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TwitterThe 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.
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TwitterThe 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
https://i.neilsberg.com/ch/greece-ny-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in Greece, New York (in 2022 inflation-adjusted dollars))">
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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TwitterA 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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The dataset presents the mean household income for each of the five quintiles in Switzerland County, IN, 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
https://i.neilsberg.com/ch/switzerland-county-in-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in Switzerland County, IN (in 2022 inflation-adjusted dollars))">
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 Switzerland County median household income. You can refer the same here
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The dataset presents the mean household income for each of the five quintiles in Mexico, MO, 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 Mexico median household income. You can refer the same here
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TwitterAs 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.
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The dataset tabulates the median household income in New York. It can be utilized to understand the trend in median household income and to analyze the income distribution in New York 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 New York median household income. You can refer the same here
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TwitterThe 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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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.
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TwitterIn the post-Covid financial year of 2021, the poorest ** percent of households witnessed income levels shrink by ** percent from levels in financial year 2016. The pandemic resulted in the gap between the richest and the poorest ** percent from *** times in financial year 2016 to ** times in financial year 2021. In the financial year 2023, the gap narrowed down to ***** times.
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Context
The dataset presents the mean household income for each of the five quintiles in Ventura County, CA, 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 Ventura County median household income. You can refer the same here
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Source: U.S. Census Bureau; American Community Survey, 2019-2023 American Community Survey 5-Year Estimates, Table B19001; generated by CCRPC staff; using data.census.gov; https://data.census.gov/cedsci/; (31 March 2025).
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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
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License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Duluth, 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 Duluth median household income. You can refer the same here
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License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Orange, CA, 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 Orange median household income. You can refer the same here
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License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Louisville, 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) 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 Louisville town median household income. You can refer the same here
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Context
The dataset presents the mean household income for each of the five quintiles in Multnomah County, OR, 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 Multnomah County median household income. You can refer the same here
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License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Madison, WI, 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
https://i.neilsberg.com/ch/madison-wi-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in Madison, WI (in 2022 inflation-adjusted dollars))">
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 Madison median household income. You can refer the same here
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TwitterThe 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.