New information on labour market signals – commentary on 2016 earnings survey (ASHE) results31st October 2016
Employers signal information to potential recruits in a number of ways. Firstly, whether they are recruiting at all, and the methods they use to advertise jobs. Secondly, the pay offered.
The Office for National Statistics produces once a year a detailed analysis of the pay and hours of employees. The detail is enormous, which means that different users may quarry different things out of the data. In this comment, we are drawing together three sources.
Firstly, the ONS release on 90 occupational groups for April 2016. Secondly, the equivalent release for 2011, the first time the same occupational groups were used. Thirdly, our own analysis of the Labour Force Survey (a quarterly ONS survey) which records, among other things, the length of time someone has been in a job and the qualifications they hold.
We are using annual earnings figures for all employees. This is so that we can see if employers respond to changes like the National Living Wage by cutting hours while increasing pay rates in line with the legal minimum. This will show up in the annual pay figures. We have compared the 2016 and 2011 earnings and hours data to see, for each of the 90 occupational groups, the percentage change in both pay and in employment numbers. We have added to this the highest qualification held by job starters in each of the same 90 occupations. We have estimated an average qualification level for the qualifications held, averaging those with Level 1, Level 2, Level 3 and Level 4 qualifications and other groupings.
What are the key findings?
These are the first results taking account of the National Living Wage for those 25 and over, which came in less than a month before the survey. Comparing the National Living Wage with the 2011 National Minimum Wage, there should have been a 18.4% rise. Because under-25s are not eligible for the higher rate, and some workers pay-periods not starting after April 1st, no occupations strongly affected by minimum wage legislation had an 18.4% rise. Two large groups, however, were close.
‘Other elementary services occupations’, including bar staff and catering assistants/waiters had a 17% rise in pay, while jobs fell by 3% over the five years. Sales assistants and cashiers had a pay rise of 15%, with a fall in numbers of 1%. Caring personal services, however, had an overall pay rise of 4%, well below the change in minimum rates, and this is likely to be due to a reduction in individual hours worked. The number of jobs in caring personal services rose by 5%, so employers have changed employment practices to reduce costs.
Cleaning occupations have had both falls in numbers and below minimum wage rises, with a 7% fall in jobs and an 8% rise in pay – above inflation (just) but below even the rise in the minimum wage. In this case, average hours have fallen (given that the minimum pay rates are set by law) but employers have also cut back on staff. Security guards (elementary security occupations) have had a very similar pattern. So different jobs affected by legal minimum wages have changed in different ways.
Other key issues are that occupations that are dominated by the public sector have had below inflation pay rises. Some (nurses, health professionals, teachers) have had growing numbers, but those associated with more administrative functions have had falls in numbers. Looking at jobs that are less affected by government decisions, two groupings where demand is strong (pay rises above inflation, growing numbers) appear. Firstly there are highly qualified professionals and associates in sales and marketing, IT professionals and Chief Executives. The second group relate to manufacturing, from engineering professionals through metal machining trades, assemblers and operatives, and distribution, with drivers and fork lift operators (mobile machine operators) doing well.
What is not visible in the figures is much evidence of demand in construction. Construction trades and building finishing trades are both down in numbers, with construction trades having below-inflation pay rises. Construction labourers are well down in numbers and have below-inflation pay rises. The only contrary factor is that construction operatives (the semi-skilled group including scaffolders) have an increase in numbers but below-inflation pay rises. These figures relate to employees, so the loudly trumpeted demand may be being expressed through self-employment, which does not send strong labour market signals by public recruitment activity and pay offers.
What is the importance of these labour market signals
Firstly, learning towards a particular career choice involves costs. It involves costs of time, effort, and, increasingly, committing to loan finance. Therefore, a prudent learner will want to know if that career choice is wanted by employers. Employers signal what they want by their recruitment activity and the earnings they pay to existing employees as well as new ones.
People will want to see that pay growth in their chosen career is doing at least as well as inflation, and that employers are growing the career by taking on more people. In some cases, where the market need for the occupation is declining, employers are seeking to improve their offers to the replacements they need by increasing pay over and above inflation. And, there are some employers who for jobs where the demand is declining and who are unwilling or unable to raise pay levels, who resort to claiming they have ‘skill shortages’ and ask careers advisers to ‘sell’ their vacancies against the market signals they are sending.
