
Domain: Employment
Data Label: Estimated percent of people aged 16 years or older who were unemployed, between 2019-2023
Data Definition: Estimated percent of civilian people age 16 years or older in the labor force who were unemployed, between 2019-2023. Civilians are defined as those not serving in the armed forces. Percentage calculations are suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
LEHD
Domain: Employment
Data Label: Number of non-federal jobs in all industries in 2022
Data Definition: Number of non-federal jobs in all industries in 2022. Data that includes federal employees is available stating in 2010. Available data for years prior to 2010 includes only employees of private firms and state and local governments. Data are not available for all states in all years. (see data dictionary)
Census
Domain: Access
Data Label: Estimated average travel time to work in minutes in 2019-2023
Data Definition: Estimated average travel time to work in 2019-2023. The average travel time to work is the number of minutes required to reach place of employment for workers age 16 years or older. Averages are suppressed in cases where the sample of the average was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Community Reinvestment Act (CRA)
Domain: Business
Data Label: Average amount of small business loans in 2023
Data Definition: Average amount of small business loans in 2023. These figures were reported under the Community Reinvestment Act (CRA). CRA data captures the lending activity of financial institutions with one billion dollars or more in holdings. Therefore, it may understate total lending, especially in rural areas in which top lenders may be smaller in asset size and, thus, not required to report. Census tract values may not sum to county values. (see data dictionary)
United States Small Business Administration (SBA)
Domain: Business
Data Label: Small business development centers
Data Definition: Small Business Development Centers (SBDCs) help small business and entrepreneurs with free business consulting and low-cost training services including business plan development, manufacturing assistance, financial packaging and lending assistance, exporting and importing support, disaster recovery assistance, procurement and contracting aid, market research help, 8(a) program support, and healthcare guidance. SBDCs are hosted by universities and state economic development agencies, and funded through a partnership with SBA. (see data dictionary)
InBIA
Domain: Business
Data Label: Business Incubators
Data Definition: The International Business Innovation Association is a trade group serving over 2,100 business incubators and related organizations worldwide. Business incubators are programs that provide support services and resources for entrepreneurial companies during their “start-up” phase. InBIA provided PolicyMap with a list of business incubators in the United States. (see data dictionary)
CDFI Fund
Domain: Banking
Data Label: Certified CDFIs (2025)
Data Definition: The Community Development Financial Institutions (CDFI) Fund, a division of the US Department of the Treasury, supports and invests in Community Development Financial Institutions through the CDFI Program and Native American CDFI Assistance Program. CDFIs are financial institutions that provide products and services in economically distressed target markets. The CDFI Fund certifies CDFIs through an application process on a rolling basis, depending on the type of institution. Not all CDFIs are certified, but certification is a requirement for some federal program funding. PolicyMap was able to locate 83% of CDFI addresses on a map. Data on certified CDFI locations are updated twice annually. (see data dictionary)
BLS Quarterly Census of Employment and Wages
Domain: Employment
Data Label: Average annual wage across all goods-producing industries in 2023
Data Definition: Average annual wage across all goods-producing industries in 2023. Wage and employment totals are from quarterly tax reports submitted to State workforce agencies by employers under State Unemployment Insurance (UI) laws. This is total wages reported for all employees divided by the average monthly employment reported throughout the year. Data do not include public-sector government employees. Any location for which the number of jobs is not available is displayed on the map as having Insufficient Data. (see data dictionary)
BLS Quarterly Census of Employment and Wages
Domain: Employment
Data Label: Average annual wage across all service-providing industries in 2023
Data Definition: Average annual wage across all service-providing industries in 2023. Wage and employment totals are from quarterly tax reports submitted to State workforce agencies by employers under State Unemployment Insurance (UI) laws. This is total wages reported for all employees divided by the average monthly employment reported throughout the year. Data do not include public-sector government employees. Any location for which the number of jobs is not available is displayed on the map as having Insufficient Data. (see data dictionary)
PolicyMap and ACS
Domain: Homeownership
Data Label: Homeownership gap between Non-Hispanic White homeowners and Black or African American homeowners, between 2019-2023.
