95 datasets found
  1. U.S. household income distribution 2023

    • statista.com
    • flwrdeptvarieties.store
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income distribution 2023 [Dataset]. https://www.statista.com/statistics/203183/percentage-distribution-of-household-income-in-the-us/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

  2. F

    Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles)...

    • fred.stlouisfed.org
    json
    Updated Mar 21, 2025
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    Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBSTP1300
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    jsonAvailable download formats
    Dataset updated
    Mar 21, 2025
    License

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

    Description

    Graph and download economic data for Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBSTP1300) from Q3 1989 to Q4 2024 about shares, net worth, wealth, percentile, Net, and USA.

  3. U.S. wealth distribution Q2 2024

    • statista.com
    Updated Oct 29, 2024
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    Statista (2024). U.S. wealth distribution Q2 2024 [Dataset]. https://www.statista.com/statistics/203961/wealth-distribution-for-the-us/
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    Dataset updated
    Oct 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.

  4. High income tax filers in Canada, specific geographic area thresholds

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Oct 28, 2024
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    Government of Canada, Statistics Canada (2024). High income tax filers in Canada, specific geographic area thresholds [Dataset]. http://doi.org/10.25318/1110005601-eng
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    Dataset updated
    Oct 28, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are geography-specific; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% income threshold of Nova Scotian tax filers. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

  5. Table 3.1a Percentile points from 1 to 99 for total income before and after...

    • gov.uk
    Updated Mar 12, 2025
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    Table 3.1a Percentile points from 1 to 99 for total income before and after tax [Dataset]. https://www.gov.uk/government/statistics/percentile-points-from-1-to-99-for-total-income-before-and-after-tax
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    HM Revenue & Customs
    Description

    The table only covers individuals who have some liability to Income Tax. The percentile points have been independently calculated on total income before tax and total income after tax.

    These statistics are classified as accredited official statistics.

    You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.

    Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.

    Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.

  6. U.S. quarterly wealth distribution 1989-2024, by income percentile

    • statista.com
    Updated Mar 19, 2025
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    Statista (2025). U.S. quarterly wealth distribution 1989-2024, by income percentile [Dataset]. https://www.statista.com/statistics/299460/distribution-of-wealth-in-the-united-states/
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    Dataset updated
    Mar 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the third quarter of 2024, the top ten percent of earners in the United States held over 67 percent of total wealth. This is fairly consistent with the second quarter of 2024. Comparatively, the wealth of the bottom 50 percent of earners has been slowly increasing since the start of the 2010s, though remains low. Wealth distribution in the United States by generation can be found here.

  7. Average earnings by percentile in Russia 2021

    • statista.com
    Updated Dec 16, 2024
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    Average earnings by percentile in Russia 2021 [Dataset]. https://www.statista.com/statistics/1364375/average-income-by-percentile-russia/
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    Dataset updated
    Dec 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Russia
    Description

    The bottom 50 percent in Russia earned an average of 7.7 thousand euros at purchasing power parity (PPP) before income tax in 2021. To compare, the mean income of the top 10 percent stood at 104.6 thousand euros in the same year. Looking at the percentage distribution of national wealth in the country, the poorest half held only three percent of the total in 2021.

  8. Income share of top one percent of earners in the UK 1980-2022

    • statista.com
    Updated Aug 7, 2024
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    Statista (2024). Income share of top one percent of earners in the UK 1980-2022 [Dataset]. https://www.statista.com/statistics/1234074/top-one-percent-income-uk/
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    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom
    Description

    In 2022 the top one percent of earners in the United Kingdom accounted for around 10.2 percent of the overall national income of the UK. The share of national income earned by the top one percent increased from 6.8 percent in 1980 to a peak of 14.8 percent in 2007.

  9. Income of individuals by age group, sex and income source, Canada, provinces...

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Apr 26, 2024
    + more versions
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    Government of Canada, Statistics Canada (2024). Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas [Dataset]. http://doi.org/10.25318/1110023901-eng
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    Dataset updated
    Apr 26, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

  10. F

    Share of Financial Assets Held by the Top 1% (99th to 100th Wealth...

    • fred.stlouisfed.org
    json
    Updated Mar 21, 2025
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    (2025). Share of Financial Assets Held by the Top 1% (99th to 100th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBST01112
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    jsonAvailable download formats
    Dataset updated
    Mar 21, 2025
    License

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

    Description

    Graph and download economic data for Share of Financial Assets Held by the Top 1% (99th to 100th Wealth Percentiles) (WFRBST01112) from Q3 1989 to Q4 2024 about wealth, percentile, financial, assets, and USA.

  11. A

    Australia Percentage of Households: One Family: Other: Source of Income:...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Australia Percentage of Households: One Family: Other: Source of Income: Wages And Salaries [Dataset]. https://www.ceicdata.com/en/australia/survey-of-income-and-housing-percentage-of-households-by-source-of-income/percentage-of-households-one-family-other-source-of-income-wages-and-salaries
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2003 - Jun 1, 2020
    Area covered
    Australia
    Variables measured
    Household Income and Expenditure Survey
    Description

    Australia Percentage of Households: One Family: Other: Source of Income: Wages And Salaries data was reported at 71.700 % in 2020. This records an increase from the previous number of 68.600 % for 2018. Australia Percentage of Households: One Family: Other: Source of Income: Wages And Salaries data is updated yearly, averaging 72.150 % from Jun 2003 (Median) to 2020, with 10 observations. The data reached an all-time high of 79.500 % in 2003 and a record low of 68.600 % in 2018. Australia Percentage of Households: One Family: Other: Source of Income: Wages And Salaries data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H040: Survey of Income and Housing: Percentage of Households: by Source of Income.

