The Structure of Earnings Survey (SES) is a nationwide survey of Irish employees conducted by the Central Statistics Office (CSO). The results of the SES 2022 presented in this publication relate to mean and median hourly earnings across the economy. Tables are provided by sector of activity, firm size, length of service, occupation, education, age and other factors that go towards explaining differences in rates of hourly pay. The survey covers both public and private sectors. The only excluded sectors are Agriculture, forestry and fishing.
The purpose of the SES is to provide detailed structural information on earnings and factors influencing earnings. The SES is carried out on a four yearly basis and has been designed as an integrated survey that addresses issues of national interest while simultaneously fulfilling requirements under EU regulation (EC) No 530/1999. Data on the structure of earnings has been provided to Eurostat for the reference years 2002, 2006, 2010, 2014 and 2018. However, the methodology over this time period has lacked consistency so comparisons between SES years are not directly comparable and should be interpreted with this in mind. This is the first year the CSO is publishing the results of the survey.
The SES sample of employees was selected from the Earnings Analysis using Administrative Sources (EAADS). The EAADS dataset was stratified based on economic sector, gender and ten earnings bands from which the sample in each stratum was selected. The sample size for each stratum had to be a minimum of ten or a census of the stratum if the count was below ten. In addition, sectors where there was a high variance for earnings and/or had a previously low response rate had more employees included in the survey.
Employees selected in the sampling process were identified by the CSO through their PPS number and contacted via a letter containing instructions on how to complete the survey.
The information required was divided into that most suitable to collect from employees (e.g., hours worked, age, full-time/part-time status, educational attainment etc.) and information best sourced from administrative data sources (e.g. weekly earnings, public/private sector status etc.) such as Earnings Analysis using Administrative Data Sources (EAADS). A stratified sample of employees based on a set criteria was selected from the EAADS dataset which acts as a population census of employees or sampling frame. Sampled employees were then contacted at their place of work via letter.
Employee Survey – This was distributed electronically via a link to sampled employees who were provided with a password to access the survey. The employees were asked to supply information such as age, gender, educational attainment, nationality, length of time in paid employment, and other job-related characteristics.
| Response Rate for Structure of Earnings Survey 2022 | |
| Employee Survey: | |
| Effective Sample | 38,475 |
|---|---|
| Number of returns | 14,972 |
| Non-respondent employees | 23,503 |
| Response Rate | 38.9% |
Survey responses to the SES were weighted to the population of employees recorded by EAADS. The weights were calculated by calibrating the survey responses to the count totals and weekly gross income totals from EAADS by sector, firm size, age group, public/private status, sex, nationality group and region of residence. The weight is a product of a design weight based on the stratification of the sample on the sampling frame and a calibration-weight based on post-stratification non-response adjustment resulting from the survey responses. This approach takes into account as fully as possible the characteristics of the sample observations in terms of auxiliary variables and their known totals.
The employee total and calibration totals are those as measured by the EAADS in 2022.
This analysis is for PAYE individuals only. It does not include any analysis of self-employed earnings. There is a restriction to employments active in October only. In line with Eurostat requirements relating to Structure of Earnings Statistics (in particular Council Regulation (EC) No 530/1999) the data used for this analysis has been restricted to employments that were active in the month of October.
Up to 2018, employments active in October were identified using employment start and end dates on the P35 data. For 2022, active employments are identified by reference to pay dates in the reference month using data from Revenue's PMOD system.
The regional classifications in this publication are based on the NUTS (Nomenclature of Territorial Units) classification used by Eurostat. Previously the NUTS3 regions corresponded to the eight Regional Authorities established under the Local Government Act, 1991 (Regional Authorities) (Establishment) Order, 1993, which came into operation on 1 January 1994 while the NUTS2 regions, which were proposed by Government and agreed by Eurostat in 1999, were groupings of those historic NUTS3 regions.
