In 2025, the difference between average hourly earnings for men and women in the United Kingdom for all workers was 12.8 percent, compared with 6.9 percent for full-time workers, and -2.9 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.

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.

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Context

The gender pay gap or gender wage gap is the average difference between the remuneration for men and women who are working. Women are generally considered to be paid less than men. There are two distinct numbers regarding the pay gap: non-adjusted versus adjusted pay gap. The latter typically takes into account differences in hours worked, occupations were chosen, education, and job experience. In the United States, for example, the non-adjusted average female's annual salary is 79% of the average male salary, compared to 95% for the adjusted average salary.

The reasons link to legal, social, and economic factors, and extend beyond "equal pay for equal work".

The gender pay gap can be a problem from a public policy perspective because it reduces economic output and means that women are more likely to be dependent upon welfare payments, especially in old age.

This dataset aims to replicate the data used in the famous paper "The Gender Wage Gap: Extent, Trends, and Explanations", which provides new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably during the 1980–2010 period.

Citation

fedesoriano. (January 2022). Gender Pay Gap Dataset. Retrieved [Date Retrieved] from https://www.kaggle.com/fedesoriano/gender-pay-gap-dataset.

Content

There are 2 files in this dataset: a) the Panel Study of Income Dynamics (PSID) microdata over the 1980-2010 period, and b) the Current Population Survey (CPS) to provide some additional US national data on the gender pay gap.

PSID variables:

NOTES: THE VARIABLES WITH fz ADDED TO THEIR NAME REFER TO EXPERIENCE WHERE WE HAVE FILLED IN SOME ZEROS IN THE MISSING PSID YEARS WITH DATA FROM THE RESPONDENTS’ ANSWERS TO QUESTIONS ABOUT JOBS WORKED ON DURING THESE MISSING YEARS. THE fz variables WERE USED IN THE REGRESSION ANALYSES THE VARIABLES WITH A predict PREFIX REFER TO THE COMPUTATION OF ACTUAL EXPERIENCE ACCUMULATED DURING THE YEARS IN WHICH THE PSID DID NOT SURVEY THE RESPONDENTS. THERE ARE MORE PREDICTED EXPERIENCE LEVELS THAT ARE NEEDED TO IMPUTE EXPERIENCE IN THE MISSING YEARS IN SOME CASES. NOTE THAT THE VARIABLES yrsexpf, yrsexpfsz, etc., INCLUDE THESE COMPUTATIONS, SO THAT IF YOU WANT TO USE FULL TIME OR PART TIME EXPERIENCE, YOU DON’T NEED TO ADD THESE PREDICT VARIABLES IN. THEY ARE INCLUDED IN THE DATA SET TO ILLUSTRATE THE RESULTS OF THE COMPUTATION PROCESS. THE VARIABLES WITH AN orig PREFIX ARE THE ORIGINAL PSID VARIABLES. THESE HAVE BEEN PROCESSED AND IN SOME CASES RENAMED FOR CONVENIENCE. THE hd SUFFIX MEANS THAT THE VARIABLE REFERS TO THE HEAD OF THE FAMILY, AND THE wf SUFFIX MEANS THAT IT REFERS TO THE WIFE OR FEMALE COHABITOR IF THERE IS ONE. AS SHOWN IN THE ACCOMPANYING REGRESSION PROGRAM, THESE orig VARIABLES AREN’T USED DIRECTLY IN THE REGRESSIONS. THERE ARE MORE OF THE ORIGINAL PSID VARIABLES, WHICH WERE USED TO CONSTRUCT THE VARIABLES USED IN THE REGRESSIONS. HD MEANS HEAD AND WF MEANS WIFE OR FEMALE COHABITOR.

1. intnum68: 1968 INTERVIEW NUMBER
2. pernum68: PERSON NUMBER 68
3. wave: Current Wave of the PSID
4. sex: gender SEX OF INDIVIDUAL (1=male, 2=female)
5. intnum: Wave-specific Interview Number
6. farminc: Farm Income
7. region: regLab Region of Current Interview
8. famwgt: this is the PSID’s family weight, which is used in all analyses
9. relhead: ER34103L this is the relation to the head of household (10=head; 20=legally married wife; 22=cohabiting partner)
10. age: Age
11. employed: ER34116L Whether or not employed or on temp leave (everyone gets a 1 for this variable, since our wage analyses use only the currently employed)
12. sch: schLbl Highest Year of Schooling
13. annhrs: Annual Hours Worked
14. annlabinc: Annual Labor Income
15. occ: 3 Digit Occupation 2000 codes
16. ind: 3 Digit Industry 2000 codes
17. white: White, nonhispanic dummy variable
18. black: Black, nonhispanic dummy variable
19. hisp: Hispanic dummy variable
20. othrace: Other Race dummy variable
21. degree: degreeLbl Agent's Degree Status (0=no college degree; 1=bachelor’s without advanced degree; 2=advanced degree)
22. degupd: degreeLbl Agent's Degree Status (Updated with 2009 values)
23. schupd: schLbl Schooling (updated years of schooling)
24. annwks: Annual Weeks Worked
25. unjob: unJobLbl Union Coverage dummy variable
26. usualhrwk: Usual Hrs Worked Per Week
27. labincbus: Labor Income from...