  12. Average income of the top percentile households in Israel 2013-2021

    • statista.com
    Updated Oct 9, 2024
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    Statista (2024). Average income of the top percentile households in Israel 2013-2021 [Dataset]. https://www.statista.com/statistics/1497463/israel-annual-average-income-of-top-percentile-households/
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    Dataset updated
    Oct 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Israel
    Description

    In 2021, the average income of households among Israel's highest one percent of earners, reached 4.7 million Israeli shekels, about 1.2 million U.S. dollars. Moreover, incomes peaked in 2017, due to a one-time tax incentive introduced by the government to release "trapped" capital gains tax. Overall, the average income of wealthy families in the country increased by 62 percent between 2013 and 2021.

  13. F

    Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles)

    • fred.stlouisfed.org
    json
    Updated Mar 21, 2025
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    (2025). Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBLB50107
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    jsonAvailable download formats
    Dataset updated
    Mar 21, 2025
    License

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

    Description

    Graph and download economic data for Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) (WFRBLB50107) from Q3 1989 to Q4 2024 about net worth, wealth, percentile, Net, and USA.

  14. V

    Virginia Median Household Income in the Past 12 Months by Census County (ACS...

    • data.virginia.gov
    csv
    Updated Jan 3, 2025
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    Office of INTERMODAL Planning and Investment (2025). Virginia Median Household Income in the Past 12 Months by Census County (ACS 5-Year) [Dataset]. https://data.virginia.gov/bs/dataset/activity/virginia-median-household-income-in-the-past-12-months-by-census-county-acs-5-year
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    csv(93377)Available download formats
    Dataset updated
    Jan 3, 2025
    Dataset authored and provided by
    Office of INTERMODAL Planning and Investment
    Area covered
    Virginia
    Description

    2013-2023 Virginia Median Household Income based on the past 12 months by Census County or County equivalent. Contains estimates and margins of error.

    U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table B19013 Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

    The United States Census Bureau's American Community Survey (ACS): -What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html) -Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html) -Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

    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. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

    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. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

    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 https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

    Annotation values are character representations of estimates and have values when non-integer information needs to be represented. Below are a few examples. Complete information is available on the ACS website under Notes on ACS Estimate and Annotation Values. (https://www.census.gov/data/developers/data-sets/acs-1year/notes-on-acs-estimate-and-annotation-values.html)

    A value of -666,666,666 in the estimate column 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 value of -222,222,222 in 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.

  15. Average earnings by percentile in Mexico 2022

    • statista.com
    Updated Oct 7, 2024
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    Statista (2024). Average earnings by percentile in Mexico 2022 [Dataset]. https://www.statista.com/statistics/1295017/average-income-by-percentile-mexico/
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    Dataset updated
    Oct 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Mexico
    Description

    In Mexico, as of 2022, the bottom 50 percent, which represents the population whose income lied below the median, earned on average 2,076 euros at purchasing power parity (PPP) before income taxes. Meanwhile, the top ten percent had an average earning of 111,484 euros, 53 times over than the average earning of the bottom half. Further, the bottom 50 percent accounted for -0.3 percent of the overall national wealth in Mexico, that is, they have on average more debts than assets.

  16. U.S. household income percentage distribution 2023, by race and ethnicity

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income percentage distribution 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/203207/percentage-distribution-of-household-income-in-the-us-by-ethnic-group/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, about 26.9 percent of Asian private households in the U.S. had an annual income of 200,000 U.S. dollars and more. Comparatively, around 13.9 percent of Black households had an annual income under 15,000 U.S. dollars.

  17. Average monthly pay of employees in the UK in 2025, by percentile

    • statista.com
    Updated Nov 13, 2024
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    Statista (2024). Average monthly pay of employees in the UK in 2025, by percentile [Dataset]. https://www.statista.com/statistics/1224844/monthly-pay-of-employees-uk/
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    Dataset updated
    Nov 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2025
    Area covered
    United Kingdom
    Description

    In January 2025, the top one percent of earners in the United Kingdom received an average pay of 15,882 British pounds per month, compared with the bottom 10 percent of earners who earned 813 pounds a month.

  18. 2023 American Community Survey: B99192 | Allocation of Household Income in...

    • data.census.gov
    Updated Aug 21, 2024
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    ACS (2024). 2023 American Community Survey: B99192 | Allocation of Household Income in the Past 12 Months - Percent of Income Allocated (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table?q=Allcare%20Chiropractic
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    Dataset updated
    Aug 21, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  19. ACS Earnings by Occupation by Sex Variables - Centroids

    • hub.arcgis.com
    Updated Oct 20, 2018
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    Esri (2018). ACS Earnings by Occupation by Sex Variables - Centroids [Dataset]. https://hub.arcgis.com/maps/6ebda2af47c349a8a7f0e357b2dfbf5a
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    Dataset updated
    Oct 20, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows median earnings by occupational group broken down by sex. This is shown by tract, county, and state centroids. 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. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. 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): B24022 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis 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.

  20. 2022 American Community Survey: B25070 | Gross Rent as a Percentage of...

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    ACS, 2022 American Community Survey: B25070 | Gross Rent as a Percentage of Household Income in the Past 12 Months (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2022.B25070
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program 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..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.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..The 2022 American Community Survey (ACS) data generally reflect the March 2020 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 2020 Census 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

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Statista (2024). U.S. household income distribution 2023 [Dataset]. https://www.statista.com/statistics/203183/percentage-distribution-of-household-income-in-the-us/
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U.S. household income distribution 2023

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50 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 16, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

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