Data Definition: Homeownership gap between Non-Hispanic White homeowners and Black or African American homeowners, between 2019-2023. The US Census Bureau identifies the householder as the person in whose name the home is owned, being bought, or rented. If there is no such person present, any household member 15 years and older can serve as the householder for the purposes of the Census. Percentage calculations are suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). PolicyMap calculated the gap using percent of owner households by race subtracted from percent of Non-Hispanic White owner households. (see data dictionary)
Resilience Data Indicators
PolicyMap, Census, and HUD
Domain: Housing affordability
Data Label: Percent of all homes that are likely affordable for a 4-person family earning 50% of AMI between 2019-2023
Data Definition: Percent of all homes that are likely affordable for a 4-person family earning 50% of AMI between 2019-2023. Likely affordable owner-occupied housing units are considered those valued at or less than roughly three times the 4-person family income. For example, a family with an income of $30,000 could afford to purchase a home valued at less than $90,000. These estimates provide information on relative availability of home ownership opportunities in different areas of the country, and can highlight any needs or shortcomings in the locally available housing stock of a given area. PolicyMap created these affordability estimates using publicly available data on incomes and housing costs. Area Median Income is the median income for a family of a specified size within the county, metropolitan area, or state, as published by HUD in 2023. Housing cost data is comprised of the estimated number of homes under specific dollar value thresholds from the Census’ 2019-2023 American Community Survey. For more information please see the data directory. Areas for which data was not reported or for which data could not be assigned are displayed as having ‘Insufficient Data’ in the map. (see data dictionary)
PolicyMap, Census, and HUD
Domain: Housing affordability
Data Label: Percent of all two-bedroom rental units that are likely affordable for a 4-person family earning 30% of AMI between 2019-2023.
Data Definition: Percent of all two-bedroom rental units that are likely affordable for a 4-person family earning 30% of AMI between 2019-2023. These estimates provide information on the relative affordability of rental housing in different areas of the country, and can highlight any needs or shortcomings in the locally available rental housing stock of a given area. PolicyMap created these affordability estimates using publicly available data on incomes and rental prices. Area Median Income is the median income for a family of a specified size within the county, metropolitan area, or state, as published by HUD in 2023. An estimated count of homes under specific dollar thresholds is taken from the Census’ 2019-2023 American Community Survey. Apartment size (number of bedrooms) needed by a family was assigned based on two people per bedroom. For more information please see the data directory. Areas for which data was not reported or for which data could not be assigned are displayed as having ‘Insufficient Data’ in the map. (see data dictionary)
Census
Domain: Housing affordability
Data Label: Estimated percent of all renter-occupied housing units with a householder who is Black or African American, where housing costs exceed 30 percent of household income, between 2019-2023
Data Definition: Estimated percent of all renter-occupied housing units with a householder who is Black or African American, where housing costs exceed 30 percent of household income, between 2019-2023. Percentage calculations are suppressed in cases where fewer than 10 of the unit that is being described (e.g., households, people, householders, etc.) are present. (see data dictionary)
CDC PLACES
Domain: Housing Affordability
Data Label: Crude percent of utility services threat in the past 12 months among adults in 2022
Data Definition: A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who reported that an electric, gas, oil, or water company threatened to shut off services at any time during the prior 12 months.
The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. (see data dictionary)
Federal Reserve Bank of NY
Domain: Credit
Data Label: Tiers of Relative Credit Security
Data Definition: Tiers of Relative Security. Credit Insecurity Index scores are assigned to tiers of relative severity: Credit Assured, Credit Likely, Mid-Tier, Credit At Risk, and Credit Insecure. These ranges are determined by using the quintiles of county-level Credit Insecurity Index scores. According to the Federal Reserve Bank of New York, 2018 is used as the base year of calculation, meaning the tiers are based on the county-level Index scores from that year. This allows the number of counties in each tier to change in subsequent years. The Tiers and the Index Score Ranges are defined as follows:
- Credit Assured: 0 – 16.6
- Credit Likely: 16.7 – 21.7
- Mid-Tier: 21.8 – 26.4
- Credit At Risk: 26.5 – 32.5
- Credit Insecure: 32.6 or above.
