42 datasets found
  1. N

    Income Distribution by Quintile: Mean Household Income in Newport News, VA...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Newport News, VA // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/4837316e-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Newport News, Virginia
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Newport News, VA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,915, while the mean income for the highest quintile (20% of households with the highest income) is 213,538. This indicates that the top earners earn 14 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 391,727, which is 183.45% higher compared to the highest quintile, and 2626.40% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Newport News median household income. You can refer the same here

  2. N

    Newport News, VA Median Income by Age Groups Dataset: A Comprehensive...

    • neilsberg.com
    csv, json
    Updated Feb 25, 2025
    + more versions
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    Neilsberg Research (2025). Newport News, VA Median Income by Age Groups Dataset: A Comprehensive Breakdown of Newport News Annual Median Income Across 4 Key Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/e94b6f8f-f353-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 25, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Newport News, Virginia
    Variables measured
    Income for householder under 25 years, Income for householder 65 years and over, Income for householder between 25 and 44 years, Income for householder between 45 and 64 years
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across four age groups (Under 25 years, 25 to 44 years, 45 to 64 years, and 65 years and over) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the distribution of median household income among distinct age brackets of householders in Newport News. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Newport News. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

    Key observations: Insights from 2023

    In terms of income distribution across age cohorts, in Newport News, householders within the 45 to 64 years age group have the highest median household income at $80,494, followed by those in the 25 to 44 years age group with an income of $67,947. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $53,857. Notably, householders within the under 25 years age group, had the lowest median household income at $46,744.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Age groups classifications include:

    • Under 25 years
    • 25 to 44 years
    • 45 to 64 years
    • 65 years and over

    Variables / Data Columns

    • Age Of The Head Of Household: This column presents the age of the head of household
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Newport News median household income by age. You can refer the same here

  3. a

    American Community Survey Median Household Income

    • hub.arcgis.com
    Updated Nov 18, 2025
    + more versions
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    trubel&co (2025). American Community Survey Median Household Income [Dataset]. https://hub.arcgis.com/maps/648ab1eff2bf40f38e23953a4edcef7c
    Explore at:
    Dataset updated
    Nov 18, 2025
    Dataset authored and provided by
    trubel&co
    Area covered
    Description

    From Esri Demographics: This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS):About the Survey Geography & ACS Technical Documentation News & Updates This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data. Data Note from the Census: 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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases. Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.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 median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate. The data for this geographic area cannot be displayed because the number of sample cases is too small.

  4. T

    United States Disposable Personal Income

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Disposable Personal Income [Dataset]. https://tradingeconomics.com/united-states/disposable-personal-income
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1959 - Aug 31, 2025
    Area covered
    United States
    Description

    Disposable Personal Income in the United States increased to 23033.50 USD Billion in August from 22947.50 USD Billion in July of 2025. This dataset provides - United States Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. F

    Income Inequality in Newport News city, VA

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
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    (2024). Income Inequality in Newport News city, VA [Dataset]. https://fred.stlouisfed.org/series/2020RATIO051700
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Newport News, Virginia
    Description

    Graph and download economic data for Income Inequality in Newport News city, VA (2020RATIO051700) from 2010 to 2023 about Newport News City, VA; Virginia Beach; inequality; VA; income; and USA.

  6. c

    Data from: Median Household Income

    • data.clevelandohio.gov
    Updated Aug 21, 2023
    + more versions
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    Cleveland | GIS (2023). Median Household Income [Dataset]. https://data.clevelandohio.gov/datasets/ClevelandGIS::demographic-profiles/about?layer=1
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey.

