Earnings refers to money earned from employment, whereas income is total money received, including from earnings, benefits and pensions, and so on. There are several different ways to calculate income:
earnings (also called gross earnings) refer to that remuneration received by employees in return for employment; most analyses of earnings consider only gross earnings, which is earnings before any benefits are added or tax deductions are made (including National Insurance contributions)
original income is obtained by combining employee earnings with those of the self-employed, along with private pensions and other sources of income such as income from investments
gross income is obtained by adding cash benefits, such as the state pension, child benefit or Jobseekers’ Allowance, to original income
disposable or net income is gross income after deductions from direct taxes (for example, Income Tax), employee National Insurance contributions and Council Tax or Northern Ireland Rates
post-tax income is obtained by further deducting indirect taxes (where the tax is typically levied on one entity but paid by another), for example, VAT and duties on alcohol or tobacco
lastly, final income is obtained by adding in benefits in kind paid by the state such as health and education which are allocated on the basis of household characteristics
In addition to income and earnings, there are other different measures of pay, for example, labour costs and take-home pay. These are:
labour costs refer to the costs experienced by the employer, rather than those received by the employee; labour costs include wages, national insurance contributions, employer pension contributions and benefits in kind paid by the employer
take-home pay refers to gross earnings minus employee deductions, for example income tax, employee national insurance contributions and pension contributions
The stages of earnings and income are summarised in Figure 1. More information on the differences between income and earnings can be found in the Guide to sources of data on earnings and income methodology article.
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The gender pay gap is the difference in median pay between men and women. The headline measure for the gender pay gap is the difference between median gross hourly earnings (excluding overtime) of men and women as a proportion of median gross hourly earnings (excluding overtime) for men. For example, in 2019, for full-time employees, the gender pay gap of 8.9% means that women earn 8.9% less, on average, than men.
Crucially, this measure does not take into account equal pay for equal work. It does not measure the difference in earnings between men and women who have the same job, at the same pay grade with the same working pattern. The gender pay gap also does not include analyses of personal characteristics that determine a person’s pay, such as age. Therefore, the gender pay gap does not necessarily mean men and women are paid differently for the same job.
The gender pay gap can be affected by a number of factors, including but not limited to, occupation (there are not equal proportions of men and women in the same occupations), working pattern (more women work part-time than men), the number of years worked in a particular job and age. The article Understanding the gender pay gap in the UK looks in more detail at the extent to which different factors affect the gender pay gap.
The headline measure is calculated using hourly earnings excluding overtime. This measure is used because including overtime can skew the results (men work relatively more overtime than women on average) and hourly earnings better account for the fact that men work more hours per week on average than women. This measure therefore gives a fairer comparison of earnings.
The Office for National Statistics’ headline measure for the gender pay gap uses Annual Survey of Hours and Earnings (ASHE) data, which is the UK’s most comprehensive survey of individual employee pay. ASHE publishes gender pay gap tables for a large number of breakdowns including by geography, occupation, industry and age. More information on ASHE can be found on the ASHE methodology page.
ASHE calculates the gender pay gap separately for full-time and part-time employees, as the net effect for all employees can mask the movements in the two different series. An explanation for the difference in the gender pay gap estimate between full-time and all employees can be found in the guide to interpreting ASHE estimates.
ONS is not responsible for and does not publish the results of gender pay gap reporting. Gender pay gap reporting is mandatory for employers with 250 or more employees and is where they must publish and report figures about the gender pay gap in their company. Guidance relating to gender pay gap reporting can be found on the GOV.UK website. If you are looking to report your company’s gender pay gap data you can also do this through their website, as well as find gender pay gap information for specific employers using their search tool.Back to table of contents
The ethnicity pay gap headline measure uses Annual Population Survey (APS) data, and is calculated as the difference between the average hourly earnings of White British and other ethnic groups as a proportion of average hourly earnings of White British employees. For example, a positive 5.0% ethnic pay gap between White British and Indian ethnic groups would denote that the median hourly earnings for employees of an Indian ethnicity are 5.0% less than median hourly earnings of White British employees. Conversely, a negative 5.0% pay gap would denote that employees of Indian ethnicity earn 5.0% more, on average, than White British employees.
