assets-and-debt

ASSETS & DEBT

How to Cite Black Wealth Data Center

To cite the Black Wealth Data Center, please refer to the [CC-BY-NC-ND](https://creativecommons.org/licenses/by-nc-nd/4.0/) license and use the below format:

Publisher. Date accessed, Article/Page Title, Website Title, URL

Example:

The Black Wealth Data Center. (2022). Explore Data - Assets & Debt. “Average Assets for Individuals, by Race/Ethnicity (Statewide, 2018)”. Blackwealthdata.org.
https://blackwealthdata.org/explore/assets

How to Cite Black Wealth Data Center 

ADT National Scale

The Survey of Consumer Finances dataset is considered the industry or “gold” standard for data on wealth accumulation in the United States. It is a dataset that is collected triannually by the US Federal Reserve. The Public Data File is a dataset containing data from 1989-present and specifically contains the variables used in the Federal Reserve Bulletin article titled: Changes in U.S. Family Finances from 2016 to 2019: Evidence from the Survey of Consumer Finances. In this dataset, all dollar variables have been inflation-adjusted to 2019 dollars by the data publishers. All data represents the household (occasionally referred to as the “family”) as the smallest unit of measure, with demographic variables (i.e. race/ethnicity, age, gender, education) being determined by the household reference person. The Federal Reserve offers the Survey Documentation and Analysis (SDA) Berkeley tool as a resource for extracting the Public Data File and the SDA-published codebook is the most user-friendly published guide to the variables contained within the Public Data File. Reflecting the methodology of the US Federal Reserve Bulletin, all asset and debt measures are conditional calculations, that is, a household needs to hold the measured item (e.g. an asset or a debt) in order to be included in the calculations. This is true for all variables except net worth, which is calculated using the total population dataset. BWDC has calculated weighted values using the FAQ on computing statistics (https://www.federalreserve.gov/econres/scf_faqs.html). The four race and ethnicity categories shown come from the SCF variable RACECL4: "White" represents "White, non-mixed race", "Black" represents "Black/African-American, non-mixed race", "Hispanic" represents "Hispanic/Latino, non-mixed race", and "Other" is defined as anyone else not in those categories.

Data for the question on financial well-being comes from the Survey of Household Economic Decisionmaking. Since 2013, the Federal Reserve Board has conducted the Survey of Household Economics and Decisionmaking (SHED), which measures the economic well-being of U.S. households and identifies potential risks to their finances. The survey includes modules on a range of topics of current relevance to financial well-being including credit access and behaviors, savings, retirement, economic fragility, and education and student loans.


National Scale

ADT State Scale

The dataset used for the state-level data exploration is the Survey of Income and Program Participation dataset. The Survey of Income and Program Participation is a dataset compiled from survey data collected by the US Census on a variety of topics related to economic well-being. As a survey, it deliberately oversamples low-income individuals, which is why it is often considered less-suited than the Survey of Consumer Finances for use in analyzing the wealth gap at a national level. The financial data presented is in current (2019) dollars and has not been inflation-adjusted.

The Black Wealth Data Center has truncated the data on the explore data page to the 2019 survey year (the 2020 SIPP publication) and has transformed the data from its raw extract form to a weighted dataset following the guidance in Chapter 7 of the SIPP Users Guide for an annual (single-year) weighted value. Reflecting the methodology of the US Federal Reserve Bulletin and in the calculations for national indicators, all state-level asset and debt measures are conditional calculations, that is, a household needs to hold the measured item (e.g. an asset or a debt) in order to be included in the calculations. This is true for all variables except net worth, which is calculated using the total population dataset. The US Census-published interactive codebook is the most user-friendly guide to the variables within the dataset. BWDC has used the following weighting guidance to produce weighted annual median estimates for households: https://www2.census.gov/programs-surveys/sipp/Select_approp_wgt_2014SIPPpanel.pdf Race categories exclude persons of Hispanic ethnicity. BWDC has not shown estimates where the sample size is less than 30 or there is insufficient SIPP data.

There are more recently published SIPP datasets than the version available on the BWDC platform, but they did not meet the Census Bureau’s Statistical Quality Standards (2019, 2020) due to nonresponse bias. Additionally, researchers have found that SIPP estimates show discrepancies with the Survey of Consumer Finance, which is called the “gold standard” of wealth data. However, BWDC has included SIPP estimates considering researchers’ conclusions that mean and median estimates of assets and debt compare more favorably to the SCF than other wealth estimates, and that “despite the differences in wealth estimates across surveys, there was no statistical difference across surveys in an estimate of the Black-White wealth gap”. BWDC has When citing SIPP estimates, users should keep the Census Bureau's user notes from 2018 in mind:

Some demographic subgroups are underrepresented in SIPP because of under-coverage and nonresponse. They include young black males, metropolitan residents, renters, people who changed addresses during a panel (movers), and people who were divorced, separated, or widowed. The Census Bureau uses weighting adjustments and imputation to correct the underrepresentation. However, those procedures may not fully correct for all potential biases. There seems to be evidence of potential bias due to nonresponse for some key statistics in SIPP. The Census Bureau has done nonresponse bias studies to investigate the effect of decreasing response rates, but more work needs to be done to truly quantify that bias.

State Scale

ADT Local Scale

The datasets used for local-level data exploration are the American Community Survey (ACS) dataset and the Federal Reserve Debt to Income Ratio dataset. 

The ACS is a dataset that provides information at a community level about employment, education, health, income, and infrastructure, among many other topics. The ACS provides measures of 1-year or 5-year estimates, and the Black Wealth Data Center uses 5-year estimates, which are considered the most reliable, and most appropriate for analyzing small populations. The ACS provides both reported numbers and estimate numbers, and the Black Wealth Data Center uses both types of measures.