    This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053

    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • 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 median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

  7. H

    Replication Data for: "Whose News? Class-Biased Economic Reporting in the...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Apr 13, 2021
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    Timothy Hicks; Alan M. Jacobs; Eric Merkley; J. Scott Matthews (2021). Replication Data for: "Whose News? Class-Biased Economic Reporting in the United States" [Dataset]. http://doi.org/10.7910/DVN/Q9E8RF
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 13, 2021
    Dataset provided by
    Harvard Dataverse
    Authors
    Timothy Hicks; Alan M. Jacobs; Eric Merkley; J. Scott Matthews
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/Q9E8RFhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/Q9E8RF

    Area covered
    United States
    Description

    There is substantial evidence that voters’ choices are shaped by assessments of the state of the economy and that these assessments, in turn, are influenced by the news. But how does the economic news track the welfare of different income groups in an era of rising inequality? Whose economy does the news cover? Drawing on a large new dataset of U.S. news content, we demonstrate that the tone of the economic news strongly and disproportionately tracks the fortunes of the richest households, with little sensitivity to income changes among the non-rich. Further, we present evidence that this pro-rich bias emerges not from pro-rich journalistic preferences but, rather, from the interaction of the media’s focus on economic aggregates with structural features of the relationship between economic growth and distribution. The findings yield a novel explanation of distributionally perverse electoral patterns and demonstrate how distributional biases in the economy condition economic accountability.

  8. T

    Newport News City, VA - Income Inequality in Newport News city, VA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Nov 7, 2025
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    TRADING ECONOMICS (2025). Newport News City, VA - Income Inequality in Newport News city, VA [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-newport-news-city-va-fed-data.html
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset updated
    Nov 7, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Newport News, Virginia
    Description

    Newport News City, VA - Income Inequality in Newport News city, VA was 14.31700 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Newport News City, VA - Income Inequality in Newport News city, VA reached a record high of 14.81666 in January of 2021 and a record low of 11.44944 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Newport News City, VA - Income Inequality in Newport News city, VA - last updated from the United States Federal Reserve on November of 2025.

  9. T

    United States Wages and Salaries Growth

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Oct 16, 2025
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    TRADING ECONOMICS (2025). United States Wages and Salaries Growth [Dataset]. https://tradingeconomics.com/united-states/wage-growth
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Oct 16, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1960 - Aug 31, 2025
    Area covered
    United States
    Description

    Wages in the United States increased 4.86 percent in August of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  10. F

    Employed full time: Wage and salary workers: News analysts, reporters and...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
    + more versions
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    (2025). Employed full time: Wage and salary workers: News analysts, reporters and correspondents occupations: 16 years and over: Men [Dataset]. https://fred.stlouisfed.org/series/LEU0254592800A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Wage and salary workers: News analysts, reporters and correspondents occupations: 16 years and over: Men (LEU0254592800A) from 2000 to 2024 about analysts, reporters, occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.

  11. T

    United States Average Hourly Wages

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 15, 2025
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    TRADING ECONOMICS (2025). United States Average Hourly Wages [Dataset]. https://tradingeconomics.com/united-states/wages
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Sep 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1964 - Aug 31, 2025
    Area covered
    United States
    Description

    Wages in the United States increased to 31.46 USD/Hour in August from 31.34 USD/Hour in July of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  12. Newport News, VA, US Demographics 2025

    • point2homes.com
    html
    Updated 2025
    + more versions
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    Point2Homes (2025). Newport News, VA, US Demographics 2025 [Dataset]. https://www.point2homes.com/US/Neighborhood/VA/Newport-News-Demographics.html
    Explore at:
    htmlAvailable download formats
    Dataset updated
    2025
    Dataset authored and provided by
    Point2Homeshttps://plus.google.com/116333963642442482447/posts
    Time period covered
    2025
    Area covered
    United States, Newport News, Virginia
    Variables measured
    Asian, Other, White, 2 units, Over 65, Median age, Blue collar, Mobile home, 3 or 4 units, 5 to 9 units, and 72 more
    Description

    Comprehensive demographic dataset for Newport News, VA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

  13. Consumer Expenditure Survey Summary Tables

    • icpsr.umich.edu
    excel
    Updated Apr 14, 2025
    + more versions
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    United States. Bureau of Labor Statistics (2025). Consumer Expenditure Survey Summary Tables [Dataset]. http://doi.org/10.3886/ICPSR36170.v12
    Explore at:
    excelAvailable download formats
    Dataset updated
    Apr 14, 2025
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/36170/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36170/terms

    Time period covered
    2010 - 2023
    Area covered
    United States
    Description