This measure does not take into account equal pay for equal work. It does not measure the difference in earnings between employees of different ethnicities who have the same job, at the same pay grade, with the same working pattern. Therefore, an ethnicity pay gap does not necessarily mean employees from different ethnic groups are paid differently for the same job.
Our headline measure for the ethnicity pay gap uses Annual Population Survey data, which is a continuous household survey covering the UK. More information on the APS can be found on the APS methodology page. Although the ethnicity pay gap headline measure uses APS data, it should be noted that the primary source of data for earnings analysis in the UK is the Annual Survey of Hours and Earnings (ASHE). Because ASHE is a business survey, it collects only a limited range of personal characteristics regarding individual employees. This limits its usefulness in analysing earnings, for instance, by different protected characteristics including ethnicity.
To conduct the analysis on the ethnicity pay gap, a new income weight was calculated for the APS. The APS combines responses from the quarterly Labour Force Survey (LFS) and Annual Local Labour Force Surveys for England, Wales and Scotland. Although the APS has a much-improved sample size compared with the LFS, it still suffers from some shortcomings when compared with ASHE. For instance, as a survey of businesses, ASHE is thought to capture more accurate earnings information, as employers can consult payroll records when responding to the survey. In comparison, earnings information collected in the LFS and APS is self-reported and as such is likely to be subject to a higher degree of recall error.Back to table of contents
The disability pay gap headline measure uses Annual Population Survey (APS) data and is calculated as the difference between disabled and non-disabled average (median) hourly pay as a proportion of non-disabled average (median) hourly pay. For example, if the pay gap is 5.0%, then disabled people are on average being paid 5.0% less than their non-disabled counterparts, while a negative 5.0% pay gap would denote that a disabled person is being paid on average 5% more than their non-disabled counterparts.
This measure does not take into account equal pay for equal work. It does not measure the difference in earnings between disabled and non-disabled employees who have the same job, at the same pay grade, with the same working pattern. Therefore, a disability pay gap does not necessarily mean disabled and non-disabled employees are paid differently for the same job.
The Office for National Statistics’ (ONS’) headline measure for the disability pay gap uses data from the APS, which is a continuous household survey covering the UK. More information on the APS can be found in the APS QMI. Although the disability pay gap headline measure uses APS data, it should be noted that the primary source of data for earnings analysis in the UK is the Annual Survey of Hours and Earnings (ASHE). Since ASHE is a business survey, it collects only a limited range of personal characteristics regarding individual employees. This limits its usefulness in, for example, analysing earnings by different protected characteristics including disability.
To conduct the analysis on the disability pay gap, a new income weight was calculated for the APS. The APS combines responses from the quarterly Labour Force Survey (LFS) and Annual Local Labour Force Surveys for England, Wales and Scotland. Although the APS has a much-improved sample size compared with the LFS, it still suffers from some shortcomings when compared with ASHE. For instance, as a survey of businesses, ASHE is thought to capture more accurate earnings information as employers can consult payroll records when responding to the survey. In comparison, earnings information collected in the LFS and APS is self-reported and as such is likely to be subject to a higher degree of recall error.Back to table of contents
The Office for National Statistics (ONS) publishes changes in average earnings for employees. However, it does not publish average pay rises.
The headline measure of changes in employee earnings is average weekly earnings (AWE), which is published monthly in the Average weekly earnings in Great Britain bulletin (and previously in the UK labour market bulletin). This is used by the Bank of England and HM Treasury to measure the inflationary pressure coming from the labour market.
AWE data are published for both regular pay ( excluding bonuses) and total pay (including bonuses). Both have specific value, but the latter typically shows more short-term variability in growth rates because it can be impacted by the timing of bonus payments each year.
Changes in earnings are presented in nominal terms (the impact of inflation is not considered) and in realterms (the impact of inflation, for which the ONS uses the Consumer Prices Index including owner occupiers’ housing costs (CPIH) measure, is considered).
AWE is calculated by dividing total pay by total number of employees (within industry strata, and then combined). This means that it is just an average and does not consider any changes in the composition of the workforce (examples of which might include a changing proportion of part-time to full-time jobs, or a change in the proportion of jobs within different occupations).
