This statistic shows the median household income in the United States from 1970 to 2020, by income tier. In 2020, the median household income for the middle class stood at 90,131 U.S. dollars, which was approximately a 50 percent increase from 1970. However, the median income of upper income households in the U.S. increased by almost 70 percent compared to 1970.
This statistic shows the average income of a middle class family in the United States in 2014, by state. In 2014, the average middle-class family in Alaska had an income of ****** U.S. dollars per year. This was significantly higher than the national average of ****** U.S. dollars.
In G20 countries, the share of the population that earned at least the equivalent of the highest 10 percent of global income earners as of 2022 in purchasing power parity (PPP) terms varies from over two thirds in Australia to only *** percent in Indonesia. The United States recorded the second-highest upper-class share of the G20 countries. However, looking at for instance China, approximately ** percent of the population counts as middle class or above, whereas just ***** percent counts as upper class or higher.
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 Rich County: 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 Rich County median household income by age. You can refer the same here
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.
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 Rich Square. The dataset can be utilized to gain insights into gender-based income distribution within the Rich Square population, 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
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 Rich Square median household income by race. You can refer the same here
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 based on national threshold values, regardless of selected geography; 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% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.
In 2024, the highest salary-earning households in Tokyo Prefecture made close to *********** Japanese yen on average per month. By comparison, the gross income of the lowest-paid households in the prefecture amounted to around ******* yen a month.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
In the 3 years to March 2021, black households were most likely out of all ethnic groups to have a weekly income of under £600.
Income statistics by economic family type and income source, annual.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Rich Square. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Rich Square, the median income for all workers aged 15 years and older, regardless of work hours, was $24,265 for males and $17,431 for females.
These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Rich Square. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Rich Square.
- Full-time workers, aged 15 years and older: In Rich Square, among full-time, year-round workers aged 15 years and older, males earned a median income of $45,893, while females earned $36,089, leading to a 21% gender pay gap among full-time workers. This illustrates that women earn 79 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Rich Square, showcasing a consistent income pattern irrespective of employment status.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
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 Rich Square median household income by race. 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 median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Rich County. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Rich County, the median income for all workers aged 15 years and older, regardless of work hours, was $45,000 for males and $22,645 for females.
These income figures highlight a substantial gender-based income gap in Rich County. Women, regardless of work hours, earn 50 cents for each dollar earned by men. This significant gender pay gap, approximately 50%, underscores concerning gender-based income inequality in the county of Rich County.
- Full-time workers, aged 15 years and older: In Rich County, among full-time, year-round workers aged 15 years and older, males earned a median income of $72,653, while females earned $35,278, leading to a 51% gender pay gap among full-time workers. This illustrates that women earn 49 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Rich County, showcasing a consistent income pattern irrespective of employment status.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
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 Rich County median household income by race. You can refer the same here
This statistic shows a forecast of the distribution of urban households across income classes in China in 2022. In 2022, around ** percent of the Chinese urban households would become upper middle class, while nine percent would be considered as wealthy.
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 Middle Inlet, Wisconsin, 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 Middle Inlet town 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
Key information about Russia Household Income per Capita
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Disposable Income per Capita: Urban: Middle Income data was reported at 48,508.000 RMB in 2024. This records an increase from the previous number of 46,276.000 RMB for 2023. Disposable Income per Capita: Urban: Middle Income data is updated yearly, averaging 8,678.295 RMB from Dec 1985 (Median) to 2024, with 40 observations. The data reached an all-time high of 48,508.000 RMB in 2024 and a record low of 737.280 RMB in 1985. Disposable Income per Capita: Urban: Middle Income 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: Income by Income Level. Since 2013, All households in the sample are grouped, by per capita disposable income of the household, into groups of low income, lower middle income, middle income, upper middle income, and high income, each group consisting of 20%, 20%, 20%, 20%, and 20% of all households respectively.
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
75% of households from the Bangladeshi ethnic group were in the 2 lowest income quintiles (after housing costs were deducted) between April 2021 and March 2024.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to Jul 2025 about disposable, personal income, personal, income, real, and USA.
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 Rich Square: 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) 2018-2022 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 Rich Square median household income by age. You can refer the same here
This statistic shows the median household income in the United States from 1970 to 2020, by income tier. In 2020, the median household income for the middle class stood at 90,131 U.S. dollars, which was approximately a 50 percent increase from 1970. However, the median income of upper income households in the U.S. increased by almost 70 percent compared to 1970.