    The Consumer Expenditure Survey (CE) program consists of two surveys: the quarterly Interview survey and the annual Diary survey. Combined, these two surveys provide information on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. The survey data are collected for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The CE collects all on all spending components including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. The CE tables are an easy-to-use tool for obtaining arts-related spending estimates. They feature several arts-related spending categories, including the following items: Spending on Admissions Plays, theater, opera, and concerts Movies, parks, and museums Spending on Reading Newspapers and magazines Books Digital book readers Spending on Other Arts-Related Items Musical instruments Photographic equipment Audio-visual equipment Toys, games, arts and crafts The CE is important because it is the only Federal survey to provide information on the complete range of consumers' expenditures and incomes, as well as the characteristics of those consumers. It is used by economic policymakers examining the impact of policy changes on economic groups, by the Census Bureau as the source of thresholds for the Supplemental Poverty Measure, by businesses and academic researchers studying consumers' spending habits and trends, by other Federal agencies, and, perhaps most importantly, to regularly revise the Consumer Price Index market basket of goods and services and their relative importance. The most recent data tables are for 2023 and include: 1) Detailed tables with the most granular level of expenditure data available, along with variances and percent reporting for each expenditure item, for all consumer units (listed as "Other" in the Download menu); and 2) Tables with calendar year aggregate shares by demographic characteristics that provide annual aggregate expenditures and shares across demographic groups (listed as "Excel" in the Download menu). Also, see Featured CE Tables and Economic News Releases sections on the CE home page for current data tables and news release. The 1980 through 2023 CE public-use microdata, including Interview Survey data, Diary Survey data, and paradata (information about the data collection process), are available on the CE website.

  14. FiveThirtyEight Police Killings Dataset

    • kaggle.com
    zip
    Updated Apr 26, 2019
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    FiveThirtyEight (2019). FiveThirtyEight Police Killings Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-police-killings-dataset
    Explore at:
    zip(53916 bytes)Available download formats
    Dataset updated
    Apr 26, 2019
    Dataset authored and provided by
    FiveThirtyEighthttps://abcnews.go.com/538
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Police Killings

    This directory contains the data behind the story Where Police Have Killed Americans In 2015.

    We linked entries from the Guardian's database on police killings to census data from the American Community Survey. The Guardian data was downloaded on June 2, 2015. More information about its database is available here.

    Census data was calculated at the tract level from the 2015 5-year American Community Survey using the tables S0601 (demographics), S1901 (tract-level income and poverty), S1701 (employment and education) and DP03 (county-level income). Census tracts were determined by geocoding addresses to latitude/longitude using the Bing Maps and Google Maps APIs and then overlaying points onto 2014 census tracts. GEOIDs are census-standard and should be easily joinable to other ACS tables -- let us know if you find anything interesting.

    Field descriptions:

    HeaderDescriptionSource
    nameName of deceasedGuardian
    ageAge of deceasedGuardian
    genderGender of deceasedGuardian
    raceethnicityRace/ethnicity of deceasedGuardian
    monthMonth of killingGuardian
    dayDay of incidentGuardian
    yearYear of incidentGuardian
    streetaddressAddress/intersection where incident occurredGuardian
    cityCity where incident occurredGuardian
    stateState where incident occurredGuardian
    latitudeLatitude, geocoded from address
    longitudeLongitude, geocoded from address
    state_fpState FIPS codeCensus
    county_fpCounty FIPS codeCensus
    tract_ceTract ID codeCensus
    geo_idCombined tract ID code
    county_idCombined county ID code
    namelsadTract descriptionCensus
    lawenforcementagencyAgency involved in incidentGuardian
    causeCause of deathGuardian
    armedHow/whether deceased was armedGuardian
    popTract populationCensus
    share_whiteShare of pop that is non-Hispanic whiteCensus
    share_bloackShare of pop that is black (alone, not in combination)Census
    share_hispanicShare of pop that is Hispanic/Latino (any race)Census
    p_incomeTract-level median personal incomeCensus
    h_incomeTract-level median household incomeCensus
    county_incomeCounty-level median household incomeCensus
    comp_incomeh_income / county_incomeCalculated from Census
    county_bucketHousehold income, quintile within countyCalculated from Census
    nat_bucketHousehold income, quintile nationallyCalculated from Census
    povTract-level poverty rate (official)Census
    urateTract-level unemployment rateCalculated from Census
    collegeShare of 25+ pop with BA or higherCalculated from Census

