In April 2021, average hourly earnings growth was 6.6 percentage points higher for employees who had changed jobs compared with those who stayed in their jobs.
Hourly earnings themselves, however, are consistently higher for employees who have stayed in their job for longer than a year; in April 2021, average hourly earnings were 17% higher for stayers.
Employees aged 16 to 24 years not only change jobs more often than those aged 25 to 49 years but have higher earnings growth when they do.
Median hourly earnings growth was 6.6 percentage points higher for employees who had not been furloughed at any point between April 2020 and April 2021, compared with those who had been furloughed.
On average, employees who changed job and moved into the accommodation and food services industry experienced negative earnings growth in April 2021.
Job changers who switched industries, occupations, or region as well as changed jobs experienced higher earnings growth than those who moved jobs within their industry, occupation, or region.
This article examines the earnings growth of job changers and stayers, updating our previous analysis from 2019, which found that nominal earnings growth was greater for employees who changed their jobs, compared with employees who stayed in their current jobs.
Since 2019, the labour market has been affected by the coronavirus (COVID-19) pandemic, with restrictions affecting some businesses' ability to trade, and the introduction of support schemes such as Coronavirus Job Retention Scheme (CJRS). More recently, the labour market has been characterised by a record number of job vacancies and falling unemployment, which could indicate a tightening of the labour market. Moreover, average earnings growth have been affected by changes in the composition of the workforce and base effects.
It is especially relevant to examine the earnings of job changers and stayers given the current context of high rates of job-to-job moves. Data from the Labour Force Survey (LFS) show job-to-job moves have increased from 530,000 in the period July to September 2020 to 994,000 in January to March 2022.
The Annual Survey of Hours and Earnings (ASHE) provides us with detailed earnings information on different characteristics of the employee workforce. These data are collected in April of each year, with the latest data available covering April 2021. As such, they provide some insight into how the coronavirus (COVID-19) pandemic and CJRS has affected nominal earnings growth for job stayers and changers but does not necessarily reflect the increases in job-to job moves, which happens after April 2021.
Using ASHE April 2021 data, we have updated previous analysis to reflect the labour market conditions of the coronavirus pandemic and expanded it to look at different types of employees who have a "moving incentive", to provide greater insight into the role of labour mobility in earnings growth.
In this analysis, job stayers are characterised as employees who stay in their job over two consecutive years, whereas those who have changed jobs from one year to the next are referred to as job changers. We use nominal annual earnings growth for both job changers and stayers throughout the analysis, that is, earnings not adjusted for inflation.Back to table of contents
Between April 2012 and April 2021, average hourly earnings growth was consistently higher for workers who had changed job. In April 2020, average hourly earnings growth for both changers and stayers fell to 6.5% and 2.1%, respectively, as employee earnings were affected by the coronavirus (COVID-19) pandemic and the Coronavirus Job Retention Scheme (CJRS). By April 2021, as unemployment began to fall, average earnings growth recovered to pre-coronavirus pandemic levels but only for workers who changed jobs.
Although average earnings growth is consistently higher for workers who have changed jobs, job stayers on average earn a higher hourly wage compared with individuals who change jobs, as seen in Figure 2. This may be partly because of the skills and experience gained by staying in a job and the nature of more secure, longer-term employment. Another explanation for this difference is the age profile of these two groups. Younger workers on average have lower earnings but higher earnings growth when they change jobs, as seen in Figure 3. In April 2021, job changers aged 65 years and over were the only group to see lower earnings growth than the year before.
Between April 2012 and April 2021, younger employees were more likely to change jobs than older employees. In the year to April 2021, 14.2% and 14.1% of those aged between 16 and 20 years, and aged between 21 and 24 years, respectively, had changed jobs. This is compared with 5.1% of employees aged between 35 and 49 years who changed jobs. Fewer financial dependants, less settled careers, and greater likelihood of renting are all potential explanations for younger workers being more mobile in the labour market.
Figure 3: Younger people on average experienced higher earnings growth when they changed jobs
Median annual growth of hourly earnings for job changers and stayers, by age group, UK, April 2012 to April 2021
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Male job changers had consistently higher average earnings growth in the period between April 2012 and April 2018, as seen in Figure 4. However, median earnings growth was very similar for male and female job changers in the period between April 2019 and April 2020.
