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.
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).
In 2021, overall, women in the technology industry were offered **** percent less than men for developer operations roles at the same company. Product management roles, on the other hand, showed the smallest wage gap in all selected countries, totaling an overall wage gap of only *** percent.
Around **** of the people in the world believe that concerns about the gender pay gap are a response to a real problem. This was stated by ** percent of the female respondents and ** percent of the male respondents in a 2021 survey. At the same time, however, ** percent of the male respondents saw these concerns as an example of political correctness going too far, which was around ** percent more than the female respondents. Overall, ** percent believe that closing the gender pay gap is important and should be one of the world's top priorities right now.
Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap each year. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings. You can also:
https://gender-pay-gap.service.gov.uk/Viewing/search-results?_ga=2.149907636.32241439.1643217071-473200138.1643217071" class="govuk-link">explore this data on a dashboard
https://data.gov.uk/dataset/gender-pay-gap" class="govuk-link">export all national gender pay gap data
We have published two reports:
HMRC and VOA combined gender pay gap report
VOA standalone gender pay gap report, which includes a greater examination of VOA gender pay gaps by grade and London/National pay
These reports analyse HMRC’s and the VOA’s gender pay gap for grades covered by the delegated pay arrangements, as of 31 March 2020.
Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to report annually on their gender pay gap.
The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
You can also:
In 2021, female elementary and middle school teachers earned on average 1,138 U.S. dollars per week, while their male counterparts earned 1,301 U.S. dollars. Male office supervisors made an average of 1,184 U.S. dollars per week, while female supervisors earned an average of 913 U.S. dollars.
Gender pay gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
You can also:
Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap data annually. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
https://gender-pay-gap.service.gov.uk/?_ga=2.231531103.1744024301.1647854519-445605660.1635168409" class="govuk-link">The Gender Pay Gap Service allows you to browse and compare data from different organisations.
This report summarises the gender pay gap for the NDA group as a whole, and within the individual organisations that make up the group:
This report deals with figures from 2021 to 2022, although RWM and LLWR came together to form Nuclear Waste Services in January 2022, the two organisations remain legal entities and for the purpose of this report are detailed as separate organisations.
In 2017, the Government introduced world-leading legislation that made it statutory for organisations with 250 or more employees to report annually on their gender pay gap. Government departments are covered by the Equality Act 2010 (Specific Duties and Public Authorities) Regulations 2017 which came into force on 31 March 2017.
These regulations underpin the Public-Sector Equality Duty and require the relevant organisations to publish their gender pay gap data annually by 30 March, including mean and median gender pay gaps; the mean and median gender bonus gaps; the proportion of men and women who received bonuses; and the proportions of male and female employees in each pay quartile.
The gender pay gap shows the difference in the average pay between all men and women in a workforce. If a workforce has a particularly high gender pay gap, this can indicate there may be a number of issues to deal with, and the individual calculations may help to identify what those issues are.
The gender pay gap is different to equal pay. Equal pay deals with the pay differences between men and women who carry out the same jobs, similar jobs or work of equal value. It is unlawful to pay people unequally because they are a man or a woman.
The Ministry of Defence supports the fair treatment and reward of all staff irrespective of gender. The Department is committed to developing a more inclusive culture within Defence and a diverse workforce at all levels.
Employers with 250 or more employees are required to report annually on their gender pay gap. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
RSH has less than 250 employees and it has only been in existence since 2018, so is voluntarily publishing the figures as part of its continued commitment to improve transparency and equality.
This report also sets out the actions being taken to close the gender pay gap in the organisation.
For other reports see our Equality information and pay gap reports collections page.
Introduction: The educational attainment of women and their value generation through education has led to the prospect of achieving economic equality between men and women. However, women continue to receive lower wages compared to men, reflecting the growing inequality in various countries.
Objective: To estimate the impact of education on the gender wage gap in Peru during the period 2017-2021.
aterials and Methods: A quantitative approach is considered, with an explanatory type of research aimed at identifying the impact of education on the gender wage gap in Peru during the period 2017-2021. The research design is non-experimental and uses a time series that analyzes the influence of the latent variable of education on the gender wage gap. This is a continuous variable for estimating the Tobit model.
Results: The results show that the gender gap in Peru exhibited a decreasing trend between men and women during the period 2017-2020, with an average reduction of 10% until 2020 due to the health crisis. The highest average salary was achieved by men in 2019, reaching S/. 2289.97 soles, while women reached an average salary of S/. 1368.85 soles. In the post-pandemic scenario for 2021, the gender gap increased by 3%, with men earning an average salary of S/. 1999.63 soles and women earning an average salary of S/. 1281.16 soles. The analysis from 2017-2021 shows that years of education had a positive impact on the gender wage gap in Peru based on the Tobit model estimation.
Conclusions: During the analysis period of 2017-2021, years of education had a positive impact on the gender wage gap in Peru, with the greatest impact occurring during the health crisis. The probability of women's incomes improving with an increase in years of education was 2.35%, while for men, the highest impact was in 2018, with a probability of income improvement of 2.16% in terms of marginal effect.
Keywords: wage gap, income, education, educational policy, Tobit model
Sexual orientation had little impact on the wage gap. When applying for the same job title at the same company in the technology industry in 2021, LGBTQIA+ job candidates across all regions were offered 0.4 percent less salary than others.
Gender pay gap legislation introduced in April 2017 requires all employers of 250 or more employees to report annually on their gender pay gap.
The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
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.
Gender pay gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap annually. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
The Equality Act 2010 (Specific Duties and Public Authorities) Regulations 2017 requires employers with 250 or more workers to publish specific data in relation their workforce.From 2017, The Equality Act 2010 (Specific Duties and Public Authorities) Regulations 2017 requires all employers with more than 250 employees to to report annually on their gender pay gap. The data in this report was collected on 31 March 2021. The regulations require organisations to publish their gender pay gap data annually. You are free to re-use this information data under the terms of the Open Government Licence.Information relating to our Gender Pay Gap is also published on the data.gov website
Gender pay gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap as of 31 March 2017.
The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.
You can also:
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 Poland town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2021
Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Poland town, the median income for all workers aged 15 years and older, regardless of work hours, was $48,472 for males and $31,847 for females.
These income figures highlight a substantial gender-based income gap in Poland town. Women, regardless of work hours, earn 66 cents for each dollar earned by men. This significant gender pay gap, approximately 34%, underscores concerning gender-based income inequality in the town of Poland town.
- Full-time workers, aged 15 years and older: In Poland town, among full-time, year-round workers aged 15 years and older, males earned a median income of $65,008, while females earned $49,159, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.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 Poland town.
https://i.neilsberg.com/ch/poland-me-income-by-gender.jpeg" alt="Poland, Maine gender based income disparity">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.
Gender classifications include:
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 Poland town median household income by gender. You can refer the same here
In recent years, there has been a consistent decrease in the wage gap between all racial groups and salaries offered to white candidates. In 2021, Asian candidates surpassed and are now offered higher average salaries by 0.4 percent versus white candidates. However, black candidates continue to have the widest wage gap in salary data, with wages 1.8 percent lower than the baseline in 2021.
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.