Other commentary from the latest labour market data can be found on the following pages:Nôl i'r tabl cynnwys
Annual growth in average employee pay continued to strengthen, the growth is driven in part by compositional effects of a fall in the number and proportion of lower-paid employee jobs and by increased bonuses, which had been postponed earlier in the year.
Growth in average total pay (including bonuses) among employees for the three months October to December 2020 increased to 4.7%, and growth in regular pay (excluding bonuses) increased to 4.1%.
Current average pay growth rates are being affected upwards by a fall in the number and proportion of lower-paid jobs compared with before the coronavirus (COVID-19) pandemic; it is estimated that underlying wage growth - if the effect of this change in profile of jobs is removed - is likely to be under 3%.
During the early summer months, some industry sectors experienced substantial falls in average pay, for example accommodation and food services and construction saw pay down more than 10% in April to June; in October to December all industry sectors are now seeing positive pay growth.
In October to December 2020, the rate of annual pay growth was positive 4.7% for total pay and positive 4.1% for regular pay.
The rate of total and regular pay growth had stood at 2.8% and 2.9%, respectively in December 2019 to February 2020 immediately prior to any impact from the coronavirus (COVID-19) pandemic was seen. It then slowed sharply in April to June 2020 to negative 1.3% for total pay and negative 0.1% for regular pay before some increase between July and December. The higher percentage growth figure for total pay reflected an increase in bonus payments, because of bonus payments being postponed from earlier in the year.
In real terms, total pay is now growing at a faster rate than inflation, at positive 3.8%, and regular pay growth in real terms is also positive, at 3.3%.
More about economy, business and jobs
The change in pay growth has been affected by a changing composition of employee jobs, where we have seen a fall in the number and proportion of lower-paid employee jobs (Figure 2).
Changes in the profile of employee jobs in the economy will affect average pay growth; a decrease in employee numbers in jobs that have lower pay can have an upward effect on average pay, and vice versa. This is particularly important to consider at present because both of the two main sources of information about number of employee or employee jobs paid through payroll (HM Revenue and Custom's Pay As You Earn Real Time Information, and the Office for National Statistics' (ONS's) Monthly Wages and Salaries Survey) identify a year-on-year fall of close to 2.5%. We consider such compositional effects from three angles.
Analysis of Labour Force Survey (LFS) data highlights a recent decrease in the number of part-time jobs (which have a lower average pay), and jobs in some lower-paying occupations such as elementary occupations. This changing composition naturally increases average pay and needs to be borne in mind when interpreting average pay growth. Figure 2 highlights that the impact of these changes, when taken in combination with age of employee, is approximately 2.8%, compared with approximately 1% before the coronavirus (COVID-19) affected the workforce. It therefore appears that the net impact of recent job losses, when measured in terms of type of job and age profile of jobholder, is to increase the estimate of average pay by approximately 1.8%.
Similar analysis, but based on the changing distribution of jobs between industries, is provided in Dataset Earn02. The pattern of change in jobs between industries has a much smaller impact on average pay growth, estimated at 0.1%. This is the net impact of a falling number of employees on payroll in lower-paying sectors, being offset by a fall in number of employees in the higher-paying industry professional, scientific and technical activities, and an increase in number of employees in lower-paying health and social work activities. This was discussed in the Average weekly earnings in Great Britain: November 2020, publication.
A third angle is provided by analysis of job inflows and outflows in HMRC Earnings and employment from Pay As You Earn Real Time Information, UK: December 2020. This considered tenure of employees who fill the stock of jobs and suggests that a fall in new entrants to the labour market (who are lower-paid than average) has contributed to an increase in average pay, with a magnitude of approximately 1%.
These three compositional analyses are not mutually exclusive, and don't necessarily consider all the compositional effects that impact average pay. Therefore, they don't provide a definitive answer to how much job composition changes have had an impact, but they do indicate that a proportion of estimated pay growth is because of recent changes in employee job profiles. We plan to conduct more detailed analysis on the impact of compositional factors.
Although we are seeing this compositional effect, there is still an underlying pay growth that is estimated to be around 3%. This is also supported by the recent growth of aggregate pay (total amount paid across all employees), as shown by the Earnings and employment from Pay As You Earn Real Time Information (RTI), UK: February 2021 data. In December 2020 aggregated pay increased by 3.3% compared with December 2019. As noted earlier RTI data have showed a decrease in the number of employees paid via payroll, so this decrease and the increase in aggregate pay growth indicate some underlying average pay growth.