In April 2021, average earnings growth for male job changers was 0.9% higher than female job changers. This may be explained by compositional effects, with women more likely to work in caring, leisure and other service occupations where there is lower earnings growth for job changers relative to other occupations, as seen in Figure 8.Back to table of contents
In April 2021 average earnings growth for employees who changed their jobs was 6.6 percentage points lower for those who had been furloughed at any point in the previous 12 months.
Figure 5: Median hourly earnings growth was 6.6 percentage points higher for employees who had not been furloughed at any point between April 2020 and April 2021
Median annual growth of hourly earnings for job changers by furlough status, UK, and April 2021
- Those identified as furloughed in 2021 comes directly from ASHE. For 2020 this is supplemented data from CJRS, therefore, the estimates of furlough will be on a slightly different basis
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Employees who were furloughed appear to have not been able to increase their earnings in the same way as those who were never furloughed, even when they changed jobs. In April 2021, average earnings growth for job changers who had not been furloughed was 6.6 percentage points higher than for changers who had been furloughed. This is likely because of an industrial composition effect, as workers in industries most affected by coronavirus (COVID-19) restrictions, such as the accommodation and food services, were more likely to be furloughed as well as having lower earnings growth than other less affected industries.
The Coronavirus Job Retention Scheme (CJRS) statistics show that the accommodation and food service activities industry had the highest proportion of its employees furloughed (84%) in April 2020.
More information on how compositional effects have affected earnings is available.
Employees who had been furloughed at any point between April 2020 and April 2021 were less mobile, with 3.1% changing jobs compared with 6.3% of employees who had never been furloughed.Back to table of contents
Between April 2012 and April 2021 employees who changed jobs within the same industry had lower earnings growth than those who changed jobs between industries.
In April 2021, median earnings growth was 2.1 percentage points higher for workers who changed jobs by moving into different industries than for those who changed jobs but remained in the same industry. This shows a moving incentive for workers to move into different industries.
Average earnings growth also varies by industry, and there are variations in the earnings growth of job changers depending upon the industry that employees move to (the industry of destination) and from (the industry of origin).
Figure 7 splits employees into three broad groups. It shows employees who, between April 2020 and April 2021:
changed jobs and industry
changed jobs within the same industry
stayed in the same job
Figure 7: Average earnings growth was highest for employees who left the accommodation and food services and negative for employees entering the accommodation and food services
Median annual growth of hourly earnings for job changers and stayers by industry, broken down by industry of origin and destination, UK, April 2021
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In the period April 2020 to April 2021, those moving from the accommodation and food services to a different industry had the greatest earnings growth of 25.9%.
Employees who changed job but remained in the accommodation and food services industry between April 2020 and April 2021 saw lower earnings growth of 9%.
The size of the difference in earnings growth (16.9 percentage points) between employees moving within this industry and those moving outside of this industry resulted in a strong incentive to leave the industry.
In contrast, employees who moved into the accommodation and food industry between April 2020 and April 2021 on average saw their earnings fall by 2.9%. This suggests a strong earnings incentive to move out of the accommodation and food services industry between April 2020 and April 2021, alongside a weak earnings incentive for employees to move into the industry.
For employees who changed jobs but remained in the information and communication industry, average earnings growth was 19.9%, the highest of any industry. This is 2.3 percentage points higher than if they were to leave the industry, resulting in an earnings growth incentive for employees to remain in the information and communication industry.Back to table of contents
When looking at the occupation of employees in April 2021, managers, directors and senior officials had the highest earnings growth (16.2%) when they had changed jobs. This group of occupations also had the lowest earnings growth for workers who had not changed jobs (2.5%). This represents a very large moving incentive for mobile employees in this group.
In groups such as elementary occupations, skilled trades occupations, and caring, leisure and other service occupations, there was a smaller moving incentive as earnings growth was low even when workers changed jobs.
Figure 8: Managers, directors and senior officials had the highest earnings growth if they changed jobs
Median annual growth of hourly earnings for changers and stayers by occupation, April 2021
- Occupation of employment in April 2021
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These occupations can be split into four “skill levels”, based upon characteristics of employees. Broadly, occupations within the higher two skill levels see high moving incentives with high earnings growth for changers but low growth for stayers. The reverse is true for occupations within the lower two “skill levels”; there is higher growth for stayers but not as high as if they were to change jobs. This shows that earnings growth from labour mobility is highly unequal and most accessible for employees in “higher skilled” occupations.
