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.

In 2023, around 10.3 percent of U.S. private households had an annual income between 35,000 and 49,999 U.S. dollars in the United States. Income levels between 100,000 to 149,999 U.S. dollars made up the largest share of the population at 16.5 percent in 2023.

Graph and download economic data for Income Before Taxes: Wages and Salaries by Quintiles of Income Before Taxes: Second 20 Percent (21st to 40th Percentile) (CXU900000LB0103M) from 1984 to 2023 about percentile, salaries, tax, wages, income, and USA.

An average of 79% of Bangladeshi households were in the 2 lowest income quintiles (after housing costs were deducted) between April 2019 and March 2022

Egypt Average Household Income: Percentage Distribution: Wages and Salaries data was reported at 67.100 % in 2015. This records a decrease from the previous number of 70.300 % for 2013. Egypt Average Household Income: Percentage Distribution: Wages and Salaries data is updated yearly, averaging 70.400 % from Jun 2005 (Median) to 2015, with 5 observations. The data reached an all-time high of 74.600 % in 2005 and a record low of 67.100 % in 2015. Egypt Average Household Income: Percentage Distribution: Wages and Salaries data remains active status in CEIC and is reported by Central Agency for Public Mobilization and Statistics. The data is categorized under Global Database’s Egypt – Table EG.H012: Average Household Income.

Egypt Average Household Income: Percentage Distribution: Urban: Wages and Salaries data was reported at 63.900 % in 2015. This records a decrease from the previous number of 67.800 % for 2013. Egypt Average Household Income: Percentage Distribution: Urban: Wages and Salaries data is updated yearly, averaging 67.800 % from Jun 2005 (Median) to 2015, with 5 observations. The data reached an all-time high of 72.400 % in 2005 and a record low of 63.900 % in 2015. Egypt Average Household Income: Percentage Distribution: Urban: Wages and Salaries data remains active status in CEIC and is reported by Central Agency for Public Mobilization and Statistics. The data is categorized under Global Database’s Egypt – Table EG.H012: Average Household Income.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in United States, 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

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 16,840, while the mean income for the highest quintile (20% of households with the highest income) is 285,351. This indicates that the top earners earn 17 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 515,555, which is 180.67% higher compared to the highest quintile, and 3061.49% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income. You can refer the same here

U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2023 about personal income, personal, median, income, real, and USA.

Distribution of employment income of individuals by sex and work activity, Canada, provinces and selected census metropolitan areas, annual.

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

Key information about United States Monthly Earnings

• United States Monthly Earnings stood at 4,901 USD in Feb 2025, compared with the previous figure of 4,887 USD in Jan 2025
• US Monthly Earnings data is updated monthly, available from Mar 2006 to Feb 2025, with an average number of 3,469 USD
• The data reached the an all-time high of 4,901 USD in Feb 2025 and a record low of 2,743 USD in Mar 2006

CEIC calculates Monthly Earnings from Average Weekly Earnings multiplied by 4. U.S. Bureau of Labor Statistics provides Average Weekly Earnings in USD. Monthly Earnings include Private Non Agricultural sector only.


Further information about United States Monthly Earnings

• In the latest reports, US Population reached 341 million people in Dec 2024
• Unemployment Rate of US increased to 4 % in Feb 2025
• The country's Labour Force Participation Rate remained the same rate at 62 % in Feb 2025

About this dataset

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 Neenah. 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 Neenah, the median income for all workers aged 15 years and older, regardless of work hours, was $51,729 for males and $36,037 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Neenah. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Neenah.

- Full-time workers, aged 15 years and older: In Neenah, among full-time, year-round workers aged 15 years and older, males earned a median income of $65,337, while females earned $50,877, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 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 Neenah, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Neenah median household income by race. You can refer the same here

About this dataset

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 Industry town. 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Industry town, the median income for all workers aged 15 years and older, regardless of work hours, was $49,429 for males and $24,321 for females.

These income figures highlight a substantial gender-based income gap in Industry town. Women, regardless of work hours, earn 49 cents for each dollar earned by men. This significant gender pay gap, approximately 51%, underscores concerning gender-based income inequality in the town of Industry town.

- Full-time workers, aged 15 years and older: In Industry town, among full-time, year-round workers aged 15 years and older, males earned a median income of $56,447, while females earned $33,508, leading to a 41% gender pay gap among full-time workers. This illustrates that women earn 59 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 Industry town, showcasing a consistent income pattern irrespective of employment status.

https://i.neilsberg.com/ch/industry-me-income-by-gender.jpeg" alt="Industry, Maine gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Industry town median household income by gender. You can refer the same here

About this dataset

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 Davis. 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 Davis, the median income for all workers aged 15 years and older, regardless of work hours, was $45,837 for males and $32,301 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Davis. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Davis.

- Full-time workers, aged 15 years and older: In Davis, among full-time, year-round workers aged 15 years and older, males earned a median income of $94,742, while females earned $73,926, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 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 Davis, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Davis median household income by race. You can refer the same here

About this dataset

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 United States. 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 2022

Based on our analysis ACS 2022 1-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In United States, the median income for all workers aged 15 years and older, regardless of work hours, was $46,036 for males and $31,298 for females.

These income figures highlight a substantial gender-based income gap in United States. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the country of United States.

- Full-time workers, aged 15 years and older: In United States, among full-time, year-round workers aged 15 years and older, males earned a median income of $64,040, while females earned $52,409, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 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.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in United States.

https://i.neilsberg.com/ch/united-states-income-by-gender.jpeg" alt="United States gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income by gender. You can refer the same here

About this dataset

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 Vian. 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Vian, the median income for all workers aged 15 years and older, regardless of work hours, was $23,355 for males and $16,833 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 Vian. 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 Vian.

- Full-time workers, aged 15 years and older: In Vian, among full-time, year-round workers aged 15 years and older, males earned a median income of $39,183, while females earned $30,401, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 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 Vian, showcasing a consistent income pattern irrespective of employment status.

https://i.neilsberg.com/ch/vian-ok-income-by-gender.jpeg" alt="Vian, OK gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Vian median household income by gender. You can refer the same here

About this dataset

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 Wiley. 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 Wiley, the median income for all workers aged 15 years and older, regardless of work hours, was $45,000 for males and $34,271 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 24% between the median incomes of males and females in Wiley. With women, regardless of work hours, earning 76 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Wiley.

- Full-time workers, aged 15 years and older: In Wiley, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,333, while females earned $44,464, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 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 Wiley, showcasing a consistent income pattern irrespective of employment status.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Wiley median household income by race. You can refer the same here