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.

In 2024, the gender pay gap in the United Kingdom for people in their 50s was 12.1 percent, compared with -0.5 percent for people aged 18 to 21.

In 2023, the gender pay gap in South Korea was highest for employees in their fifties, amounting to a difference of an average of **** million South Korean won. The gap was smallest among youths, but still present and widened among all age groups compared to 2022.

Gender pay gap in unadjusted form by age - NACE Rev. 2 activity (B-S except O), structure of earnings survey methodology

In 2022, Polish women between the ages of 35 and 44 earned 13.1 percent less than men.

Women and Men in Spain: Gender salary gap (not adjusted to individual characteristics) by hourly salary by age and period Spain. Annual. National.

In 2024, the difference between average hourly earnings for men and women in the United Kingdom for all workers was 13.1 percent, compared with seven percent for full-time workers, and -3 percent for part-time workers. During the provided time period, the gender pay gap was at its highest in 1997, when it was 27.5 percent for all workers. Compared with 1997, the gender pay gap has fallen by 13.2 percent for all workers, and 9.7 percent for full-time workers. Gender pay gap higher in older age groups Although the gender pay gap among younger age groups was relatively small in 2024, the double-digit pay gap evident in older age groups served to keep the overall gap high. The gender pay gap for workers aged between 18 and 21 for example was -0.5 percent, compared with 12.1percent for people in their 50s. Additionally, the gender pay gap for people aged over 60 has changed little since 1997, falling by just 1.2 percent between 1997 and 2023, compared with a 14.9 percent reduction among workers in their 40s. Positions of power As of 2024, women are unfortunately still relatively underrepresented in leadership positions at Britain’s top businesses. Among FTSE 100 companies, for example, just 9.4 percent of CEOs were female, falling to just 6.1 percent for FTSE 250 companies. Representation was better when it came to FTSE 100 boardrooms, with 44.7 percent of positions at this level being filled by women, compared with 42.6 percent at FTSE 250 companies. In the corridors of political power, the proportion of female MPs was estimated to have reached its highest ever level after the 2024 election at 41 percent, compared with just three percent in 1979.

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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.

This database automatically includes metadata, the source of which is the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL USE OF THE REPUBLIC OF SLOVENIA and corresponding to the source database entitled “Gender pay gap by cohesion and statistical regions of residence and age groups, Slovenia, annually”.

Actual data are available in Px-Axis format (.px). With additional links, you can access the source portal page for viewing and selecting data, as well as the PX-Win program, which can be downloaded free of charge. Both allow you to select data for display, change the format of the printout, and store it in different formats, as well as view and print tables of unlimited size, as well as some basic statistical analyses and graphics.

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

In 2021, female workers in the age group of 25-34 years recorded a 1.3 percentage difference in their hourly salaries in Spain. By contrast, the pay gap among workers aged 65 or more stood at 27 percent.

De gender loonkloof geeft het verschil weer tussen het gemiddelde bruto uurloon van vrouwen en mannen, uitgedrukt als een percentage van het gemiddelde mannenloon. In een formule geeft dit de volgende uitdrukking: Gender loonkloof = (uurloon mannen – uurloon vrouwen) / uurloon mannen De gender loonkloof wordt berekend op basis van de Loonenquête. De statistische populatie bestaat uit alle loontrekkenden die werkzaam zijn in ondernemingen: die minstens 10 werknemers tellen; waarvan de voornaamste economische activiteit ressorteert onder de NACE Rev.2 secties B-S (-O). Er gelden geen beperkingen naar leeftijd of arbeidsduur. De gender loonkloof omvat dus zowel voltijdse- als deeltijdse tewerkgestelde loontrekkenden. Het gehanteerde loonconcept omvat betaalde overuren evenals deze premies die iedere betalingsperiode worden uitbetaald. Premies voor nacht- of weekendwerk zijn hier voorbeelden van. Premies die slechts op uitzonderlijke basis worden uitgekeerd, zoals een dertiende maand of het dubbel vakantiegeld, worden uitgesloten. Alle lidstaten van de EU hanteren dezelfde geharmoniseerde concepten en methoden bij de berekening van de gender loonkloof. Hierdoor kunnen we de Belgische situatie vergelijken met de loonkloof in de overige EU-lidstaten. De gender loonkloof wordt eenmaal om de vier jaar berekend op basis van de Loonenquête. Dit is het geval voor de referentiejaren 2010, 2014, 2018 en 2022. In de tussenliggende jaren schat Statbel op basis van RSZ-gegevens de loonkloof. Hiervoor worden de cijfers van de recentste Loonenquête geactualiseerd op basis van een evolutie die afgeleid wordt uit de RSZ-datasets. De cijfers van 2023 werden op deze manier geschat. Tenslotte worden de nationale schattingen eenmaal om de vier jaar, namelijk na de publicatie van een nieuwe Loonenquête, door Eurostat herzien. De cijfers voor de jaren 2007-2009, 2011-2013, 2015-2017 en 2019-2021 werden bijgevolg door Eurostat berekend.