These tiers offer another dimension of categorical information to demonstrate how credit constrained a community is relative to other communities in the United States. (see data dictionary)
IRS
Domain: Tax Credit
Data Label: Percent of income tax returns with earned income credit (EITC) in 2021
Data Definition: Percent of income tax returns with earned income credit (EITC) in 2021. Percent of all 1040, 1040A, and 1040EZ forms filed with the IRS with earned income credit (EITC) reported for the tax year 2021. The EITC is a refundable federal income tax credit for low-income working individuals and families. Total and average amounts include both refundable and non-refundable portions of the credit. More information is available from the IRS. The percent is suppressed where fewer than 10 total returns are filed. (see data dictionary)
EPA CIMC
Domain: Environment
Data Label: Brownfields (2023)
Data Definition: The EPA regularly updates its Brownfields Sites Report List. The points in PolicyMap are as of April 2024. The coordinates used in PolicyMap are provided by the EPA. PolicyMap removes points that do not appear in the site’s listed state. The points shown on PolicyMap include brownfield sites that have received assessment, cleanup, and/or redevelopment funding from the EPA. Brownfields designated by states or local entities, sites that may qualify for but have not received EPA assessment funding, and underground storage tanks are not included on the map. Each point represents a transfer of funds related to a known brownfield site. Multiple points for the same brownfield location indicate multiple actions over a period of time; the entity receiving funds may differ. (see data dictionary)
CDC & ATSDR
Domain: Environment
Data Label: Environmental Justice Index (EJI) Environmental Burden Module
Data Definition: The Environmental Burden Module (EBM) contains environmental indicators that either cause pollution or otherwise negatively affect human health. The EBM contains indicators relating to air pollution, potentially hazardous and toxic sites, the built environment, pollution related to transportation, and water pollution. The Environmental Justice Index (EJI) scores census tracts using a percentile ranking which represents the proportion of tracts that experience cumulative impacts of environmental burden and injustice equal to or lower than a tract of interest. A higher percentile rank means the tract faces more severe impacts relative to other tracts nationwide. (see data dictionary)
CDC & ATSDR
Domain: Environment
Data Label: Environmental Justice Index (EJI) Climate Burden Module
Data Definition: The Climate Burden Module (CBM) contains environmental indicators that are or have been influenced by climate change, such as extreme heat and wildfires. The CBM contains indicators relating to heat, wildfires, and extreme events. The Environmental Justice Index (EJI) scores census tracts using a percentile ranking which represents the proportion of tracts that experience cumulative impacts of environmental burden and injustice equal to or lower than a tract of interest. A higher percentile rank means the tract faces more severe impacts relative to other tracts nationwide. (see data dictionary)
CDC
Domain: Health
Data Label: Total count of high prevalence sensitivity module indicators (out of six) in 2024
Data Definition: Total count of high prevalence sensitivity module indicators (out of six) in 2024. This variable was calculated as the sum of flagged indicators for sensitivity module. The Sensitivity module is comprised of pre-existing health conditions that may increase risk of negative health outcomes when the individual with the condition is exposed to extreme heat. The pre-existing health conditions in this module are:
- Asthma
- Chronic Obstructive Pulmonary Disease (COPD)
- Coronary Heart Disease (CHD)
- Diabetes
- Obesity
- Poor Mental Health.
While most indicators can have a range of values, the Sensitivity module indicators represent only whether a given ZCTA has a high estimated prevalence of the disease or not. High prevalence was determined when a ZCTA had a greater than 66th percentile rank of the pre-existing disease. The total count of these disease indictors ranges from 0-6, with a total of 6 indicating a higher risk of biological conditions that may increase negative health outcomes when exposed to extreme heat.
