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Mantas Sekmokas Unit E3 – VET, Apprenticeships and Adult learning

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Presentation on theme: "Mantas Sekmokas Unit E3 – VET, Apprenticeships and Adult learning"— Presentation transcript:

1 Subject for LFS AHM 2022 Job Skills – the background 23-24 October 2018, Luxembourg
Mantas Sekmokas Unit E3 – VET, Apprenticeships and Adult learning Directorate General for Employment, Social Affairs and Inclusion

2 Recap: policy need Changing the content of tasks carried out at work – driver of technological, economic and social transformation Tasks established as a key measure of individual level skills demand However only limited availability of actual data for the EU – existing sources face issues with qulity, sample, conceptual and country coverage

3 Recap: policy use For assessing automation risk (different criteria):
Physical tasks (brute force – more automatable) Routine tasks (more automatable) Social/complex tasks (less automatable) Cognitive tasks (complementary with technology) Use of digital equipment (machine learning) Use of non-digital equipment (digitalisation) For assessing occupational skills demand (literacy/numeracy/technology training needed) For assessing differences (inequality) of skills use within sectors, companies, occupations > wages

4 Recap: why LFS Ranked as top priority by LAMAS priority setting
Reliability and possible disaggregation of occupational data (ISCO) Reliability and possible disaggregation of educational attainment data (ISCED) EU28 coverage LFS the only source providing these possibilities

5 Recap: validity and reliability
“Using original, representative survey data, we document that analytical, routine, and manual job tasks can be measured with high validity, vary substantially within and between occupations, are significantly related to workers’ characteristics, and are robustly predictive of wage differences between occupations and among workers in the same occupation.” Autor and Handel (2013) Journal of Labour Economics, Vol. 31, No. 2, The Princeton Data Improvement Initiative

6 Recap: preparatory work
Eurofound taxonomy of tasks using cluster analysis of available survey variables in 2016 JRC statistical analysis to identify best performing and predictive items in 2018 Review of new items developed recently by OECD (PIAAC cycle II), Germany (NEPS), US (STAMP) Detailed feedback from TF2 members

7 Thank you


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