    Note regarding income calculations:

    All income fields are in inflation-adjusted 2013 dollars.

    comp_income is simply tract-level median household income as a share of county-level median household income.

    county_bucket provides where the tract's median household income falls in the distribution (by quintile) of all tracts in the county. (1 indicates a tract falls in the poorest 20% of tracts within the county.) Distribution is not weighted by population.

    nat_bucket is the same but for all U.S. counties.

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

  15. Consumer Expenditure Survey Summary Tables

    • icpsr.umich.edu
    Updated Apr 21, 2020
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    United States. Bureau of Labor Statistics (2020). Consumer Expenditure Survey Summary Tables [Dataset]. http://doi.org/10.3886/ICPSR36170.v7
    Explore at:
    Dataset updated
    Apr 21, 2020
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/36170/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36170/terms

    Time period covered
    2010 - 2018
    Area covered
    United States
    Description

    The Consumer Expenditure Survey (CE) program consists of two surveys: the quarterly Interview survey and the annual Diary survey. Combined, these two surveys provide information on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. The survey data are collected for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The CE collects all on all spending components including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. The CE features several arts-related spending categories, including the following items: Spending on Admissions Plays, theater, opera, and concerts Movies, parks, and museums Spending on Reading Newspapers and magazines Books Digital book readers Spending on Other Arts-Related Items Musical instruments Photographic equipment Audio-visual equipment Toys, games, arts and crafts The CE is important because it is the only Federal survey to provide information on the complete range of consumers' expenditures and incomes, as well as the characteristics of those consumers. It is used by economic policymakers examining the impact of policy changes on economic groups, by the Census Bureau as the source of thresholds for the Supplemental Poverty Measure, by businesses and academic researchers studying consumers' spending habits and trends, by other Federal agencies, and, perhaps most importantly, to regularly revise the Consumer Price Index market basket of goods and services and their relative importance. The most recent data tables are for 2018, and were made available on September 10, 2019. The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Excel" in the Dataset(s) section). Also, see Featured CE Tables and Economic News Releases sections on the CE home page for current data tables and news release. The 2018 public-use microdata is the most recent and was released on September 10, 2019.

  16. Quarterly Census of Employment and Wages (QCEW)

    • catalog.data.gov
    • data.ca.gov
    Updated Nov 23, 2025
    + more versions
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    California Employment Development Department (2025). Quarterly Census of Employment and Wages (QCEW) [Dataset]. https://catalog.data.gov/dataset/quarterly-census-of-employment-and-wages-qcew-a6fea
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    Dataset updated
    Nov 23, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels. Disclaimer: For information regarding future updates or preliminary/final data releases, please refer to the Bureau of Labor Statistics Release Calendar: https://www.bls.gov/cew/release-calendar.htm

  17. Consumer Expenditure Survey Summary Tables

    • icpsr.umich.edu
    Updated May 27, 2021
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    United States. Bureau of Labor Statistics (2021). Consumer Expenditure Survey Summary Tables [Dataset]. http://doi.org/10.3886/ICPSR36170.v8
    Explore at:
    Dataset updated
    May 27, 2021
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/36170/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36170/terms

    Time period covered
    2010 - 2019
    Area covered
    United States
    Description