Between October to December 2019 and October to December 2020, average pay growth varied by industry sector (Figure 3). The finance and business services sector saw the highest estimated growth in total pay, at 6.8%. All sectors saw positive growth, although construction (1.9%) and manufacturing (1.5%) had smaller growth than the other sectors. This is an improvement on the growth rates in April to June 2020, the three-month period with the biggest falls in average pay, when all these sectors except for the public sector had negative growth rates.
The pattern of pay growth is also affected by the proportion of employees who are furloughed and the extent to which employers have topped up payments received for these employees under the Coronavirus Job Retention Scheme (CJRS). We have published estimates of less than 8% of the workforce on partial or furlough leaving during October, before rising to 13.7% later in December.
For December 2020, average total pay, before tax and other deductions, for employees in Great Britain was estimated at £571 per week in nominal terms. When expressed in real terms (constant 2015 prices) the figure in December 2020 was £523 per week, notably higher than the £488 per week estimated in June 2020.
Average regular pay was estimated at £534 per week in nominal terms. When expressed in real terms (constant 2015 prices) the figure in December 2020 was a record £489, after having fallen back to £464 per week in April 2020.Nôl i'r tabl cynnwys
Average weekly earnings
Dataset EARN01 | Released 23 February 2021
Headline estimates of earnings growth in Great Britain (seasonally adjusted).
Average weekly earnings by sector
Dataset EARN02 | Released 23 February 2021
Estimates of earnings in Great Britain broken down to show the effects of changes in wages and the effects of changes in the composition of employment (not seasonally adjusted).
Average weekly earnings by industry
Dataset EARN03 | Released 23 February 2021
Estimates of earnings in Great Britain broken down by detailed industrial sector (not seasonally adjusted).
Average Weekly Earnings
Average Weekly Earnings (AWE) is the lead monthly measure of average weekly earnings per employee. It is calculated using information based on the Monthly Wages and Salaries Survey (MWSS), which samples around 9,000 employers in Great Britain.
The estimates are not just a measure of pay rises as they do not, for example, adjust for changes in the proportion of the workforce who work full-time or part-time or other compositional changes within the workforce. The estimates do not include earnings of self-employed people.
Estimates are available for both total pay (which includes bonus payments) and regular pay (which excludes bonuses). Estimates are available in both nominal terms (not adjusted for inflation) and real terms (adjusted for inflation).
Estimates of pay growth are also published using HM Revenue and Custom's (HMRC) data in the Earnings and employment from Pay As You Earn Real Time Information, UK: February 2021.
The HMRC estimates are presented in median pay-terms, but they also include mean pay as does AWE. There are some differences between the sources, most notably that the HMRC estimates include any redundancy payments that are made through payroll. Further detail is provided in a Comparison of labour market sources, published 11 December 2020.
A bonus is a form of reward or recognition granted by an employer. When an employee receives a bonus payment, there is no expectation or assumption that the bonus will be used to cover any specific expense. The value and timing of a bonus payment can be at the discretion of the employer or stipulated in workplace agreements.
Consumer Prices Index including owner occupiers' housing costs
As of 21 March 2017, the Consumer Prices Index including owner occupiers' housing costs (CPIH) became our lead measure of inflation. It is our most comprehensive measure of UK consumer price inflation.
Monthly Wages and Salaries Survey
The Monthly Wages and Salaries Survey (MWSS) is a survey through which we collect information on wages and salaries. It is distributed monthly to around 9,000 employers covering around 12.8 million employees.
A more detailed glossary is available.Nôl i'r tabl cynnwys
The survey response rate was 78%, only slightly lower than the 83% target in more typical months.
In line with international guidance, the seasonal adjustment process has been reviewed and revised this month, with all periods in the AWE series open to revision.
For more information on how labour market data sources are affected by the coronavirus (COVID-19) pandemic, see the article published on 6 May 2020, which details some of the challenges that we have faced in producing estimates at this time.
An article published 11 December 2020 compares our labour market data sources and discusses some of the main differences.
Our latest data and analysis on the impact of the coronavirus on the UK economy and population are available on our dedicated coronavirus web page. This is the hub for all special coronavirus-related publications, drawing on all available data. In response to the developing coronavirus (COVID-19) pandemic, we are working to ensure that we continue to publish economic statistics. For more information, please see COVID-19 and the production of statistics.