However, the NUTS3 boundaries were amended on 21st of November 2016 under Regulation (EC) No. 2066/2016. These new groupings are reflected in this publication. As a result of these changes, Louth moved from the Border to the Mid-East and what was formerly South Tipperary was amalgamed with North Tipperary and moved from the South-East to the Mid-West.
| NUTS3 Areas | Counties |
| Border | Cavan Donegal Leitrim Monaghan Sligo |
|---|---|
| Midland | Laois Longford Offaly Westmeath |
| West | Galway Mayo Roscommon |
| Dublin | Dublin City Dun Laoghaire-Rathdown Fingal South Dublin |
| Mid-East | Kildare Meath Wicklow Louth |
| Mid-West | Clare Limerick Tipperary |
| South-East | Carlow Kilkenny Waterford Wexford |
| South-West | Cork Kerry |
The official Gender Pay Gap is calculated by Eurostat from Structure of Earnings data sent to them on a 4 yearly basis (SES reference years 2002, 2006, 2010, 2014, 2018 and 2022).
For non-SES years, member states are requested to submit estimates for the GPG. These estimates can be 'benchmarked' to SES when available.
Currently there is no legal requirement to provide GPG data to Eurostat for non-SES years. Data is returned under a voluntary agreement. However, by 2026 there will be a legal requirement to transmit data to Eurostat on an annual basis.
For the non-SES years, the GPG is calculated by imputing average total weekly paid hours from economic sector along with full-time/part-time status from the Earnings Hours and Employment Costs Survey (EHECS) onto the EAADS dataset. These figures are then transmitted to Eurostat. Some variances between the GPG figures sent to Eurostat and those published by the CSO can be explained by the inclusion of all firm sizes and economic sector O Public Administration in the SES/GPG figures published by the CSO. Whereas firm size 1-9 and economic sector O are excluded from the figures transmitted to Eurostat. Another part is explained by the differences in the methodologies used for SES and non-SES years as discussed above.
SES 2018 figures are not released in this publication; however, they are available via the supplementary PxStat tables. There are differences in the methodologies used between SES 2018 and SES 2022 therefore results are not directly comparable.
In 2022, only employees who were active in October are included, whereas all employees who were active over the whole year in 2018 are included in SES 2018. The reference month for 2022 is October whereas the reference month for 2018 is an average month (based on all 12 months).
The month October is the preferred reference month as it is less affected by factors such as temporary/ seasonal work, annual leave or public holidays and is seen to be most representative of a typical month.
Revenue’s Temporary Wage Subsidy Scheme enabled employees, whose employers were affected by the COVID-19 pandemic, to receive supports directly from their employer through the payroll system. The scheme operated in two phases, a transitional phase from 26 March to 3 May 2020, and an operational phase from 4 May to 31 August 2020.
The Employment Wage Subsidy Scheme was an economy-wide enterprise support for eligible businesses in respect of eligible employees. The scheme provided a flat-rate subsidy to qualifying employers based on the numbers of eligible employees on the employer’s payroll and gross pay to employees. The EWSS replaced the TWSS from 1 September 2020. EWSS ended for most employers on 30 April 2022 and for everyone on 31 May 2022.
The arithmetic mean is the most commonly used “average” or measure of central tendency. It is calculated by summing the values of an item for all observations in a category of data and then dividing the total by the number of observations in the category. There are other measures of central tendency. The tables in this report present information using the mean and the median.
The median is the “middle value” in an ordered sequence of data. Approximately 50% of the observations lie above the median and 50% below. The median is unaffected by any extreme observations. For instance, the size of an extremely large value will not affect the position of the median whereas it would affect the position of the mean. In this sense, the median is a more robust measure than the mean.
Estimates of mean hourly earnings are derived by dividing estimates of the gross weekly earnings by estimates of the total hours paid in the week at the level of the individual employee.
Hours paid include all normal and overtime hours worked and remunerated by the employer during the reference period. Hours not worked but nevertheless paid are counted as ‘paid hours’ (e.g., for annual leave, public holidays, paid sick leave, paid vocational training, paid special leave etc).
The economic sector classification (NACE) is aligned to the CSO’s EHECS Survey. The economic sector classification used for the EHECS is based on the ‘Statistical Classification of Economic Activities in the European Community (NACE Rev.2)’. The NACE code of each enterprise included in the survey was determined from the predominant activity of the enterprise, based on information provided to the CSO.
Public sector data comprises employments in the Civil Service, Defence, An Garda Síochána, Education, Regional bodies, Health and Semi State, both commercial and non-commercial.
The variable refers to the main job of a person in employment. This main job can be a full-time job or a part-time job. The distinction should be based on the respondent's own perception referring to the paid hours worked in the main job. Distinction between a full-time and part-time job should be made on the basis of the self-assessment given by the respondent.
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