Progress towards gender parity is proceeding at different speeds across geographic areas. As of 2025, North America and Europe had the smallest gender gap at around 75 percent, followed by Latin America and the Caribbean, which has closed 74.5 percent of its gap. At the current rate, it is estimated that gender parity will be achieved in 67 years. The Global Gender Index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2024, the leading country was Iceland with a score of 0.94.

According to a recent survey, ** percent of the male respondents believed that their respective countries have gone far enough in terms of giving women equal rights with men. This statement was only supported by ** percent of the female respondents. However, female respondents found to a greater extent than male respondents that workplaces treat men and women equally.

Achieve gender equality and empower all women and girls : The region has made progress in achieving gender equality and empowering women and girls, particularly in education and health and to a lesser extent women’s participation in formal employment and national policy making. This is attributed to growing awareness of the need to address gender inequalities; While almost all countries in the Pacific have adopted specific gender policies and strategies, the resources for integrating and implementing these priorities are limited. Budgets for national women’s offices are less than one percent of national appropriations; Gender inequality is highlighted by the high prevalence rates of violence against women (more than 60 percent in Melanesia, and more than 40 percent in Polynesia and Micronesia). Sexual and reproductive health and rights issues also remain substantial challenges to be addressed under Goal 5. Fertility rates, especially teenage fertility, remain high in some.

Find more Pacific data on PDH.stat.

Over the past decades, more and more women have entered the labor market around the world. Today, over 40 percent of the global workforce are women. However, only one third are in senior roles, and less than 30 percent work within science, technology, engineering, and mathematics (STEM). The Global Gender Index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the leading country was Iceland .

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.

The Gender Statistics Database provides a broad overview of statistics on gender as well as information on the various aspects of (in)equality between women and men. These include indicators referred to the EU Strategy for Equality between Women and Men (2010-2015) and the Beijing Declaration and Platform for Action on Equality.

Moreover, it is possible to access the Gender Equality Index Scores on the same platform. The Index is a composite indicator that measures how far (or close) the EU and its Member States were from achieving complete gender equality in the reference year.

Gender statistics on the numbers of women and men in key decision-making positions across a number of different life domains. The domains covered include: politics; public administration; judiciary; business and finance; social partners and NGOs; environment and climate change; and media.

Data on decision-making are collected for 35 European countries - the 28 EU Member States, 4 candidate countries (Montenegro, the former Yugoslav Republic of Macedonia, Serbia and Turkey) and the remaining EEA countries (Iceland, Liechtenstein and Norway).

Figures are available at international, European, national, regional and local level. Most data are updated annually, but some key data are updated more frequently. In particular, data on national and European politics are updated quarterly, and data on large companies biannually, in order to ensure that the information is always right up to date.

In 2023, Sub-Saharan Africa had the highest child mortality rate worldwide, with 69 children under the age of five deceased per 1,000 live births. The region has the highest poverty rates worldwide. Nevertheless, global child mortality rates have fallen steadily since the millennium.

The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the country offering the most gender equal conditions was Iceland, with a score of 0.93. Overall, the Nordic countries make up 3 of the 5 most gender equal countries worldwide. The Nordic countries are known for their high levels of gender equality, including high female employment rates and evenly divided parental leave. Sudan is the second-least gender equal country Pakistan is found on the other end of the scale, ranked as the least gender equal country in the world. Conditions for civilians in the North African country have worsened significantly after a civil war broke out in April 2023. Especially girls and women are suffering and have become victims of sexual violence. Moreover, nearly 9 million people are estimated to be at acute risk of famine. The Middle East and North Africa have the largest gender gap Looking at the different world regions, the Middle East and North Africa have the largest gender gap as of 2023, just ahead of South Asia. Moreover, it is estimated that it will take another 152 years before the gender gap in the Middle East and North Africa is closed. On the other hand, Europe has the lowest gender gap in the world.

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.