In April 2021, employees who changed job and moved to another occupation on average had earnings growth of 12.4%, compared with 8% for those who changed job but remained in the same occupation. This creates a moving incentive of 4.4 percentage points for changing occupation, which is higher than the 2.1 percentage points for those who changed industry.
Employees who changed job but not occupation are those who are recorded in the Annual Survey of Hours and Earnings (ASHE) as having moved jobs in the last 12 months but have the same occupation code. Promotions may be captured by employees who have moved jobs but remain in the same occupation, as high-level occupation breakdowns are used.
More detailed information on Coronavirus and occupational switching is available.Back to table of contents
In April 2021, average hourly earnings growth was 0.2 percentage points higher for employees who changed job within the same international territorial level (ITL1) classification English region or UK country, compared with employees who changed job as well as the ITL1 region in which they worked.
This is markedly different to April 2019, before the coronavirus (COVID-19) pandemic, where average earnings growth was 1.6 percentage points higher for employees who changed jobs as well as the ITL region in which they worked.
Figure 10: Earnings growth for stayers was similar across the UK
Median annual growth of hourly earnings for job changers and stayers, ITL1, UK, April 2021
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The increase in homeworking during the coronavirus pandemic may have enabled employees to access jobs further away from their home, rather than having to look for employment in different areas.
Using international territorial level (ITL1) classification of the highest-level UK countries and regions, this includes workers who moved employment and ITL1 English region and UK country, for example, from London to Scotland, as well as those who moved employers over neighbouring ITL1 regions, such as from London to the South East.
Median average earnings growth was highest for changers who worked in London in April 2021 at 14.6%. However, for employees in this region who stayed in their jobs, there was comparatively low earnings growth of 2.8%, resulting in a large moving incentive.
The ITL1 English region or UK country with the highest growth for those who stayed in their jobs was Northern Ireland and Scotland, where median earnings growth for stayers in April 2021 was 3.2%. London had the highest earnings growth for changers; however, this is comparing a singular city with large regions and whole countries and is therefore a result of strong compositional effect.Back to table of contents
ASHE contains the variable "sjd" that identifies employees who were in the same job as the year before or not. We use this variable to define job stayers, who are in the same job as the previous year (sjd=1), and job changers, who are not in the same job as the previous year (sjd=2).
To create the longitudinal ASHE dataset, employees are matched at t and t-1 years to identify those who are surveyed in ASHE in consecutive years, earnings growth between years can then be calculated. This, however, means that each year around 30% of the total sample "drop out" and do not feature in the constructed longitudinal ASHE data.
For the analysis:
all earnings analysis is conducted using hourly earnings, derived by dividing the gross pay (including incentive pay, overtime and shift premiums) by the total paid hours worked during the reference period
median hourly earnings growth is used to capture the typical experience of earnings growth; this pay growth is representative because it is the centre of the distribution of earnings growth and indicates how the middle earnings in one period compares with that in the next period
ASHE methodology is not specifically designed to model earnings growth for employees over time
A measure of the average. The median is calculated by identifying the exact middle point in a set of observations. When the observations are ranked from lowest to highest, the median is the value in the exact middle of the observed values. It is the Office for National Statistics' (ONS) preferred measure of average earnings as it is less affected by a relatively small number of very high earners than the mean is.
COVID-19 is the name used to refer to the disease caused by the SARS CoV-2 virus, which is a type of coronavirus.
International Territorial Level (ITL)
The International Territorial Levels (ITL) is a hierarchical classification of administrative areas used for statistical purposes. ITL1 are major socio-economic regions, while ITL2 and ITL3 are progressively smaller regions. In the context of the UK, the ITL1 areas are Wales, Scotland, Northern Ireland and the nine regions of England.Back to table of contents
This analysis focused on the subset of ASHE for which employees appear in two consecutive years, allowing us to make inferences about the wider population of individuals who are employed at both t and t-1 years.
Given that the annual response rate is less than 100% and the construction of the longitudinal dataset drops employees not surveyed in consecutive years, there is attrition in the panel dimension of ASHE. This has necessitated the construction of longitudinal weights that correct for attrition in longitudinal ASHE data. The Office for National Statistics (ONS) is working with the Wage and Employment Dynamics project. This project aims to quality assure ASHE and provide longitudinal weights.Back to table of contents
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