In April 2020, potentially significant changes in employee pay, associated with social distancing measures, made it necessary to change some aspects of the processing of average weekly earnings (AWE) data. The normal approach to processing both non-responding companies and those whose pay shows sharp unconfirmed changes from historical returns, is to roll forward (impute) employee and pay details from the most recent responding month. In April, additional data validation was conducted, and information gathered from responding companies was used in the imputation of non-responding companies.
End of EU exit transition period
As the UK enters into a new Trade and Co-operation Agreement with the EU, the UK statistical system will continue to produce and publish our wide range of economic and social statistics and analysis. We are committed to continued alignment with the highest international statistical standards, enabling comparability both over time and internationally, and ensuring the general public, statistical users and decision makers have the data they need to be informed.
As the shape of the UK's future statistical relationship with the EU becomes clearer over the coming period, the ONS is making preparations to assume responsibilities that as part of our membership of the EU, and during the transition period, were delegated to the statistical office of the EU, Eurostat. This includes responsibilities relating to international comparability of economic statistics, deciding what international statistical guidance to apply in the UK context and to provide further scrutiny of our statistics and sector classification decisions.
In applying international statistical standards and best practice to UK economic statistics, we will draw on the technical advice of experts in the UK and internationally, and our work will be underpinned by the UK's well-established and robust framework for independent official statistics, set out in the Statistics and Registration Service Act 2007. Further information on our proposals will be made available later this year.
We will continue to produce our labour market statistics in line with the UK Statistics Authority's Code of Practice for Statistics and in accordance with International Labour Organization (ILO) definitions and agreed international statistical guidance.
Estimates for small businesses in average weekly earnings
This bulletin relies on data collected from the Monthly Wages and Salaries Survey (MWSS), a survey of employers in Great Britain, excluding small businesses employing fewer than 20 people. More quality and methodology information on strengths, limitations, appropriate uses, and how the data were created is available in the Average weekly earnings QMI.
Because the MWSS does not sample businesses with fewer than 20 employees, the earnings for these businesses are estimated using a factor derived from the Annual Survey of Hours and Earnings (ASHE). These "under 20s" factors are reviewed annually, and the revised factors are included in AWE if they cause notable changes to the earnings data.
The main challenge for updating the factors this year is that the ASHE data are felt to be out-of-date considering the rapidly changing picture regarding furloughed employees. Initial investigations suggest that not updating the under 20s factors would have little impact on the AWE estimates - the impact is estimated to be approximately 0.2% at whole economy level.
Therefore, it has been agreed that the under 20s factors will not be updated for 2020. However, the ONS will explore the possibility of using more up-to-date data to produce factors better reflecting the evolving situation for furloughed employees.
|Including bonuses |
(Jan to Apr)¹ ²
|Including bonuses |
(May to Dec)¹ ²
|Whole Economy||± 0.9||± 0.5||± 0.5|
|Private Sector||± 0.9||± 0.6||± 0.5|
|Public Sector||± 0.9||± 0.5||± 0.5|
|Services||± 1.0||± 0.6||± 0.5|
|Finance and Business Services||± 2.8||± 1.6||± 1.4|
|Public Sector excluding Financial Services||± 0.7||± 0.5||± 0.5|
|Manufacturing||± 1.1||± 1.0||± 0.9|
|Construction||± 2.5||± 2.6||± 2.4|
|Wholesale and retail, hotels and restaurants||± 2.1||± 1.7||± 1.5|
Download this table Table 1: Sampling variability for average weekly earnings single month growth rates in percentage points.xls .csv
The figures in this bulletin come from a survey of businesses that gathers information from a sample rather than from the whole population. The sample is designed to be as accurate as possible given practical limitations such as time and cost constraints. Results from sample surveys are always estimates, not precise figures. This can have an impact on how changes in the estimates should be interpreted, especially for short-term comparisons.
As the number of people available in the sample gets smaller, the variability of the estimates that we can make from that sample size gets larger. Estimates for small groups (for example, earnings for the construction sector), which are based on small subsets of the Monthly Wages and Salaries Survey (MWSS) sample, are less reliable and tend to be more volatile than for larger aggregated groups (for example, earnings for the private sector).
In general, short-term changes in the growth rates reported in this bulletin are not usually greater than the level that can be explained by sampling variability. Short-term movements in reported rates should be considered alongside longer-term patterns in the series and corresponding movements in other sources to give a fuller picture.Nôl i'r tabl cynnwys
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