For many newly emerging jobs, labour-market mismatches prevail as workers and firms are unable to apply precise occupation taxonomies and training lags behind workforce needs. We report on how data can enable useful foresight about skill requirements and training needs, even when that data has not been collected for this express purpose. First, we show how online generated freelance data can help monitor labour-market developments in the short run. Second, in the long run, we illustrate how data can shed light on development of workplace-ready aptitudes among students, even when these are not the direct focus of instruction. This combination of data-intensive activities can inform the immediate and long-term needs for education and training in order to help individuals develop the ability to learn, train and retrain as often and as much as needed.
The Beveridge curve that describes the relationship between unemployment and job vacancy rates allows us to study the impact of business cycles on skill mismatches and their development over time. In times of economic contractions, vacancy rates decrease and unemployment rises. In times of skill mismatches or increased search intensity, shifts in the curve can occur when unemployment rises given a specific level of vacancies. Figure 1 shows that in the European Union, the Beveridge curve shifted outwards during the 2008-2021 period. After 2013, job vacancy rates increased and unemployment rates declined. At time of writing, vacancy rates are higher than 10 years ago, with a slightly higher level of unemployment, indicating that despite economic recovery, many firms are not able to fill their vacancies.
Chosen excerpts by Job Market Monitor. Read the whole story @ Is the workforce ready for the jobs of the future? Data-informed skills and training foresight | Bruegel