The difference between the earnings of women and men shrank slightly over the past years. Considering the controlled gender pay gap, which measures the median salary for men and women with the same job and qualifications, women earned one U.S. cent less. By comparison, the uncontrolled gender pay gap measures the median salary for all men and all women across all sectors and industries and regardless of location and qualification. In 2025, the uncontrolled gender pay gap in the world stood at 0.83, meaning that women earned 0.83 dollars for every dollar earned by men.

Annual gender pay gap estimates for UK employees by age, occupation, industry, full-time and part-time, region and other geographies, and public and private sector. Compiled from the Annual Survey of Hours and Earnings.

In 2024, the gender pay gap in Germany was around 16 percent. This meant that wages for men were on average 16 percent higher than for women. Figures have gradually decreased since 2009.

Introduction

Gender Pay Gap Statistics: The gender pay gap remains a persistent issue globally, with women earning, on average, 20% less than men. This means women earn 80 cents for every dollar earned by men. At the current rate of progress, it could take approximately 132 years to close this gap.

This disparity is evident across various industries, with women in finance and technology earning as much as 25% less than their male counterparts. The gap is even more pronounced among women, with Black and Hispanic women earning 37% and 46% less, respectively, than white men.

Despite advancements in gender equality, pay inequality continues to hinder women’s economic c and long-term financial security. Addressing this gap requires systemic change, including pay transparency, policy reforms, and active corporate strategies.

The statistic shows the female to male earnings ratio in the United States in the fourth quarter of 2022, based on the median income in current U.S. dollars, by age group. In the fourth quarter of 2022, the earnings ratio of female to male workers aged between 16 to 24 years was at about 92.9 percent.

This table describes gender pay gap and is defined as the ratio of the gross earnings between women and men. The disaggregation variables are subject to data availability and where the numbers are lesser than 6, the disaggregation will be dropped.

Find more Pacific data on PDH.stat.

The indicator measures the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The indicator has been defined as unadjusted, because it gives an overall picture of gender inequalities in terms of pay and measures a concept which is broader than the concept of equal pay for equal work. All employees working in firms with ten or more employees, without restrictions for age and hours worked, are included.

In 2023, the Rhode Island had the highest earnings ratio for women, as female workers earned ***** percent of their male counterparts on average. The state of Louisiana had the lowest earnings ratio for female workers, who earned ***** percent of what their male counterparts earn.

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 Van Meter. 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 Van Meter, the median income for all workers aged 15 years and older, regardless of work hours, was $71,458 for males and $48,500 for females.

These income figures highlight a substantial gender-based income gap in Van Meter. 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 city of Van Meter.

- Full-time workers, aged 15 years and older: In Van Meter, among full-time, year-round workers aged 15 years and older, males earned a median income of $85,238, while females earned $56,750, leading to a 33% gender pay gap among full-time workers. This illustrates that women earn 67 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 Van Meter, 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 Van Meter median household income by race. You can refer the same here

Men in the European Union earned approximately 12 percent more than women in 2023, with Latvia having the biggest gender pay gap of 19 percent and Luxembourg having the lowest at minus 0.9 percent, meaning that on average women actually earned more than men in Luxembourg during that year.

In 2021, female employee earnings were outpaced by male earnings across nearly all industries, with sharp disparities in the professional and technical services industry, as well as the finance and insurance industry. In that year, there were no industries in which women earned more than men.

Women and Men in Spain: Gender salary gap (not adjusted to individual characteristics) by hourly salary by sectors of economic activity and period in the EU. Annual. National.

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 gender wage gap indicator compares the median earnings between male and female workers in Champaign County.

Two worker populations are analyzed: all workers, including part-time and seasonal workers and those that were not employed for the full survey year; and full-time, year-round workers. The gender wage gap is included because it blends economics and equity, and illustrates that a major economic talking point on the national level is just as relevant at the local scale.

For all four populations (male full-time, year-round workers; female full-time, year-round workers; all male workers; and all female workers), the estimated median earnings were higher in 2023 than in 2005. The greatest increase in a population’s estimated median earnings between 2005 and 2023 was for female full-time, year-round workers; the smallest increase between 2005 and 2023 was for all female workers. In both categories (all and full-time, year-round), the estimated median annual earnings for male workers was consistently higher than for female workers.

The gender gap between the two estimates in 2023 was larger for full-time, year-round workers than all workers. For full-time, year-round workers, the difference was $11,863; for all workers, it was approaching $9,700.

The Associated Press wrote this article in October 2024 about how Census Bureau data shows that in 2023 in the United States, the gender wage gap between men and women working full-time widened year-over-year for the first time in 20 years.

Income data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Median Earnings in the Past 12 Months (in 2020 Inflation-Adjusted Dollars) by Sex by Work Experience in the Past 12 Months for the Population 16 Years and Over with Earnings in the Past 12 Months.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (16 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (20 October 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (21 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).

Average hourly and median hourly gender wage ratio by National Occupational Classification (NOC), type of work, sex, and age group, last 5 years.

In 2024, Italian women earned annually about ***** euros less than men. However, the gender pay gap decreased in the last years. In 2016, it amounted to **** percent in favor of men, whereas the difference in 2022 was equal to **** percent. For 2024, it reduced to *** percent. According to JobPricing, women's annual gross salary amounted to around ****** euros in 2024. On the other hand, men had an average annual salary of approximately ****** euros. Regional differences In Italy, significant wage differences can also be observed among regions. As of 2024, regions in northern Italy registered higher average annual salaries compared to the southern regions. Lombardy had the highest average wages in the country, ****** euros per year. On the other hand, people living in Basilicata, in the south, had the lowest wages in the country, ****** euros annually. Differences in the sectors Different sectors registered various levels of pay gaps. For instance, in the banking and financial services, the difference in between the salaries of men and women favored men by ***** euros in 2020. Nonetheless, in very few sectors, the gap favors women. In the construction industry, women earned, on average, around ***** euros more than men. In the field of metallurgy and steel, women and men were equally paid.

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 Young America township. 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 Young America township, the median income for all workers aged 15 years and older, regardless of work hours, was $61,786 for males and $44,559 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 Young America township. 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 thetownship of Young America township.

- Full-time workers, aged 15 years and older: In Young America township, among full-time, year-round workers aged 15 years and older, males earned a median income of $80,417, while females earned $61,750, leading to a 23% gender pay gap among full-time workers. This illustrates that women earn 77 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 Young America township, 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 Young America township median household income by race. You can refer the same here

Results of statistical modelling exploring linear regression and Blinder-Oaxaca decomposition.

Data tables from the Gender pay gap in Jersey report published by Statistics Jersey

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 Washington. 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 Washington, the median income for all workers aged 15 years and older, regardless of work hours, was $64,325 for males and $37,453 for females.

These income figures highlight a substantial gender-based income gap in Washington. Women, regardless of work hours, earn 58 cents for each dollar earned by men. This significant gender pay gap, approximately 42%, underscores concerning gender-based income inequality in the city of Washington.

- Full-time workers, aged 15 years and older: In Washington, among full-time, year-round workers aged 15 years and older, males earned a median income of $84,217, while females earned $50,290, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 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 Washington, 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 Washington median household income by race. You can refer the same here