Since 1990, the employment rate of women in the United States has stayed more or less steady, reaching a peak of 57.5 percent in 2000. In 1990, the female employment rate was 54.3 percent, and in 2023, the employment rate was 55.4. Women in the workforce
There have historically been less women then men in the workforce. Additionally, women face many hurdles to equal treatment when they are employed, such as wage discrepancies, sexual harassment, and being expected to carryout the majority of household and family related tasks even while working full-time.
Women have historically been the primary caregivers and homemakers through many cultures worldwide. Despite this, the number of women joining the workforce has increased globally. Women in history faced the additional barrier of not being able to attend university, which barred them from gaining an education and access to professional job. However, as our cultures have modernized, women have been granted equal access to university in many societies. In 2014 in the United States, the number of university degrees awarded to women exceeded that of men for the first time. In 2021, 39.1 percent of women had completed at least four years of university compared to 36.6 percent of men. Despite this, the unemployment rate of women in the United States has fluctuated significantly since 1990. In 2021, Nebraska was the state with the highest percentage of women participating in the civilian labor force, second to the District of Columbia.
The wage gap
Today, the wage gap is still a problem for women, although improvements have been made. There is no state in the U.S. where women earn more than men, but women in Vermont had the smallest wage gap to men in 2021. Additionally, there are no occupations in which women out-earn men, even in occupations that traditionally employ more women. A more detailed look at wage inequality in the United States can be found here.
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Graph and download economic data for Labor Force Participation Rate - Women (LNS11300002) from Jan 1948 to Feb 2025 about females, participation, 16 years +, labor force, labor, household survey, rate, and USA.
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The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within New York. The dataset can be utilized to gain insights into gender-based income distribution within the New York population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for New York median household income by race. You can refer the same here
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Graph and download economic data for Infra-Annual Labor Statistics: Labor Force Participation Rate Female: From 25 to 54 Years for United States (LRAC25FEUSM156S) from Jan 1955 to Feb 2025 about 25 to 54 years, females, participation, labor force, labor, rate, and USA.
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The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Odessa. The dataset can be utilized to gain insights into gender-based income distribution within the Odessa population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Odessa median household income by race. You can refer the same here
In 2023, the share of female employees in the total workforce of most leading U.S. banks exceeded 50 percent. Among the observed banks, Truist and PNC Financial Services had the highest share of female employees in terms of the total workforce, at 62.7 and 59 percent, respectively. The lowest share of female employees was seen at Capital One and Goldman Sachs, where the share of women was less than 50 percent.Gender diversity: total workforce vs. senior management The relatively high share of female employees in the total workforce of leading U.S. banks may show gender diversity in a good light, but the devil is in the details. The share of female executives and senior level officials and managers in the largest U.S. banks was significantly lower in 2023. The relatively low share of female executives and senior managers in banks is not unique. In numerous other industries, the share of women employed on executive and senior levels tends to be lower than the share of women in the total workforce. Global gender gap index There has been a gradually increasing focus on gender equality in recent years. The global gender gap index was first introduced by the World Economic Forum in 2006 to measure the gender-based gaps among four key dimensions (economic participation and opportunity, educational attainment, health and survival, and political empowerment), and to track the progress of closing these gaps. Based on the four dimensions, the index scores each country between zero and one. In 2023, Europe held seven spots in the top ten, while the United States ranked 43rd.
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The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Whitehall. The dataset can be utilized to gain insights into gender-based income distribution within the Whitehall population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Whitehall median household income by race. You can refer the same here
The statistic shows the distribution of the workforce across economic sectors in the United States from 2013 to 2023. In 2023, 1.57 percent of the workforce in the US was employed in agriculture, 19.34 percent in industry and 79.09 percent in services. See U.S. GDP per capita for more information. American workforce A significant majority of the American labor force is employed in the services sector, while the other sectors, industry and agriculture, account for less than 20 percent of the US economy. However, the United States is among the top exporters of agricultural goods – the total value of US agricultural exports has more than doubled since 2000. A severe plunge in the employment rate in the US since 1990 shows that the American economy is still in turmoil after the economic crisis of 2008. Unemployment is still significantly higher than it was before the crisis, and most of those unemployed and looking for a job are younger than 25; youth unemployment is a severe problem for the United States, many college or university graduates struggle to find a job right away. Still, the number of employees in the US since 1990 has been increasing slowly, with a slight setback during and after the recession. Both the number of full-time and of part-time workers have increased during the same period. When looking at the distribution of jobs among men and women, both project the general downward trend. A comparison of the employment rate of men in the US since 1990 and the employment rate of women since 1990 shows that more men tend to be employed than women.
