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 Deciles of Income Before Taxes: Highest 10 Percent (91st to 100th Percentile) (CXUINCBEFTXLB1511M) from 2014 to 2023 about percentile, tax, 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.
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Context
The dataset presents the mean household income for each of the five quintiles in New Germany, MN, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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 New Germany median household income. You can refer the same here
The poorest five percent of the population in Brazil received a monthly income of merely *** reals in 2024, with their jobs as their only source of income. By contrast, the average income of workers who fall within the 40 percent to 50 percent percentile, and from 50 percent to 60 percent are **** and **** Brazilian reals, respectively.
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Context
The dataset presents the mean household income for each of the five quintiles in Greece, New York, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
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 Greece town median household income. 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 Q1 2025 about wealth, percentile, households, and USA.
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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.
In 2021, the average income of households among Israel's highest one percent of earners, reached *** million Israeli shekels, about *** 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 ** percent between 2013 and 2021.
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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
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Employment income is generally income (salary, wages, compensation, taxes, bonuses, compensation for job inventions, etc.) received in return for providing labor, which is a non-independent personal service, through an employment relationship or a similar contract, and is distinguished from business income, other income, and retirement income. (Employment income) Payment received for providing labor through an employment relationship or a similar contract → Withholding tax according to the simplified tax table (Business income) Payment received for continuously providing services in an independent capacity without an employment relationship → Withholding tax of 3% of the income amount (Other income) Payment received for temporarily providing services → Withholding tax of 20% of the other income amount (income amount - necessary expenses) (Retirement income) Income paid due to actual retirement based on employer contributions, etc. → Withholding tax upon retirement Employment income percentile (top 1%, 1,000th percentile) data - Number of people - Total salary amount (100 million won) - Employment income amount (100 million won) - Income deduction amount (100 million won) (Employment income deduction + Personal deduction + Pension insurance premium deduction + Special income deduction + Other income deduction - Amount exceeding income deduction limit) - Taxable standard (100 million won) - Determined tax amount (100 million won) This is the value of the total employment income for each quintile, and is expressed in 0.1% units only within the top 1%.
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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
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.
Upper income limit, income share and average of market, total and after-tax income by economic family type and income decile, annual.
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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
This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. The purpose of this dataset is to track the distribution of aggregate city income between the 5 quintile of population segments. The dataset comes from the 2019 U.S. Census Bureau, American Communities Survey (5yr) Table B19082. The row levels contain total percentage of income shares by the middle 3 quintiles (20-80%) of population. This data can be used to provide insights into growth/decline of middle class. Distribution of household income (Note: This indicator can provide insights into growth/decline of middle class) View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/Distribution-of-Household-Income/i3a3-vjnc/
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Hudson, OH, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
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 Hudson median household income. You can refer the same here
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.
The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.
Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.
Small changes in estimates between years should be treated with caution as they may not be statistically significant.
Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm
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Graph and download economic data for Household Count in the Bottom 50% (1st to 50th Wealth Percentiles) (WFRBLB50300) from Q3 1989 to Q1 2025 about 1 to 49, wealth, percentile, households, and USA.
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.