Changes in earnings among employee breakdowns such as male compared with female, part-time compared with full-time, or within different parts of the UK can be taken from the Annual Survey of Hours and Earnings (ASHE). Examples of the types of findings that ASHE provided in 2019 are:
- pay has increased relatively strongly among lowest-paid employees due to factors such as increases in the National Minimum Wage
- pay has increased more strongly in some regions of the UK than others
- there is a slow decrease in the gender pay gap
ASHE also allows users to take account of changes in the composition of the workforce. Further, it provides both median and mean estimates of pay in hourly, weekly and annual terms. Each of these measures might show a different pattern from the others and in combination they provide a comprehensive profile of how pay changes over time.
An article comparing the average weekly earnings and ASHE headline outputs investigated some of these points.Back to table of contents
During 2018 and 2019, average earnings grew faster than inflation. We refer to this as earnings growing in real terms. It follows a period of earnings rising at a slower rate than inflation (that is, earnings fell in real terms), during 2017.
Looking back further, data from the monthly UK labour market statistical bulletin show that earnings grew in real terms from 2001 to 2007, but since 2008 the trend in real earnings has been quite flat with upward and downward fluctuations. The net result is that earnings in real terms are now lower than they were in 2008. For the latest figures, use the “View latest release” button in the Average weekly earnings in Great Britain monthly bulletin.
Real earnings are calculated by deflating the average weekly earnings measure by the Consumer Prices Index including owner occupiers’ housing costs (CPIH). The CPIH is our lead measure of inflation as it is the most comprehensive measure of inflation faced by consumers.Back to table of contents
In April 2019, the occupation group with the highest median gross weekly earnings (basic pay plus incentive pay, shift-premium pay, overtime pay and other pay) for full-time employees was managers, directors and senior officials, at £862. Caring, leisure and other service occupations was the lowest-paid group, at £392 per week. These figures are taken from the Employee earnings in the UK: 2019 bulletin, which gives the median full-time gross weekly earnings for each occupation group (see Figure 10).
More in-depth occupations, with annual gross pay figures, are available in Figure 11 of the Employee earnings in the UK bulletin, with the highest-earning occupation being chief executives and senior officials (£97,708 median full-time) and the lowest-earning occupation being launderers, dry cleaners and pressers (£16,069).
These data are published as part of the Annual Survey of Hours and Earnings (ASHE), which is the UK’s most comprehensive survey of individual employee pay. Occupations are defined by the Standard Occupational Classification 2010: SOC 2010 and in-depth earnings statistics for different occupations are published in ASHE Table 14.
Gross weekly earnings by occupation are also published by the Labour Force Survey (LFS), although the data on individuals’ earnings captured by the LFS are thought to be of a lower quality than ASHE or average weekly earnings (AWE) as LFS information is self-reported by employees.Back to table of contents
The Annual Survey of Hours and Earnings (ASHE) is the official source of estimates for the number of jobs paid below the National Minimum Wage.
The ASHE dataset, Jobs paid below minimum wage by category, provides annual estimates of the number of UK jobs paid below the National Minimum Wage, and the National Living Wage since its implementation in 2016. Estimates are available by full-time and part-time working patterns, sex, age, occupation, industry, and region, from 1998 onwards. The current and historic National Minimum Wage and National Living Wage rates can be found on the GOV.UK website.
The living wage, not to be confused with the National Living Wage, is a voluntary hourly rate defined by the Living Wage Foundation. It is calculated based on the cost of living and there are separate rates for London and the rest of the UK. The current and historic living wage rates can be found on the Living Wage Foundation website. The Office for National Statistics (ONS) estimates for the number of employee jobs earning below the living wage by work geography are available, down to local authority and Parliamentary constituency levels.
The ASHE bulletin, Low and high pay in the UK: 2019, looks at the distribution of high- and low-paid jobs using the Organisation for Economic Co-operation and Development (OECD) definitions of low and high pay. Low pay is defined as the value that is two-thirds of median hourly earnings and high pay is defined as the value that is 1.5 times median hourly earnings. This is looked at in addition to jobs paid below the National Minimum Wage.
It is worth noting that, since ASHE is a survey of employee jobs, its analysis does not cover the self-employed or any jobs within the armed forces. Additionally, given the survey reference date in April, the survey does not fully cover certain types of seasonal work, for example, employees taken on for only summer or winter work.Back to table of contents