The HHI uses ZIP Code Tabulation Areas (ZCTAs) to aggregate data and show index ranks across the United States. Click a ZCTA on the map to see the indicators associated with this module. (see data dictionary)
CDC
Domain: Health
Data Label: Life expectancy at birth, as of 2010-2015
Data Definition: The average number of years a person born in this tract would be expected to live, as of 2010 to 2015. (see data dictionary)
Census
Domain: Access
Data Label: Estimated percent of Black or African American people without health insurance, between 2019-2023
Data Definition: Estimated percent of the Black or African American population without health insurance coverage, between 2019-2023. (see data dictionary)
HRSA
Domain: Access
Data Label: Medically Underserved Areas (MUA), as of 2024
Data Definition: Medically Underserved Areas (MUA), as of 2024. Medically Underserved Areas are designated by the Health Resources and Services Administration as having too few primary care providers, high infant mortality, high poverty, and/or a high elderly population. Medically Underserved Populations (MUP) are areas where a specific population group is underserved, including groups with economic, cultural, or linguistic barriers to primary medical care. If a population group does not meet the criteria for an MUP, but exceptional conditions exist which are a barrier to health services, they can be designated with a recommendation from the state’s Governor. (see data dictionary)
Feeding America
Domain: Access
Data Label: Percent of Black inhabitants (all ethnicities) who are food insecure in 2023
Data Definition: According to the United States Department of Agriculture (USDA), food insecurity is defined as the limited or uncertain availability of nutritionally adequate and safe foods, or the limited or uncertain ability to acquire acceptable foods in socially acceptable ways. Feeding America first analyzes the relationship between food insecurity and key indicators such as poverty, unemployment, homeownership, and disability prevalence at the state level. The resulting coefficients are then applied to the same variables at the county and congressional district levels to produce modeled local estimates of food insecurity for both individuals and children. These estimates are part of Feeding America’s annual Map the Meal Gap analysis. See the Data Directory for a link to the full methodology.
(see data dictionary)
Census
Domain: Access
Data Label: Estimated percent of households with no internet access, between 2019-2023
Data Definition: Estimated percent of households with no internet access, between 2019-2023. Internet access can include a subscription for dial-up, cellular, cable, fiber optic, DSL, satellite, or other service, or internet access without a subscription. Percentage calculations are suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Census
Domain: Access
Data Label: Estimated percent of housing units for which no vehicles are available in 2019-2023
Data Definition: Estimated percent of occupied housing units for which no vehicles are available in 2019-2023. Percentage calculations are suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Repair Data Indicators
Census
Domain: Housing segregation
Data Label: Estimated median value of an owner-occupied home, between 2019-2023
Data Definition: Estimated median value of an owner-occupied housing unit, between 2019-2023. The value is based on survey respondents’ estimates of how much their properties and lots would sell for if they were for sale. Medians were suppressed in cases where the sample of the average was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). ACS employs values to indicate top and bottom ranges of values. A value of 1,000,001 indicates a value of 1,000,000 or greater, whereas a value of 9,999 indicates a value of 10,000 or less. (see data dictionary)
University of Richmond, University of Maryland, Virginia Tech, and Johns Hopkins University
Domain: Housing discrimination
Data Label: Grade assigned by the Home Owners Loan Corporation (HOLC) between 1935-1940
Data Definition: Grade assigned by the Home Owners Loan Corporation (HOLC) between 1935-1940. Area grades range from A to D, with A denoting ‘Excellent’, B denoting ‘Still Desirable’, C denoting ‘Definitely Declining’, D denoting ‘Hazardous’. Grades were assigned based on input from mortgage lenders, developers, and real estate appraisers, and were used to measure creditworthiness and risk on neighborhood and metropolitan levels. Mapping Inequality: Redlining in New Deal America, published by the Digital Scholarship Lab at University of Richmond in collaboration with University of Maryland, Virginia Tech, and Johns Hopkins University, includes a collection of digital maps on area security and descriptions for major urban centers developed by the Home Owners’ Loan Corporation (HOLC) from 1935 to 1940. (see data dictionary)
PolicyMap and FFIEC
Domain: Housing discrimination
Data Label: Percent of all home loans applied for by Black applicants that were denied in 2024
Data Definition: Percent of all home loans applied for by Black applicants that were denied in 2024.These denied loan applications were for the purchase or refinance of an owner-occupied, one-to-four family dwelling. Percents are not computed where the denominator of the calculation was less than five. (see data dictionary)
FDIC
Domain: Banking
Data Label: Percent of households with a Black householder that are unbanked as of 2019-2023
Data Definition: Percent of households with a Black householder that are unbanked as of 2019-2023. These households lack any kind of deposit account at an insured depository institution such as a bank or credit union. Data are not available where the sample size was too small to make an accurate estimate. These areas are labeled as “Insufficient Data” on the map. (see data dictionary)
United States Elections Project
Domain: Voter Turnout
Data Label: Turnout rate among voting eligible population in the 2020 presidential general election.
