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.
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Graph and download economic data for Income Before Taxes: Income Before Taxes by Quintiles of Income Before Taxes: Fourth 20 Percent (61st to 80th Percentile) (CXUINCBEFTXLB0105M) from 1984 to 2023 about percentile, tax, income, and USA.
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Graph and download economic data for Income Before Taxes: Wages and Salaries by Deciles of Income Before Taxes: Ninth 10 Percent (81st to 90th Percentile) (CXU900000LB1510M) from 2014 to 2023 about percentile, salaries, tax, wages, income, and USA.
A breakdown of annual household incomes in Japan showed that around ***** percent of households earned less than *** million Japanese yen per year as of 2024. That year, the average annual household income of Japanese households was approximately *** million yen compared to a median household income of *** million yen.
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.
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Graph and download economic data for Expenditures: Total Average Annual Expenditures by Deciles of Income Before Taxes: Sixth 10 Percent (51st to 60th Percentile) (CXUTOTALEXPLB1507M) from 2014 to 2023 about percentile, average, tax, expenditures, income, and USA.
In 2022, the median annual tech wage corresponding to the **** percentile in the United States was reported as ******* U.S. dollars. The **** percentile for tech wages in the U.S. was ******* U.S. dollars for that same year.
Data on the average annual gross salary percentiles in the United Kingdom (UK) in 2020, by gender, shows that while women's average annual gross pay for the tenth percentile was around 6.8 thousand British pounds in 2020, the male average was more than twice as high in the same percentile. The female percentile with the highest annual pay averaged at 45.3 thousand British pounds, but was exceeded by the male average by 65 thousand in 2020.
This statistic shows the distribution of annual disposable personal income in Taiwan in 2023 among a total of around **** million income recipients. In 2023, approximately ******* individuals in Taiwan had over *** million New Taiwan dollars in disposable income.
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License information was derived automatically
Context
The dataset tabulates the median household income in Austin. It can be utilized to understand the trend in median household income and to analyze the income distribution in Austin by household type, size, and across various income brackets.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Austin median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Los Angeles: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Los Angeles median household income by age. You can refer the same here
As surveyed by Infocus Mekong in 2020, around ** percent of households in Vietnam had an income from ********** to ********** Vietnamese dong. Meanwhile, ***** percent of them stated to have an income of under ********* Vietnamese dong.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Savoy: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Savoy median household income by age. You can refer the same here
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Graph and download economic data for Household Count in the 50th to 90th Wealth Percentiles (WFRBLN40301) from Q3 1989 to Q2 2025 about wealth, percentile, households, and USA.
Upper income limit, income share and average of market, total and after-tax income by economic family type and income decile, annual.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Denver: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Denver median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Orange County household income by age. The dataset can be utilized to understand the age-based income distribution of Orange County income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Orange County income distribution by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
China % of Household grouped by Annual Income: Urban:RMB80000-85000 data was reported at 3.330 % in 2011. This records an increase from the previous number of 3.010 % for 2010. China % of Household grouped by Annual Income: Urban:RMB80000-85000 data is updated yearly, averaging 2.030 % from Dec 2005 (Median) to 2011, with 7 observations. The data reached an all-time high of 3.330 % in 2011 and a record low of 0.780 % in 2005. China % of Household grouped by Annual Income: Urban:RMB80000-85000 data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Household Income Distribution: Urban.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within United States. The dataset can be utilized to gain insights into gender-based income distribution within the United States population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/united-states-income-distribution-by-gender-and-employment-type.jpeg" alt="United States gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for United States median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This file contains measured and modeled breast cancer rates by stage and median household income percentile in New York State, 2006-2015. It accompanies the book chapter, "Spatial and Contextual Analyses of Stage at Diagnosis" by Francis Boscoe and Lindsey Hutchison, in Geospatial Approaches to Energy Balance and Breast Cancer. D Berrigan, NA Berger, eds. Berlin: Springer, 2018..4,835 census tracts in New York State were divided into percentiles based on median household income, using data from the 2006-2010 and 2011-2015 editions of American Community Survey Table S1903. Census tracts are defined here:https://figshare.com/articles/Population_Estimates_by_Census_Tract_New_York_State_by_Age_and_Sex_1990-2016_/681302958 of the 4,893 census tracts in this file did not have households (primarily college campuses, prisons, and military bases) and thus had no reported median household income and were excluded, leaving 4,835.200,022 cases of breast cancer diagnosed among New York State residents from 2006-2015 were assigned an income percentile. Cases diagnosed between 2006-2010 were assigned based on the 2006-2010 edition of ACS Table S1903 and cases diagnosed between 2011-2015 were assigned based on the 2011-2015 edition.Directly-adjusted incidence rates were calculated for all cancers and for those diagnosed at in situ, local, regional, and distant stage, using the SEER Summary Stage 2000 staging system. The file contains the following fields: income percentile; rates for all cancers, in situ, local, regional, and distant stage; and modeled rates for all cancers, in situ, local, regional and distant stages. The modeled rates used a polynomial of order 3. The equations of the best-fit lines and r-squared values, to 4 decimal places or significant figures, are as follows:All cancers: y = 0.0001986x3 - 0.02035x2 + 1.0691x + 133.7353, r2 = 0.96In situ: y = 0.00008906x3 - 0.007555x2 + 0.3169x + 27.5728, r2 = 0.96Local: y = 0.0001436x3 - 0.01919x2 + 1.0526x + 58.4627, r2 = 0.94Regional: y = -0.00001676x3 + 0.003410x2 - 0.1389x + 37.6709, r2 = 0.41Distant: y = -0.00001724x3 + 0.002989x2 - 0.1615x + 10.0288, r2 = 0.32
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.