BWDC has used the 2016 ACS 5 year estimates for historical comparison based on the ACS guidance to not use 5-year estimates with overlapping years.

BWDC has calculated homeownership rate disaggregated by race by using the following Census definition: "The homeownership rate is computed by dividing the number of owner-occupied housing units by the number of occupied housing units or households." (see https://www.census.gov/quickfacts/fact/note/US/HSG445221). BWDC uses the Census estimates for owner-occupied housing units and occupied housing units disaggregated by race to derive a homeownership rate. Because BWDC is calculating the homeownership rate via ACS estimates that have associated confidence intervals, in certain geographies with small Black populations, the calculated homeownership rate is greater than 100. BWDC has capped the homeownership at 100 and included the Black population totals (in addition to Black population percentage) in the visualization.

BWDC has ingested local level estimates from the ACS at a county and a Zip Code Tabulation Area (ZCTA) level. ZCTAs are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. The Census Bureau says "In most instances the ZCTA code is the same as the ZIP Code for an area. In creating ZCTAs, the Census Bureau took the most frequently occurring ZIP Code in an area for the ZCTA code. Some addresses will end up with a ZCTA code different from their ZIP Code. Some ZIP Codes represent very few addresses (sometimes only one) and therefore will not appear in the ZCTA universe." https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html

The Federal Reserve has published estimates on debt to income ratios at a county level since 1999. BWDC has shown data from 2007 to present, showing Q4 of each year but the latest quarter of the most recent year. This is the same method used by the Federal Reserve for their interactive maps. Household debt is calculated from FRBNY Consumer Credit Panel/Equifax Data, and household income is reported by the Bureau of Labor Statistics. The Federal Reserve has only made the low and high estimates for debt to income ratios available for public download, so BWDC has displayed the high estimate for debt to income ratios.

Local Scale

ADT National

Black Wealth Data Center calculations from US Federal Reserve, Survey of Consumer Finances (SCF) years from 2007 to 2019. 2019 is the most recent year. All asset and debt measure calculations except for net worth are conditional, that is, a household needs to hold the measured item (e.g. an asset or a debt) in order to be included in the calculations. All financial data is presented in constant 2019 dollars.
Descriptor words: national, median assets, median debt, median net worth, household, scf, survey of consumer finance, over time, year

AD1 Average Total Assets for Households by Race Ethnicity Nationwide 2007-2019

Median Total Net Worth for Households, by Race/Ethnicity

Data source: Black Wealth Data Center calculations from US Federal Reserve, Survey of Consumer Finances (SCF) years from 2007 to 2019. 2019 is the most recent year. All asset and debt measure calculations except for net worth are conditional, that is, a household needs to hold the measured item (e.g. an asset or a debt) in order to be included in the calculations. All financial data is presented in constant 2019 dollars.
Descriptor words: national, asset, debt, household, life insurance, stocks, investment funds, liquid, retirement account, ira, 401k, stock holdings, credit card, primary residence, mortgage, education loan, student, installment, scf, survey of consumer finance

Percent Holding by Asset/Debt Type

Percent of Households Holding by Asset/Debt Types by Race/Ethnicity

Black Wealth Data Center calculations from US Federal Reserve, Survey of Consumer Finances (SCF) years from 2007 to 2019. 2019 is the most recent year. All asset and debt measure calculations except for net worth are conditional, that is, a household needs to hold the measured item (e.g. an asset or a debt) in order to be included in the calculations. All financial data is presented in constant 2019 dollars.
Descriptor words: national, median asset, median debt, household, life insurance, stocks, investment funds, liquid, retirement account, ira, 401k, stock holdings, credit card, primary residence, mortgage, education loan, student, installment, percentile, distribution, year, over time, scf, survey of consumer finance

Median Assets by category

 Total Assets & Debt for Households, by Race/Ethnicity

Data Source: Black Wealth Data Center calculations from the Federal reserve Board, Survey of Household Decisionmaking.
Tags: Financial wellbeing, assets, household wealth, finances

ADT09

Compared to 12 months ago, would you say that you or your family is better off financially?

Explore measures of assets, debt, and net worth at a national level

ADT State

Black Wealth Data Center calculations from US Census, Survey of Income and Program Participation (SIPP) 2018. 2018 is the most recent year without significant data limitations. All asset and debt measure calculations except for net worth are conditional, that is, a household needs to hold the measured item (e.g. an asset or a debt) in order to be included in the calculations. All financial data is presented in constant 2018 dollars.
Descriptor words: state, median asset, median debt, median net worth, sipp, survey of income and program participation

AD3 Median Assets statewide

Median Total Assets for Households by Race/Ethnicity

Explore measures of assets, debt, and net worth at a state level

ADT Local

Data Source: Data made available throught the US Federal Reserve. Household debt is calculated from FRBNY Consumer Credit Panel/Equifax. Household income is reported by the Bureau of Labor Statistics. 
Descriptor words: county, zipcode, zip code, debt to income ratio, federal reserve, equifax, debt, income

Debt to Income Ratio

Debt to Income Ratio for Households

US Census American Community Survey 2022 five-year estimates data. 2022 is the most recent year for five-year estimates.
Descriptor words: county, zipcode, zip code, below poverty line, american community survey, acs, percentage poverty

Data Source: US Census, American Community Survey, 2021-5 year estimates data. 2021 is the most recent year.

Percentage of Population in Poverty, by Race/Ethnicity

Percent Poverty, by Race/Ethnicity

US Census American Community Survey 2022 five-year estimates data. 2022is the most recent year for five-year estimates. All financial data is presented in constant 2022 dollars.
Descriptor words: county, zipcode, zip code, homeownership rate, owner occupied homes, occupied homes, housing, american community survey, acs, homeowner

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