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Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Tyler. The dataset can be utilized to gain insights into gender-based income distribution within the Tyler population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Tyler median household income by race. You can refer the same here
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Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Wyoming. The dataset can be utilized to gain insights into gender-based income distribution within the Wyoming population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Wyoming median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Cambridge. The dataset can be utilized to gain insights into gender-based income distribution within the Cambridge population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Cambridge median household income by race. You can refer the same here
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License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Virginia. The dataset can be utilized to gain insights into gender-based income distribution within the Virginia population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Virginia median household income by race. You can refer the same here
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License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within South Carolina. The dataset can be utilized to gain insights into gender-based income distribution within the South Carolina population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Carolina median household income by race. You can refer the same here
As of 2019, most employees in selected tech companies were male. Biotech company 23andMe was ranked first with 51 percent female employees, the only company on the list to feature a majority female workforce. Airbnb was ranked second with 48.94 percent female employees. Hardware-focused companies Intel, Cisco, and Nvidia closed the ranking with less than 30 percent female workforce each.
One female to every two males in U.S. tech industry
The majority of employees in the U.S. tech industry are male. Round about a third of all employees in tech occupations in the United States are women – Washington D.C., or the District of Columbia, was the state with the greatest tech gender balance in the U.S., with close to 40 percent of tech employees there being female in 2019. In general, females also earn less than their male counterparts: males in the U.S. earn around 20,000 U.S. dollars on average more than females.
Types of tech employment
The IT sector employment includes professionals from various sub-fields, such as, technology manufacturing, telecommunications and internet services, software publishing, etc. The worldwide full-time employment in the ICT sector is forecast to grow by around ten million in the next four years. Full-time employees represent close to 70 percent of all IT workers worldwide. Other types of employment include outsourced, contractor, or part-time workers.
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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 $69,375Surprisingly, 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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for China median household income by race. You can refer the same here
Alaska had the highest male to female ratio in the United States in 2020, with 109.2 men for every 100 women. The male to female ration was lowest in the District of Columbia, with 90.3 men for every 100 women.
The final frontier
Alaska, which was purchased from the Russian Empire in 1867, is the largest state in the U.S. and one of the newest states, having been admitted to the U.S. in 1959. Although oil production dominates the economy, Alaska has a very high poverty rate and consistently has the highest unemployment rate in the country.
It’s a man’s world
Alaska is one of 10 states in the U.S. that has more men than women. The male to female ratio in the United States as a whole is about even, but as the population ages, there tend to be more females than males. Even though the sex ratio in the U.S. is almost one to one, a little more than 56 percent all females participated in the labor force in 2021, compared with 67.6 percent of men.
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The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Charleston. The dataset can be utilized to gain insights into gender-based income distribution within the Charleston population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Charleston median household income by race. You can refer the same here
Women held 60 percent of marketing jobs in the United States between May 2020 and May 2021. Real estate and wellness & fitness were the industries with the highest female representation in marketing, with a respective 71 and 70 percent of marketing roles being held by women.
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Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Brainerd. The dataset can be utilized to gain insights into gender-based income distribution within the Brainerd population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Brainerd median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Delhi. 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 Delhi, the median income for all workers aged 15 years and older, regardless of work hours, was $36,124 for males and $20,750 for females.
These income figures highlight a substantial gender-based income gap in Delhi. 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 town of Delhi.
- Full-time workers, aged 15 years and older: In Delhi, among full-time, year-round workers aged 15 years and older, males earned a median income of $41,746, while females earned $43,875Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.05 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.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Delhi median household income by race. You can refer the same here
Since 1990, the employment rate of women in the United States has stayed more or less steady, reaching a peak of 57.5 percent in 2000. In 1990, the female employment rate was 54.3 percent, and in 2023, the employment rate was 55.4. Women in the workforce
There have historically been less women then men in the workforce. Additionally, women face many hurdles to equal treatment when they are employed, such as wage discrepancies, sexual harassment, and being expected to carryout the majority of household and family related tasks even while working full-time.
Women have historically been the primary caregivers and homemakers through many cultures worldwide. Despite this, the number of women joining the workforce has increased globally. Women in history faced the additional barrier of not being able to attend university, which barred them from gaining an education and access to professional job. However, as our cultures have modernized, women have been granted equal access to university in many societies. In 2014 in the United States, the number of university degrees awarded to women exceeded that of men for the first time. In 2021, 39.1 percent of women had completed at least four years of university compared to 36.6 percent of men. Despite this, the unemployment rate of women in the United States has fluctuated significantly since 1990. In 2021, Nebraska was the state with the highest percentage of women participating in the civilian labor force, second to the District of Columbia.
The wage gap
Today, the wage gap is still a problem for women, although improvements have been made. There is no state in the U.S. where women earn more than men, but women in Vermont had the smallest wage gap to men in 2021. Additionally, there are no occupations in which women out-earn men, even in occupations that traditionally employ more women. A more detailed look at wage inequality in the United States can be found here.