    The Consumer Expenditure Survey (CE) program consists of two surveys: the quarterly Interview survey and the annual Diary survey. Combined, these two surveys provide information on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. The survey data are collected for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The CE collects all on all spending components including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. The CE features several arts-related spending categories, including the following items: Spending on Admissions Plays, theater, opera, and concerts Movies, parks, and museums Spending on Reading Newspapers and magazines Books Digital book readers Spending on Other Arts-Related Items Musical instruments Photographic equipment Audio-visual equipment Toys, games, arts and crafts The CE is important because it is the only Federal survey to provide information on the complete range of consumers' expenditures and incomes, as well as the characteristics of those consumers. It is used by economic policymakers examining the impact of policy changes on economic groups, by the Census Bureau as the source of thresholds for the Supplemental Poverty Measure, by businesses and academic researchers studying consumers' spending habits and trends, by other Federal agencies, and, perhaps most importantly, to regularly revise the Consumer Price Index market basket of goods and services and their relative importance. The most recent data tables are for 2019, and were made available on September 9, 2020. The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Excel" in the Dataset(s) section). Also, see Featured CE Tables and Economic News Releases sections on the CE home page for current data tables and news release. The 1980 through 2019 CE public-use microdata, including Interview Survey data, Diary Survey data, and paradata (information about the data collection process), are available on the CE website.

  18. State

    • data.amerigeoss.org
    csv, esri rest +4
    Updated Jan 14, 2020
    + more versions
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    ESRI (2020). State [Dataset]. https://data.amerigeoss.org/es/dataset/state11
    Explore at:
    kml, esri rest, html, zip, csv, geojsonAvailable download formats
    Dataset updated
    Jan 14, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description

    This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey.


    This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2014-2018
    ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053
    Date of API call: December 19, 2019
    National Figures: data.census.gov

    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • 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 median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.
      • NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

  19. D

    Incomes Occupations and Earnings - Seattle Neighborhoods

    • data.seattle.gov
    • data-seattlecitygis.opendata.arcgis.com
    • +1more
    csv, xlsx, xml
    Updated Oct 22, 2024
    + more versions
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    (2024). Incomes Occupations and Earnings - Seattle Neighborhoods [Dataset]. https://data.seattle.gov/dataset/Incomes-Occupations-and-Earnings-Seattle-Neighborh/5r7r-hvze
    Explore at:
    xml, csv, xlsxAvailable download formats
    Dataset updated
    Oct 22, 2024
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on income and earning related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B19025 Aggregate Household Income, B19013 Median Household Income, B19001 Household Income, B19113 Median Family Household Income, B19101 Family Household Income, B19202 Median Nonfamily Household Income, B19201 Nonfamily Household Income, B19301 Per Capita Income/B19313 Aggregate Income/B01001 Sex by Age, C24010 Sex by Occupation of the Civilian Employed Population 16 years and Over, B20017 Median Earnings by Sex by Work Experience for the Population 16 years and over with Earnings, B20001 Sex by Earnings for the Population 16 years and over with Earnings. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.


    Table created for and used in the Neighborhood Profiles application.

    Vintages: 2023


    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb(year)a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional <span style='font-family:inherit; margin:0px;

  20. c

    Poverty Status

    • data.clevelandohio.gov
    • opendatacle-clevelandgis.hub.arcgis.com
    • +1more
    Updated Aug 21, 2023
    + more versions
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    Cleveland | GIS (2023). Poverty Status [Dataset]. https://data.clevelandohio.gov/datasets/ClevelandGIS::poverty-status/about
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows poverty status by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Poverty status is based on income in past 12 months of survey.

    This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B17020, C17002

    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • 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 median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

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Cite
Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Newport News, VA // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/4837316e-f81d-11ef-a994-3860777c1fe6/

Income Distribution by Quintile: Mean Household Income in Newport News, VA // 2025 Edition

Explore at:
json, csvAvailable download formats
Dataset updated
Mar 3, 2025
Dataset authored and provided by
Neilsberg Research
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Newport News, Virginia
Variables measured
Income Level, Mean Household Income
Measurement technique
The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
Dataset funded by
Neilsberg Research
Description
About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Newport News, VA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

  • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,915, while the mean income for the highest quintile (20% of households with the highest income) is 213,538. This indicates that the top earners earn 14 times compared to the lowest earners.
  • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 391,727, which is 183.45% higher compared to the highest quintile, and 2626.40% higher compared to the lowest quintile.
Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

  • Lowest Quintile
  • Second Quintile
  • Third Quintile
  • Fourth Quintile
  • Highest Quintile
  • Top 5 Percent

Variables / Data Columns

  • Income Level: This column showcases the income levels (As mentioned above).
  • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Newport News median household income. You can refer the same here

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