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Welsh Government
Data Provider: Welsh Government National Statistics Gender pay difference in Wales by year (median hourly earnings full-time employees excluding overtime) (£)
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[Collapse]YearMethodological changes in 2004, 2006 and 2011 resulted in discontinuities in the time series; therefore care should be taken when making comparisons with other years. See statistical quality information for more details.[Filtered]
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Year 1
Gender[Filter]
[Collapse]2004 to 2005[Collapse]2006 to 2010[Collapse]2011 onwards
Click here to sort2004Data for 2004 are only directly comparable to the 2005 estimates, comparisons with other years are not strictly valid.Click here to sort2005Data for 2005 are only directly comparable to the 2004 estimates, comparisons with other years are not strictly valid.Click here to sort2006Data for 2006 are only directly comparable to the 2007-2010 estimates, comparisons with other years are not strictly valid.Click here to sort2007Data for 2007 are only directly comparable to the 2006-2010 estimates, comparisons with other years are not strictly valid.Click here to sort2008Data for 2008 are only directly comparable to the 2006-2010 estimates, comparisons with other years are not strictly valid.Click here to sort2009Data for 2009 are only directly comparable to the 2006-2010 estimates, comparisons with other years are not strictly valid.Click here to sort2010Data for 2008 are only directly comparable to the 2006-2009 estimates, comparisons with other years are not strictly valid.Click here to sort2011Data for 2011 are only directly comparable to the 2012 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2012Data for 2012 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2013Data for 2013 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2014Data for 2014 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2015Data for 2015 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2016Data for 2016 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2017Data for 2017 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2018Data for 2018 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2019Data for 2019 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2020Data for 2020 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2021Data for 2021 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2022Data for 2022 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2023Data for 2023 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.Click here to sort2024Data for 2024 are only directly comparable to the 2011 estimates onwards, comparisons with other years are not strictly valid.
Male10.0010.1610.5610.5011.2811.7411.6411.8711.9212.2412.2912.4212.9112.9013.0213.8514.1514.5015.48(p) The data item is provisional.16.62(p) The data item is provisional.17.43
Female8.518.929.249.529.7410.2610.7210.7710.8011.2311.2611.5011.8912.0812.0812.9913.4413.8714.62(p) The data item is provisional.15.80(p) The data item is provisional.17.11
Difference1.491.241.320.981.541.480.921.101.121.011.030.921.020.820.940.860.710.630.86(p) The data item is provisional.0.82(p) The data item is provisional.0.32
Percentage differenceDifference as a percentage of male earnings14.912.212.59.413.712.67.99.29.58.38.47.47.96.47.36.25.04.4(r) The data item has been revised since previously published in StatsWales. The revision may not be reflected in the rounded value.5.6(p) The data item is provisional.4.9(p) The data item is provisional.1.9

Metadata

Title

Gender pay difference (median earnings for full-time employees excluding overtime)

Last update

3 December 2024 3 December 2024

Next update

To be confirmed

Publishing organisation

Welsh Government

Source 1

Annual Survey of Hours and Earnings, Office for National Statistics

Contact email

LabourMarket.Stats@gov.wales

Designation

National Statistics

Lowest level of geographical disaggregation

UK regions

Geographical coverage

UK regions

Languages covered

English and Welsh

Data licensing

You may use and re-use this data free of charge in any format or medium, under the terms of the Open Government License - see http://www.nationalarchives.gov.uk/doc/open-government-licence

Keywords

Earnings

General description

These data show average gross hourly and weekly earnings in pounds for male and female full-time employees excluding overtime. The data relate to full-time employees on adult rates whose pay for the survey period was not affected by absence, and the difference between these figures. Area relates to the location of workplace, not the residence of the employee.
Various methods can be used to measure the earnings of women relative to men. ONS's headline estimates of the gender pay gap are for hourly earnings excluding overtime. Including overtime can distort the picture as men work relatively more overtime than women. Although median and mean hourly pay excluding overtime provide useful comparisons of men's and women's earnings, they do not reveal differences in rates of pay for comparable jobs. This is because such measures do not allow for the different employment characteristics of men and women, such as the proportion in different occupations and their length of time in jobs.

Data collection and calculation

The Annual Survey of Hours and Earnings (ASHE) is based on a 1% sample of employee jobs taken from HM Revenue and Customs PAYE records. Consequently, individuals with more than one job may appear in the sample more than once. Information on earnings and hours is obtained from employers and treated confidentially. ASHE does not cover the self-employed or employees not paid during the reference period.
The median is often presented as the headline measure for average earnings because the distribution of earnings is skewed, with more people earning lower salaries than higher salaries. In a skewed distribution a relatively small number of high values can have a disproportionate influence on the mean, pulling it away from what might be regarded as typical. The median is not affected by extreme values and consequently is considered a better indicator of typical “average” earnings.
Percentage differences for weekly earnings are calculated using the published rounded figures.

Frequency of publication

Annual

Data reference periods

1997 to 2024

Revisions information

Prior to the release of the 2018 estimates the gender pay difference statistics published here were based on gross hourly and gross weekly earnings. We now publish gender pay statistics on the basis of hourly and weekly earnings excluding overtime. Including overtime can distort the picture as men work relatively more overtime than women. The Office for National Statistics’ preferred measure for the gender pay gap is median hourly earnings, excluding overtime.

Statistical quality

The figures are taken from the Annual Survey of Hours and Earnings (ASHE), which is run by the Office for National Statistics (ONS). In 2004, the ASHE replaced the New Earnings Survey (NES) by introducing a new methodology into the calculation of earnings data. This new methodology applies weights to the results to take account of the structure of the population in terms of age, gender, occupation and area of workplace (London and the South East or elsewhere in the UK). The NES data for 1997 to 2003 were reworked to provide a back-series of earnings data using the new methodology.
There were further changes to the ASHE methodology in 2005 as a result of the introduction of a new questionnaire. 2004 data were reworked to be comparable with this new methodology, but it was not possible to do this for earlier years. Thus there are discontinuities in the data that must be taken account of when making comparisons over time.
A new automatic coding system for occupations was introduced in 2007. The main impact of this was to move a number of jobs away from the top occupational groups to other occupational groups. This tended to lower the average earnings in the top occupational groups and to lower earnings overall. Partly in response to the change to the sample design, an additional weighting stratum was introduced for those large enterprises which submit electronic returns to the survey (special arrangements). There was no reduction in the sample amongst these enterprises.
In 2007 and 2008, there was a sample reduction of around 20 per cent. The sample reduction was designed to be biggest in those industries where earnings exhibit lower levels of variation. In 2009 the original sample size was re-instated.
For the publication of the 2011 ASHE estimates, the occupational groups were reclassified. Since the occupational classification forms part of the methodology by which ASHE data are weighted to produce estimates for the UK, this release marked the start of a new time series and therefore care should be taken when making comparisons with earlier years.
As the results come from a survey, the results are sample-based estimates and therefore subject to differing degrees of sampling variability, i.e. the true value for any measure lies in a differing range about the estimated value. This range or sampling variability increases as the detail in the data increases, for example regional data are subject to higher variability than the Great Britain or United Kingdom data.

For further information on the quality and methodology of the data please see ONS’ Annual Survey of Hours and Earnings quality and methodology information report: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/methodologies/annualsurveyofhoursandearningslowpayandannualsurveyofhoursandearningspensionresultsqmi