If people are committing to loan finance for a learning programme leading to an occupation, they are likely to be more sensitive to the need to be able to pay these loans back in the future, at least if they are prudent.
Charting changes over five years
We have produced an interactive chart showing the percentage change in pay (vertical axis) over the five years, the percentage change in employee numbers (horizontal axis), the number of employees in the occupation (the size of the bubble), and the qualification level for recruits (the colour of the bubble, with the lighter blue being higher qualifications).
N.B. The chart has been tested and is working (so far) in Chrome, Internet Explorer, Edge and Safari. Firefox is giving problems at the moment. We’re working on it.
For each bubble, the information for that occupation is available if you move a mouse or pointer over the bubble. You can zoom in to parts of the chart by selecting an area. You can return to the overall view by double-clicking anywhere or there is a menu at the top right.
We have six areas on the chart. These are:
- Top right. Growing jobs, rising pay. The most desirable area, where numbers in jobs are growing and pay, over five years, has risen faster than inflation.
- Middle right. Growing jobs, pay below inflation but some growth. Caution needed.
- Bottom right. Growing jobs, pay falling. May be trading on earlier pay rises so the pay levels need looking at as well as the five-year change. Caution needed.
- Top left. Falling jobs, rising pay. In this area, employers are actively seeking to replace workers who leave or retire in otherwise declining jobs.
- Middle left. Falling jobs, pay below inflation but some growth. Caution needed here.
- Bottom left. Falling jobs, actually falling pay. Here be dragons.
The changes in pay shown are affected by movements in the National Minimum Wage and, this year, by the start of the National Living Wage (aka National Minimum Wage for 25s and over) in April. This means that the five year change is likely to be higher than it would have been without these changes in legal minima. However, for these jobs, it is useful to look more closely at the changes in employment numbers. If the rises in pay were leading to job losses, this would be evident in the employment numbers. If employers are continuing to grow employment while having to pay higher earnings, this could be a good sign.
The earnings figures we are using here are annual earnings, including both full-time and part-time workers. The 2016 earnings figures used range from Chief Executives and senior officials at £81,048 (average earnings £108,450) down to elementary cleaning occupations at £7,488 (average earnings £9,161). These are the ‘median’ earnings – the point above (and below) which half the employees are paid.
Why do we use earnings including part and full-time workers equally? This is because the choice of careers is increasingly needing the learner committing to loans. If you are committing to a loan to train for a job that is largely part-time such as hairdressers (median pay £10,602) or Caring personal services (median pay £14,346) you should take this into account. Looking only at full-time workers (hairdressers £15,337, Caring personal services £18,108) might be seriously misleading. The ‘Careerometer’ from UKCES lmiforall quotes earnings for caring personal service workers from £19,240 to £21,320, nationally. As these are based on older figures, the difference in earnings of more than £5,000 a year (over a third of the 2016 overall median earnings) is very large and could, or maybe should, make a difference to career advice.
The Labour Force Survey analysis covers the whole five-year period, because in each quarterly survey there are remarkably few people who have just started a job in many of the occupation groups. With 22 quarterly datasets, we amass 33,810 job starters (including those moving jobs). If all the jobs were evenly spread across the occupations, we would have 376 in each of the 90 occupation groups, enough to do some detail on the analysis. However, job starts are not evenly spread, and so there are some of the 90 (grouped) occupations with around 30 job starts or fewer.
This is enough to calculate an average qualification level but not a great deal more. We have counted those with a both a ‘trade apprenticeship’ and no other qualification information as Level 2.5, as some older apprenticeships could be counted as Level 3 and some as Level 2. Recent Apprenticeships normally include qualifications counted as a full Level 2 or 3, but older ones may not have done so, and survey respondents can be vague on qualifications they (or their partner) did twenty years or more ago.
The 90 occupations we use are grouped from a larger list. This is because both survey sources (the ONS Annual Survey of Hours and Earnings and our analysis of the Labour Force Survey) end up with small numbers in some of the 371 occupations into which the infinite number of job titles and descriptions are coded, rendering all numerical estimates unreliable.
We have produced an interactive schematic showing how the occupation classes fit together, and therefore, the lowest-level occupation groups that fit into our 90 third-level classes.
Lastly, a major issue with these figures is that they are all based on employees. Self-employed people are not counted in these figures. This is something on which the Office of National Statistics is working, but has not got there yet. The available evidence is that self-employed earnings as recorded in their tax returns (the official source) are lower than those for employees, but show a wide range.