1. #EUDatathon2017 Webinar Ilias Livanos Expert, Cedefop
September, 28, WebEx
25/10/ 2011

2. The Data: Skills Demand and Supply Projections

3. How was the data produced?
Cedefop has engaged into skills needs forecasting since 2005.
Various datasets were used (e.g. National Accounts, EU LFS), including official macroeconomic and population projections.
Different modules were applied combining macroeconomic modelling and various sophisticated econometric techniques.
The results go through ICE’s scrutiny.

4. Why is the data important?
Knowledge of future employment prospects can inform an number of actors:
Policy makers (education, migration etc.)
Employers (recruitment policies)
Employees (career moves)
Individuals (future planning)
Intermediaries (guidance tools)

5. What could be improved & limitations
However detailed, users will always want more
The projections do not mean to replace national forecasts but provide comparative evidence
Demand and supply are not directly comparable
Detailed estimates may be unreliable (<10 000)
Should be combined with local knowledge and other sources of information
The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.
The detailed occupational estimates are based on data from the European LFS, often covering just a few years. These have been used to forecast the shares to The LFS values used in the calculation are indicated in sheet 'Info'. For historical years the LFS share, or the share in the first LFS year available, is used. In some cases, the small sample sizes mean that individual cells of the data arrays (by country, industry and occupation) are empty or contain unreliable data. This can distort pictures of change over time. Various criteria have been used to check the estimates and to try to avoid implausible projections.

6. What could the data still reveal?
Prospects of occupations and sectors across countries
Job opportunities due to expansion & replacement
Deep country, sectoral, occupational analysis
Can help job mobility (immigration trends) by identifying future needs
Can inform career planning tools
The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.
The detailed occupational estimates are based on data from the European LFS, often covering just a few years. These have been used to forecast the shares to The LFS values used in the calculation are indicated in sheet 'Info'. For historical years the LFS share, or the share in the first LFS year available, is used. In some cases, the small sample sizes mean that individual cells of the data arrays (by country, industry and occupation) are empty or contain unreliable data. This can distort pictures of change over time. Various criteria have been used to check the estimates and to try to avoid implausible projections.

7. Thank you for your attention!
Ilias Livanos
Department for Skills and Labour Market