Abstract

This dataset contains tables that match an estimated Gini coefficient to a specific geographic region (either census tract, county, or state) from 2010 to 2018. The 1-year estimates are produced by the American Community Survey (ACS).

Documentation

*The passage below comes from the US Census website:*

GINI INDEX OF INCOME INEQUALITYSurvey/Program: American Community SurveyUniverse: HouseholdsYear: 2018Estimates: 1-YearTable ID: B19083

Source: U.S. Census Bureau, 2018 American Community Survey 1-Year Estimates Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties. Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation ). The effect of nonsampling error is not represented in these tables. While the 2018 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities. Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization. Explanation of Symbols: Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.

Income InequalityThe level of income inequality among households in a county can be measured using the Gini index. A Gini index varies between zero and one. A value of one indicates perfect inequality, where only one household in the county has any income. A value of zero indicates perfect equality, where all households in the county have equal income.The United States, as a country, has a Gini Index of 0.47 for this time period. For comparision in this map, the purple counties have greater income inequality, while orange counties have less inequality of incomes. For reference, Brazil has an index of 0.58 (relatively high inequality) and Denmark has an index of 0.24 (relatively low inequality).The 5-year Gini index for the U.S. was 0.4695 in 2007-2011 and 0.467 in 2006-2010. Appalachian Regional Commission, September 2013Data source: U.S. Census Bureau, 5-Year American Community Survey, 2006-2010 & 2007-2011

A broad and generalized selection of 2013-2017 US Census Bureau 2017 5-year American Community Survey income and earnings data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico counties). The selection, while not comprehensive, provides a first-level characterization of the household income, median household income by race and by age group, Social Security income, the GINI Index, per capita income, median family income, and median household earnings by age, and by education level, in New Mexico. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users. The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. As in the decennial census, strict confidentiality laws protect all information that could be used to identify individuals or households.The ACS combines population or other data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups. Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. While each full Data Profile contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by New Mexico county boundaries, based on TIGER/Line Files: shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database. NOTE: A '-666666666' entry indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.

The index ranges from 0.0, when all families (households) have equal shares of income (implies perfect equality), to 1.0 when one family (household) has all the income and the rest have none (implies perfect inequality). Index data is provided for California and its counties, regions, and large cities/towns. The data is from the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Income is linked to acquiring resources for healthy living. Both household income and the distribution of income across a society independently contribute to the overall health status of a community. On average Western industrialized nations with large disparities in income distribution tend to have poorer health status than similarly advanced nations with a more equitable distribution of income. Approximately 119,200 (5%) of the 2.4 million U.S. deaths in 2000 are attributable to income inequality. The pathways by which income inequality act to increase adverse health outcomes are not known with certainty, but policies that provide for a strong safety net of health and social services have been identified as potential buffers.Dataset taken from https://data.chhs.ca.gov/dataset/income-inequalityData Dictionary: COLUMN NAMEDEFINITIONFORMATCODINGind_idIndicator IDPlain Text770ind_definitionDefinition of indicator in plain languagePlain TextFree textreportyearYear(s) that the indicator was reportedPlain Text2005-2007, 2008-2010, 2006-2010. 2005-2007, 2008-2010, and 2006-2010 data is from the American Community Survey (ACS), U.S. Census Bureau. The ACS is a continuous survey. ACS estimates are period estimates that describe the average characteristics of the population in a period of data collection. The multiyear estimates are averages of the characteristics over several years. For example, the 2005-2007 ACS 3-year estimates are averages over the period from January 1, 2005 to December 31, 2007. Multiyear estimates cannot be used to say what was going on in any particular year in the period, only what the average value is over the full time period (Source: http://www.census.gov/acs/www/about_the_survey/american_community_survey/).race_eth_codenumeric code for a race/ethnicity groupPlain Text9=Totalrace_eth_nameName of race/ethnic groupPlain Text9=TotalgeotypeType of geographic unitPlain TextPL=Place (includes cities, towns, and census designated places -CDP-. It does not include unincorporated communities); CO=County; RE=region; CA=StategeotypevalueValue of geographic unitPlain Text9-digit Census tract code; 5-digit FIPS place code; 5-digit FIPS county code; 2-digit region ID; 2-digit FIPS state codegeonameName of geographic unitPlain Textplace name, county name, region name, or state namecounty_nameName of county that geotype is inPlain TextNot available for geotypes RE and CAcounty_fipsFIPS code of county that geotype is inPlain Text2-digit census state code (06) plus 3-digit census county coderegion_nameMetopolitan Planning Organization (MPO)-based region name: see MPO_County List TabPlain TextMetropolitan Planning Organizations (MPO) regions as reported in the 2010 California Regional Progress Report (http://www.dot.ca.gov/hq/tpp/offices/orip/Collaborative%20Planning/Files/CARegionalProgress_2-1-2011.pdf).region_codeMetopolitan Planning Organization (MPO)-based region code: see MPO_CountyList tabPlain Text01=Bay Area; 08=Sacramento Area; 09=San Diego; 14=Southern CaliforniaNumber_HouseholdsNumber of households in a jurisdictionNumericGini_indexCumulative percentage of household income relative to the cumulative percentage of the number of households expressed on a 0 to 1 scale called the Gini Index. The index ranges from 0.0, when all families (households) have equal shares of income, to 1.0, when one family (household) has all the income and the rest none (https://www.census.gov/prod/2000pubs/p60-204.pdf).NumericLL_95CILower limit of 95% confidence intervalNumericLower limit of 95% confidence interval. The 95% confidence limits depict the range within which the percentage would probably occur in 95 of 100 sets of data (if data similar to the present set were independently acquired on 100 separate occasions). In five of those 100 data sets, the percentage would fall outside the limits.UL_95CIUpper limit of 95% confidence intervalNumericUpper limit of 95% confidence interval. The 95% confidence limits depict the range within which the percentage would probably occur in 95 of 100 sets of data (if data similar to the present set were independently acquired on 100 separate occasions). In five of those 100 data sets, the percentage would fall outside the limits.seStandard error of percent NumericThe standard error (SE) of the estimate of the mean is a measure of the precision of the sample mean. The standard error falls as the sample size increases. (Reference: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1255808/)rseRelative standard error (se/percent * 100) expressed as a percentNumericThe relative standard error (RSE) provides the rational basis for determining which rates may be considered “unreliable.” Conforming to National Center for Health Statistics (NCHS) standards, rates that are calculated from fewer than 20 data elements, the equivalent of an RSE of 23 percent or more, are considered unreliable. From: http://www.cdph.ca.gov/programs/ohir/Documents/OHIRProfiles2014.pdfCA_decileDecilesNumeric"CA_decile" groups places or census tracts into 10 groups (or deciles) according to the distribution of values of the index (Gini_index). The first decile (1) corresponds to the highest Gini indices; the tenth decile (10) corresponds to the lowest Gini indices. Equal values or 'ties' are assigned the mean decile rank. For example, in a database of 100 records where 70 records equal 0, 0 values span from the 1st to 7th deciles (70% of all data records). As a result, all 0 values will be assigned to the 4th decile: the mean between the 1st and 7th deciles. The deciles are only calculated for places and/or census tracts.CA_RRIndex ratio to state indexNumericRatio of local index to state index. This indicates how many times the local index is higher or lower than the state index (Reference: http://health.mo.gov/training/epi/RateRatio-b.html). Values higher than 1 indicate local index is higher than state index.Median_HH_incomeMedian household income data is provided for users to stratify the Gini index by income deciles for places and countiesNumericMedian_HH_decileMedian household income data is provided for users to stratify the Gini index by income deciles for places and countiesNumericversionDate/time stamp of version of dataDate/Timemm/DD/CCYY hh:mm:ss