Data Definition: Turnout rate among voting eligible population in the 2020 presidential general election. Percent of voting eligible population who participated in the 2020 presidential general election. The turnout rate was calculated by dividing the number of votes for the highest office in the election (often president, governor, or congress) by the voting age population minus non-citizens and those in prison, on probation, or on parole, for states where such people are ineligible to vote. Some states permanently disenfranchise felons and people who have been judged mentally incompetent; these exclusions are not included in the data. Votes from people living overseas are counted in the vote total, but such people are not counted in the denominator, except at the national level. More information can be found at http://www.electproject.org/home/voter-turnout/faq. (see data dictionary)
Census, Opportunity Insights
Domain: Justice System
Data Label: Incarceration rate for Black people raised in very low income families as of 2018
Data Definition: Incarceration rate for Black people raised in very low income families as of 2018. This represents the percentage of people born between 1978 and 1983 who were raised in this area in households with incomes at or below the 25th percentile nationally who were incarcerated, according to the 2010 Census. The Opportunity Atlas was created by Opportunity Insights, a Harvard University-based research group, and researchers at the Census Bureau. The researchers linked responses from the U.S. Census with federal income tax data and American Community Survey responses to trace a person’s outcomes back to the place they were raised. (see data dictionary)
Demographic Data Indicators
Census
Domain: Race/Ethnicity
Data Label: Predominant racial or ethnic group, between 2019-2023
Data Definition: Predominant racial or ethnic group, by percentage of the population in the group. Data were obtained from the Census’ American Community Survey 2019-2023 estimates. This was calculated with non-overlapping racial and ethnic categories provided by the US Census Bureau, including the ethnic category Hispanic and the following 7 Non-Hispanic racial categories: White, African American, American Indian or Alaska native, Asian, Native Hawaiian or Pacific Islander, some other race, and two or more races. Geographies for which no data were provided or for which the population was less than 10 are represented as having “Insufficient Data.” (see data dictionary)
Census
Domain: Race/Ethnicity
Data Label: Estimated percent of all people who were Black or African American, between 2019-2023
Data Definition: Estimated percent of the population that is Black or African American, by single classification of Census race, between 2019-2023. Percentage calculations are suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Census
Domain: Income
Data Label: Estimated median income of a Black or African American householder, between 2019-2023
Data Definition: Estimated median income of a Black or African American householder, between 2019-2023. (see data dictionary)
Census
Domain: Educational attainment by race/ethnicity
Data Label: Estimated percent of Black or African American people with some high school, but no diploma, between 2019-2023
Data Definition: Estimated percent of the Black or African American population that is 25 years and older whose educational attainment is some high school but no diploma, between 2019-2023. Percentage calculations were suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Census
Domain: Educational attainment by race/ethnicity
Data Label: Estimated percent of Black or African American people with at least a high school diploma, between 2019-2023
Data Definition: Estimated percent of the Black or African American population that is 25 years and older with a high school diploma or greater level of education, between 2019-2023. Percentage calculations were suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Census
Domain: Educational attainment by race/ethnicity
Data Label: Estimated percent of Black or African American people with at least a Bachelor’s degree, between 2019-2023
Data Definition: Estimated percent of the Black or African American population that is 25 years and older with a Bachelor’s degree, graduate, or professional degree, between 2019-2023. Percentage calculations were suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.). (see data dictionary)
Census
Domain: Poverty
Data Label: Estimated percent of all Black or African American people who lived in poverty, between 2019-2023
Data Definition: Estimated percent of all Black or African American people who lived in poverty, between 2019-2023. (see data dictionary)