In Canada, women earned an average of 0.73 Canadian dollars for every dollar earned by men in 2021, just under three quarters of the average annual employment income for men. The people among whom this ratio was least unequal were Canadians aged between 16 and 24 (0.82), and those over 65 (0.79). In contrast, women aged 35-44 and those aged 55-64 earned on average two-thirds of what men of the same age earned.

Encouraging women to pursue STEM employment is frequently touted as a means of reducing the gender wage gap. We examine whether the attributes of computer science workers–who account for nearly half of those working in STEM jobs–explain the persistent gender wage gap in computer science, using American Community Survey (ACS) data from 2009 to 2019. Our analysis focuses on working-age respondents between the ages of 22 and 60 who had a college degree and were employed full-time. We use ordinary least squares (OLS) regression of logged wages on observed characteristics, before turning to regression decomposition techniques to estimate what proportion of the gender wage gap would remain if men and women were equally rewarded for the same attributes–such as parenthood or marital status, degree field, or occupation. Women employed in computer science jobs earned about 86.6 cents for every dollar that men earned–a raw gender gap that is smaller than it is for the overall labor force (where it was 82 percent). Controlling for compositional effects (family attributes, degree field and occupation) narrows the gender wage gap, though women continue to earn 9.1 cents per dollar less than their male counterparts. But differential returns to family characteristics and human capital measures account for almost two-thirds of the gender wage gap in computer science jobs. Women working in computer science receive both a marriage and parenthood premium relative to unmarried or childless women, but these are significantly smaller than the bonus that married men and fathers receive over their childless and unmarried peers. Men also receive sizable wage premiums for having STEM degrees in computer science and engineering when they work in computer science jobs, advantages that do not accrue to women. Closing the gender wage gap in computer science requires treating women more like men, not just increasing their representation.

In 2023, in France, younger people who worked in the private sector experienced a smaller gender pay gap than their elders. Indeed, for those aged 25 years old and younger, the salary gap between men and women was around *** percent. In comparison, women workers in their 40s earned approximately **** percent less than male workers. The largest gender pay gap was experienced by people in their 60s and older, with a salary difference of around **** percent.

The gender overall earnings gap is a synthetic indicator. It measures the impact of the three combined factors, namely: (1) the average hourly earnings, (2) the monthly average of the number of hours paid (before any adjustment for part-time work) and (3) the employment rate, on the average earnings of all women of working age - whether employed or not employed - compared to men.

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 Reading. 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 Reading, the median income for all workers aged 15 years and older, regardless of work hours, was $30,763 for males and $22,146 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 Reading. 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 thecity of Reading.

- Full-time workers, aged 15 years and older: In Reading, among full-time, year-round workers aged 15 years and older, males earned a median income of $45,759, while females earned $38,704, resulting in a 15% gender pay gap among full-time workers. This illustrates that women earn 85 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 Reading.

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 Reading.

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

The gender overall earnings gap is a synthetic indicator. It measures the impact of the three combined factors, namely: (1) the average hourly earnings, (2) the monthly average of the number of hours paid (before any adjustment for part-time work) and (3) the employment rate, on the average earnings of all women of working age - whether employed or not employed - compared to men.

As of 2023, South Korea is the country with the highest gender pay gap among OECD countries, with a **** percent difference between the genders. The gender pay gap displays the difference between the median wages of full-time employed men and full-time employed women.