In 2024, the gender pay gap for all workers in the United Kingdom was highest in the financial and insurance sector, at **** percent, and lowest in accommodation and food services, where it was *** percent.

This statistic shows the median pay gap between women and men of selected retailers in the United Kingdom (UK) as of the 2024/25 financial year. Of the companies included, Kingfisher plc had the highest median gender pay gap, at **** percent.

Context

In the United Kingdom, it's mandated by law that any organization employing over 250 individuals must disclose their gender pay gap data annually. This is not to be mistaken with equal pay, which is the legal obligation to pay men and women the same for equivalent work. The gender pay gap, on the other hand, is a broader measure that looks at the average differences in pay, seniority, and career advancement between male and female employees. This makes it a more potent indicator of gender equality and institutional bias within organizations.

Content

Geography: United Kingdom

Time period: 2018-2023

Unit of analysis: UK Gender Pay Gap

Dataset: This dataset currently contains data collected by the Gender Pay Gap Service for the 2018 to 2023 reporting years. More data will be added as it becomes available.

At present, the Gender Pay Gap Service only provides data downloads in CSV format, divided by the reporting year. This dataset amalgamates all the available CSV files, with column descriptions and file introductions informed by my firsthand experience working on the Gender Pay Gap Service website for the Government Equalities Office.

Variables

In 2024, the highest median gender pay gap among the leading banks in the United Kingdom (UK) was reported by HSBC. Here, the median gender pay gap stood at **** percent. HSBC was followed by Lloyds and Barclays. Among the observed banks, Santander UK reported the lowest median gender pay gaps, at **** percent.

According to data published in April 2022, Mirror Group Newspapers was the media company with the biggest median hourly gender pay gap in the United Kingdom that year. Male employees earned **** percent more per hour on average than their female colleagues, resulting in an increase of *** percent compared to 2017. In fact, the development of the median hourly gender pay gap in the media industry in the United Kingdom varies strongly from company to company, but Mirror Group, Bloomberg, Conde Nast, and The Economist stood out as having the least parity in this regard.

Median earnings of residents - Gross Weekly Pay (£) - Gender Pay Gap

This dataset contains gender pay gap figures for all employees in London and large employers in London. The pay gap figures for GLA group organisations can be found on their respective websites. The gender pay gap is the difference in the average hourly wage of all men and women across a workforce. If women do more of the less well paid jobs within an organisation than men, the gender pay gap is usually bigger. The UK government publish gender pay gap figures for all employers with 250 or more employees. A cut of this dataset that only shows employers that are registered in London can be found below. Read a report by the Local Government Association (LGA) that summarises the mean and median pay gaps in local authorities, as well as the distribution of staff across pay quartiles. This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more. This dataset is one of the Greater London Authority's measures of Economic Development strategy. Click here to find out more.

This is the pay gap for a local authority or fire authority as reported annually to the Gender pay gap service. A late submission by an authority may not be included. Employers with 250 or more employees must publish figures comparing men and women's average pay across the organisation. This metric shows the difference between the mean hourly rates for male staff and female staff expressed as a percentage of the male rate. A positive figure indicates that females are paid less than males on average; a negative figure indicates that females are paid more than males on average. For example; in the period 2023/2024 when comparing mean (average) hourly pay, women’s mean hourly pay is 2.8% lower than men’s.https://gender-pay-gap.service.gov.uk/ Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Context

In the UK, it is a legal requirement for organisations with more than 250 employees to report their annual gender pay gap figures. The gender pay gap is often confused with equal pay - men and women being paid the same amount for the same work - which is also a legal requirement. Instead, the gender pay gap examines the difference in average salaries, seniority and progression between male and female staff, which makes it a far more powerful metric and predictor of gender equality and systemic bias in organisations.

Content

This dataset currently contains data collected by the Gender Pay Gap Service for the 2017/18 to 2020/21 reporting years. More data will be added as it becomes available. Data is collected via employers self-reporting gender pay gap figures through the Gender Pay Gap Service website. The site also allows users to find data on employer gender pay gaps, or compare between multiple employers.

Currently, the data downloads offered by the Gender Pay Gap Service are limited to CSV downloads, split by reporting year. This dataset is a combination of all currently available CSV files, with column descriptors and file introductions based on my personal experience working for the Government Equalities Office on the Gender Pay Gap Service website.

Acknowledgements

All data has been taken from the GOV.UK Gender Pay Gap Service's downloads, available here: https://gender-pay-gap.service.gov.uk/viewing/download

In 2024, there were roughly 591,000 full-time male employees in the financial and insurance activities sector in the United Kingdom (UK). The number of full-time female employees, on the other hand, was much lower, at 424,000. In terms of part-time employment, there were significantly more female employees in the sector than males. In 2024, a total of 122,000 people worked part-time, and only 16,000 were male.

The difference in average earnings between male and female employees at DCMS.