Un_ and Under_ employment

The unemployment rate is a headline indicator, widely reported and used in policy debates. However, low
unemployment rates could mask reality and underestimate under_employment. 

The unemployment rate shows the percentage of people in the labour force who (i) do not have a job, (ii)
are looking for one; and (iii) available to start a job. This is a set of questions, asked in a questionnaire of Labour Force Survey, the primary source of labour data nationally and globally. People, who have a job, are employed, so the unemployment rate doesn’t care about them. In a similar vein, people, who are outside of labour forces, assumed to lost connection with labour market, quit the job search and not ready to take a job. However, these assumptions could be wrong. People could work less hours than desired, be discouraged to continue job search.

Since 2013 ILO has been collecting and publishing data on underemployment, which includes three measures. One is the combined rate of time-related underemployment—persons in employment whose working time is insufficient in relation to alternative employment situations in which they are willing and available to engage—and unemployment (LU2). Another is the combined rate of unemployment and the potential labour force—persons who are not in employment, while express an interest in it, for whom existing conditions limit their active job search and/or their availability (LU3). The broadest composite rate of labour underutilization (LU4) includes all three categories, time-related underemployment, unemployment and the potential labour force.

Chart below shows these rates for countries in Europe and Central Asia. The picture varies by countries, however there are three common points here:

Underemployment rates are much higher than traditional unemployment rates. For instance, in cases of Kosovo*, Georgia, Armenia there is huge number of people out of labour force, who would like to work, but limited by circumstances. Contrary, in Montenegro, Azerbaijan, Albania, there is significant time-related underemployment.

These differences call for a systemic approach in tackling un_ and under_employment, taking into account local conditions. Lack of affordable transportation could be an obstacle in some urban areas, while lack of housing could be a limiting factor in other urban areas.

One form of labour underutilization is a skill-related inadequate employment, resulting from imbalances between skills offered by workers and those needed for jobs. We need a flexible and forward-looking approach to skills formation, which should combine traditional learning approaches with practical application during apprenticeship or internship.

LU2 is the combined rate of time-related underemployment and unemployment. LU3 is the combined rate of unemployment and the potential labour force. LU4 is the composite rate of labour underutilization. Reference year for the unemployment rate and may differ for LU2-LU4.
Data from ILOSTAT https://ilostat.ilo.org/topics/unemployment-and-labour-underutilization/

Skills for Green Jobs Transition

Every crisis is an opportunity. The Great Reshuffle and post-COVID recovery present an opportunity for the green transition and activating the jobs. However, LinkedIn’s Global Green Skills Report suggests that we face a number of challenges. This chart shows one of them. The current pace of transitions into green and greening is too slow. According to LinkedIn data, for every 10,000 workers leaving a Not Green job, only 1 moves into a Green job.

One possible accelerator of transition is skills formation. Recent publication by the European Training Foundation “The future of skills: A case study of the agri-food sector in Morocco” provides a glimpse into future of skills. Trends like automation, digitisation, global trade, competition, climate change, sustainable farming and changing consumer behaviour put a pressure on the agri-food sector, which has relied upon traditional technologies and skills.
No doubts, the forthcoming radical changes will affect jobs, by creating new ones or transforming existing ones. For instance, the boundaries between disciplines call for entirely new professions, like environmental economist or nutritionist engineer. In general, these changes imply introduction, use, and maintenance of new technologies, and more interactions with people from different disciplinary or professional backgrounds. From the skills point of view, this mean increase in demand for multi-disciplinary competences and the ability to cooperate and interact with people from different backgrounds.
This could be done by improving collaboration between education providers and companies, enhancing continuing training and reskilling and upskilling, and structuring learning courses around certain value chains.