5 year GINI economic inequality index for tracts in Hamilton County

A broad and generalized selection of 2012-2016 US Census Bureau 2016 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of the household income, median household income by race and by age group, Social Security income, the GINI Index, per capita income, median family income, and median household earnings by age, and by education level, in New Mexico. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. NOTE: A '-666666666' entry indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.

A broad and generalized selection of 2014-2018 US Census Bureau 2018 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of the household income, median household income by race and by age group, Social Security income, the GINI Index, per capita income, median family income, and median household earnings by age, and by education level, in New Mexico. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. NOTE: A '-666666666' entry indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.

Data comes from ACS 2019-2023 table B19083. The Gini index, also known as the Gini coefficient or Gini ratio, is a statistical measure of how income, wealth, or consumption is distributed within a group or country. It's calculated by comparing the Lorenz curve, which shows the cumulative distribution of income, to a line of perfect equality. The Gini index is expressed as a percentage that ranges from 0 to 100, with 0 representing perfect equality and 100 representing perfect inequality.

Map Flint - Feature Service layer(s) : ACS5YR 2012-2016 estimates for City of Flint, Michigan, USA by tract of Gini Index of Income Inequality.

Data Dictionary: https://mapflint.org/dictionaries/2016_Flint_by_tract_ACS5YR_Gini_Index_of_Income_Inequality_vars001_data_dictionary.pdf

Note: Layer(s) not initially visible and must be turned on.

This feature layer is an American Community Survey (ACS) estimate (U.S. Census Bureau) that is derived from the National Historical Geographic Information System (NHGIS) and has been customized for various Map Flint analyses and projects pertaining to the City of Flint, Genesee County, Michigan U.S.A. and other surrounding counties - e.g., counties and communities in the greater Flint vicinity that also overlap with the mission of the University of Michigan-Flint EDA University Center for Community and Economic Development. All NHGiS layers in Map Flint projects maintain the uniquely-valued GISJOIN geographic ID assigned by the NHGIS in order to work with multiple data sets.

For more information, visit https://mapflint.org

The Gini Index (or Gini Coefficient) measures the income inequality within a group. A Gini Index of 0 represents perfect equality, while a Gini Index close to 1 represents maximal inequality.

Detailed information regarding the Gini index, in Marin County. Data is sourced from American Community Survey 5-Year Estimates, which is updated annually.

This dataset is automatically updated by Socrata; please contact support@socrata.com if you encounter any questions or issues.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This dataset is for an example workflow and contains three tables—two from the American Community Survey measuring the population/Gini index by county and the third from the National Weather Service measuring the lat/long coordinates for each county.