Income – Inequality (GINI Index) (783)

Method


Counts of total households GINI index values are acquired from the U.S. Census Bureau’s American Community Survey (ACS). Data represent estimates for the 5 year period 2017-2021. Mapped data are summarized to 2021 census tract boundaries. This indicator reports income inequality in the US using the GINI index. The Census Bureau defines the Gini index as “a statistical measure of income inequality ranging from 0 to 1. A measure of 1 indicates perfect inequality, i.e., one household having all the income and rest having none. A measure of 0 indicates perfect equality, i.e., all households having an equal share of income.

This indicator draws directly from reported data and cannot be re-summarized to custom report areas. For multi-county areas, the average population-weighted GINI index value is reported. For more information about this source, refer to the United States Census 2021 Household Income data briefing website.

Background

The American Community Survey (ACS) is a nationwide survey designed to provide communities with reliable and timely social, economic, housing, and demographic data every year. The ACS has an annual sample size of about 3.5 million addresses, with survey information collected nearly every day of the year. Data are pooled across a calendar year to produce estimates for that year. As a result, ACS estimates reflect data that have been collected over a period of time rather than for a single point in time as in the decennial census, which is conducted every 10 years and provides population counts as of April 1. The Census Bureau combines 5 consecutive years of ACS data to produce estimates for geographic areas with fewer than 65,000 residents. These 5-year estimates represent data collected over a period of 60 months. Because the ACS is based on a sample, rather than all housing units and people, ACS estimates have a degree of uncertainty associated with them, called sampling error. In general, the larger the sample, the smaller the level of sampling error. Data users should be careful in drawing conclusions about small differences between two ACS estimates because they may not be statistically different.

Citation: U.S. Census Bureau: UNDERSTANDING AND USING AMERICAN COMMUNITY SURVEY DATA: WHAT ALL DATA USERS NEED TO KNOW (2018).

For more information about this source, including data collection methodology and definitions, refer to the American Community Survey data users website.

Note

Race and Ethnicity
Race and ethnicity (Hispanic origin) are collected as two separate categories in the American Community Survey (ACS) based on methods established by the U.S. Office of Management and Budget (OMB) in 1997. Indicator race and ethnicity statistics are generated from self-identified survey responses. Using the OMB standard, the available race categories in the ACS are: White, Black, American Indian/Alaskan Native, Asian, and Other. An ACS survey respondent may identify as one race alone, or may choose multiple races. Respondents selecting multiple categories are racially identified as “Two or More Races”. The minimum ethnicity categories are: Hispanic or Latino, and Not Hispanic or Latino. Respondents may only choose one ethnicity. All social and economic data are reported in the ACS public use files by race alone, ethnicity alone, and for the white non-Hispanic population.