Investor Gender Equality Report_Listed Statistics Data

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 Wheeling. 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 Wheeling, the median income for all workers aged 15 years and older, regardless of work hours, was $34,933 for males and $25,827 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 26% between the median incomes of males and females in Wheeling. With women, regardless of work hours, earning 74 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Wheeling.

- Full-time workers, aged 15 years and older: In Wheeling, among full-time, year-round workers aged 15 years and older, males earned a median income of $55,684, while females earned $49,275, resulting in a 12% gender pay gap among full-time workers. This illustrates that women earn 88 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Wheeling.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Wheeling.

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 Wheeling 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 West Palm Beach. 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 West Palm Beach, the median income for all workers aged 15 years and older, regardless of work hours, was $43,939 for males and $31,320 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 29% between the median incomes of males and females in West Palm Beach. With women, regardless of work hours, earning 71 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of West Palm Beach.

- Full-time workers, aged 15 years and older: In West Palm Beach, among full-time, year-round workers aged 15 years and older, males earned a median income of $55,693, while females earned $51,397, resulting in a 8% gender pay gap among full-time workers. This illustrates that women earn 92 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of West Palm Beach.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in West Palm Beach.

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 West Palm Beach median household income by race. You can refer the same here

The data and programs replicate tables and figures from "Sexual Harassment and Gender Inequality in the Labor Market", by Folke and Rickne. Please see the README file for additional details.

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

The effectiveness of gender equality propaganda in the National Army

According to a survey about Chinese career women conducted in 2025, about **** percent of female respondents said they had experienced gender discrimination at work, whereas only **** percent of male respondents had similar experience. Similarly, more women than men felt that age was affecting their career prospects.

According to the Gender Inequality Index (GII), Denmark and Norway were the most gender equal countries in the world in 2023, reporting an index of ***** and *****, respectively. The Gender Inequality Index measures inequality between women and men in three dimensions: reproductive health, empowerment, and the labor market. A low GII value indicates low inequality between women and men and vice versa. Yemen was considered the least gender equal country that same year. Gender inequality in the workplace The most prominent source of gender inequality is the workplace, often captured by the gender pay gap. In 2023, women still earned one percent less than their male counterparts with the same qualification and the same job. Women are less represented in senior roles and top management positions, with only one third percent of companies worldwide having a woman in leadership positions. The same situation can be observed in government roles - only 17 out of 195 countries worldwide have ever had a woman in the highest position of executive power. Future outlook Numbers on how long it will take to close gender gaps highly differ between regions. In Europe, it is estimated that it will take around 67 years to achieve equality between the genders. In East Asia and the Pacific, on the other hand, it is projected to take 189 years. New data shows that the COVID-19 pandemic has increased female poverty worldwide and widened the gender poverty gap even further. Heightened female poverty will also negatively impact the Gender Inequality Index (GII).

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 Yamhill. 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 Yamhill, the median income for all workers aged 15 years and older, regardless of work hours, was $65,714 for males and $37,361 for females.

These income figures highlight a substantial gender-based income gap in Yamhill. Women, regardless of work hours, earn 57 cents for each dollar earned by men. This significant gender pay gap, approximately 43%, underscores concerning gender-based income inequality in the city of Yamhill.

- Full-time workers, aged 15 years and older: In Yamhill, among full-time, year-round workers aged 15 years and older, males earned a median income of $90,208, while females earned $53,611, 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 Yamhill, 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 Yamhill 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 Wilna 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 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Wilna town, the median income for all workers aged 15 years and older, regardless of work hours, was $47,256 for males and $29,624 for females.

These income figures highlight a substantial gender-based income gap in Wilna town. Women, regardless of work hours, earn 63 cents for each dollar earned by men. This significant gender pay gap, approximately 37%, underscores concerning gender-based income inequality in the town of Wilna town.

- Full-time workers, aged 15 years and older: In Wilna town, among full-time, year-round workers aged 15 years and older, males earned a median income of $59,773, while females earned $48,786, 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 Wilna town.

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 Wilna town median household income by race. You can refer the same here