Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/270461 
Erscheinungsjahr: 
2022
Schriftenreihe/Nr.: 
Bruegel Working Paper No. 07/2022
Verlag: 
Bruegel, Brussels
Zusammenfassung: 
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.
Schlagwörter: 
inequality
growth
future of work
Dokumentart: 
Working Paper
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