In the United States, the median earnings of female workers in 1990 amounted to 26,110 U.S. dollars. In 2023, the earnings of the average female worker had increased to approximately 42,110 U.S. dollars. These earnings are adjusted to 2023 CPI-U-RS dollars.

In 2023, the median annual earnings of full-time male workers in the United States stood at ****** U.S. dollars after being adjusted for inflation, which was significantly higher than the median earnings of full-time women at ******. For further reading, see the female to male earnings ratio.

Average female and male earnings and female-to-male earnings ratio, Canada.

Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 to 24 years: Women (LEU0252883100Q) from Q1 2000 to Q2 2025 about 16 to 24 years, full-time, females, salaries, earnings, workers, wages, median, employment, real, and USA.

In Sweden, men earn slightly more than women. From 2016 to 2021, women's average earnings in the country were 96 percent of that of their male counterparts, but dropped to 95 percent in 2022. This is despite the fact that women have a higher educational level than men.Unequal pay, a frequently observed problem Even though women in Sweden earn less on average than men, the gender pay gap is smaller in Sweden than in several other European countries. However, in a survey about attitudes towards gender equality, equal pay for equal work was considered the second most important issue facing women and girls in Sweden today. Gender difference in the distribution among occupations and sectors The main reason for the lack of equal pay for men and women is that the latter group tends to work in occupations where average salaries are lower than in those dominated by men. For instance, the average salary in the human health sector in Sweden is 35,000 Swedish kronor, compared to 57,200 in financial institutions and insurance companies. The health care sector in the country has a high share of female employees.

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 2023

Based on our analysis ACS 2019-2023 5-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 $48,138 for males and $32,546 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 $67,966, while females earned $54,999, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 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.

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 United States median household income by race. You can refer the same here

The average monthly wage for female full-time workers in Japan amounted to ******* Japanese yen in 2024, which represented an increase of *** percent compared to 2023. The breakdown by age group showed that the average income was highest among women aged 50 to 54 years old.

Average and median gender pay ratio in annual employment income and in annual wages, salaries and commissions. Data are available by National Occupational Classification (NOC) and age group.

In 2024, the average annual full-time salary for men in the United Kingdom was 40,035 British pounds, compared with 34,000 pounds for women, a difference of just over 6,000 pounds. In the previous year, men earned an average annual salary of 37,382, compared with women who earned 31,672.

This comprehensive indicator offers detailed insights into the average hourly earnings derived from paid employment across various dimensions, including sex, occupation, age, and disability status. By examining the interplay of these factors, the indicator provides a nuanced understanding of wage differentials within the workforce. This information is invaluable for assessing patterns of income inequality, identifying potential areas for policy intervention, and fostering a more inclusive and equitable employment environment. Through its multifaceted approach, the indicator enables a thorough analysis of how various demographic variables intersect with earnings, thereby contributing to a more holistic comprehension of labor market dynamics and the socioeconomic landscape.

PS I hope this dataset will answer many of your questions and will be trigger to many new ones. I will read every comment and notebooks as I do it every time and hope to see your mind blowing conclusions. Good luck and thank you for being here

Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Black or African American: Women (LEU0252885200Q) from Q1 2000 to Q2 2025 about African-American, females, full-time, earnings, salaries, workers, 16 years +, wages, median, employment, real, and USA.

Indonesia Monthly Average Wage: Female data was reported at 2,178,134.000 IDR in 2018. This records an increase from the previous number of 2,070,274.000 IDR for 2017. Indonesia Monthly Average Wage: Female data is updated yearly, averaging 720,632.000 IDR from Aug 1994 (Median) to 2018, with 24 observations. The data reached an all-time high of 2,178,134.000 IDR in 2018 and a record low of 113,497.000 IDR in 1994. Indonesia Monthly Average Wage: Female data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GBB002: Monthly Average Wage: by Industry.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: 16 to 24 years: Women (LEU0252883000Q) from Q1 2000 to Q2 2025 about 16 to 24 years, second quartile, full-time, females, salaries, earnings, workers, wages, median, employment, and USA.

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 China. 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 China, the median income for all workers aged 15 years and older, regardless of work hours, was $58,750 for males and $30,313 for females.

These income figures highlight a substantial gender-based income gap in China. Women, regardless of work hours, earn 52 cents for each dollar earned by men. This significant gender pay gap, approximately 48%, underscores concerning gender-based income inequality in the city of China.

- Full-time workers, aged 15 years and older: In China, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,188, while females earned $69,375

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.12 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

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 China 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 Draper. 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 Draper, the median income for all workers aged 15 years and older, regardless of work hours, was $77,562 for males and $36,752 for females.

These income figures highlight a substantial gender-based income gap in Draper. Women, regardless of work hours, earn 47 cents for each dollar earned by men. This significant gender pay gap, approximately 53%, underscores concerning gender-based income inequality in the city of Draper.

- Full-time workers, aged 15 years and older: In Draper, among full-time, year-round workers aged 15 years and older, males earned a median income of $107,277, while females earned $65,027, leading to a 39% gender pay gap among full-time workers. This illustrates that women earn 61 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 Draper, 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 Draper median household income by race. You can refer the same here

Pakistan Average Monthly Wages: Female data was reported at 9,760.000 PKR in 2015. This records an increase from the previous number of 8,228.000 PKR for 2014. Pakistan Average Monthly Wages: Female data is updated yearly, averaging 6,422.000 PKR from Jun 2008 (Median) to 2015, with 7 observations. The data reached an all-time high of 9,760.000 PKR in 2015 and a record low of 3,853.000 PKR in 2008. Pakistan Average Monthly Wages: Female data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G004: Average Monthly Wages: By Industry.

In 2023, the median hourly rate of a female wageworker in the United States between 20 and 24 years old was 15.88 current U.S. dollars. Women between the ages of 35 and 44 years old made the most in that year, with a median hourly wage of 19.84 current U.S. dollars.

Median pay for women employed by the region as a percentage of median pay for men employed by the region. All salary reported is calculated as full-time salary, SEK/month. Full-time salary includes basic salary plus variable allowances and benefits. For employees aged 18-66 (until 2013 18-64 years) who are monthly or hourly paid. Employees of municipal-owned companies are not included.

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