In a fast changing world of work, we need Labour Market Data to understand future employment needs and future provision of vocational education and training. Yet, making sense of this data can be problematic. This has led to the idea of Labour Market Intelligence, based on sense making and interpretation of Labour Market Information.
Why this is important is shown up dramatically in the article in Social Europe by German Bender entitled ‘The myth of job polarisation may fuel populism’. As German explains “It has become conventional wisdom since the turn of the century that labour markets are rapidly becoming polarised in many western countries. The share of medium-skilled jobs is said to be shrinking, while low- and high-skilled jobs are growing in proportion.” But as German points out: “In a research report published last May by the Stockholm-based think tank Arena Idé, Michael Tåhlin, professor of sociology at the Swedish Institute for Social Research, found no job polarisation—rather, a continuous upgrading of the labour market.”
German goes on to explain:
The main reason is that the research, as is to be expected from studies rooted in economics, has used wages as a proxy for skills: low-paying jobs are taken to be low-skilled jobs and so on. But there are direct ways of measuring skill demands in jobs, and Arena Idé’s report is based on a measure commonly used in sociology—educational requirements as classified by the International Labour Organization’s ISCO (International Standard Classification of Occupations) scheme. Using this methodology to analyse the change in skill composition yields strikingly different results for the middle of the skill distribution.
The study found that while jobs relatively low skill demands but relatively high wages—such as factory and warehouse workers, postal staff and truck drivers—have diminished, others with the same or slightly higher skill demands but lower wages—nursing assistants, personal-care workers, cooks and kindergarten teachers—have increased.
The reason is that the former jobs are male dominated whilst the jobs which have grown have a majority of female workers. Research in most countries has shown that women (and jobs in which women are the majority) are lower paid than jobs for men, regardless of skills levels.
“Put simply”, says German: “wages are a problematic way to measure skills, since they clearly reflect the discrimination toward women prevalent in most, if not all, labour markets across the world.”
A further review of two British studies from 2012 and 2013, showed a change in the composition, but not the volume, of intermediate-level jobs. “Perhaps the most important conclusion”, German says “was that ‘the evidence shows that intermediate-level jobs will remain, though they are changing in nature’.”
The implications of this interpretation of the data are profound. If lower and medium skilled jobs are declining there is little incentive to invest in vocational education and training for those occupations. Furthermore, young people may be put off entering such careers and similarly careers advisers may further mislead school leavers.
There has been a trend in many European countries towards higher level apprenticieships, rather than providing training with the skills need to enter such medium skilled jobs. But even a focus on skills, rather than wages, may also be misleading. It is interesting that jobs such as social care and teaching appear more resistant to automation and job replacement from technologies such as Artificial Intelligence. But those who are arguing that we should be teaching so called soft skills such as team building, empathy and communication are talking about the very skills increasingly demanded in the female dominated low and middle skilled occupations. It may be that we need not ony to relook at how we move away from wages as a proxy for skills, but also look at how we measure skills.
German references research by Daniel Oesch and Giorgio Piccitto, who studied occupational change in Germany, Spain, Sweden and the UK from 1992 to 2015, characterising good and bad jobs according to four alternative indicators: earnings, education, prestige and job satisfaction.
They concluded that occupations with high job quality showed by far the strongest job growth, whereas occupations with low job quality showed weak growth regardless of indicator used.