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Skills Supply forecast
Working group I
Frank Cörvers (ROA) and Hector Pollitt (CE)
21-22 February 2008, Thessaloniki
Skills for Europe’s Future
Cedefop Skillsnet Agora conference
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21-22 February 2008, Thessaloniki
Skills for Europe’s Future
Cedefop Skillsnet Agora conference
Labour supply forecast by age and gender – E3ME
Labour supply forecast of population by
qualification
Feedback from individual country experts and Cedefop
Labour supply forecast of graduates by
qualification
Final report
Interim report
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Role of the E3ME model in the project
• To provide the link between economic development and overall labour supply
• This forms an input to modelling the supply of skills
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Description of E3ME
• Econometric model– covers EU27 + Norway and Switzerland
– based on the system of national accounts
– large sectoral disaggregation
– long and short term specification
• For more details see www.e3me.com
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Data Sources
• Eurostat National Accounts data
• OECD Structural Analysis (STAN)
• Eurostat Labour Force Survey
• Other– AMECO database
– national statistical agencies
• Model parameters are estimated on time series covering 1970-2006– 1993-2006 for New Members
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Model Enhancements
• Labour supply currently modelled for male and female population
• This will be further disaggregated into age groups
• E3ME’s equations will be modified to take into account factors relevant to particular age groups, such as pensions and training opportunities
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Forecasting Labour Supply
• Population projections to match Eurostat baseline
• Economic forecast to match EC publication
• Labour participation rates are modelled as a function of:– cyclical indicators (output)
– average wage rates
– unemployment rate
– benefit rates
– economic structure (services / manufacturing)
• Initial forecasts will be discussed with individual country experts before being finalised
• Two scenarios will be run to test key sensitivities
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Forecasting labour supply of population by qualification
• Predicting the distribution of people by qualification
• Use of multi-logit qualification model
• Cross sectional data from the Labour Force Survey (LFS)
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Multi-logit method
• Focus on Stocks of people by qualification level
• Propensity of a representative individual to obtain a level of highest qualification
• Use of multinomial logistic regression model• Independent variables:
− age − gender
− time trends− country
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Data issues
• Use of LFS microdata
• EU-27 (plus Norway and Switzerland)
• Three levels of qualification:− low: ISCED 1, 2, 3C− intermediate: ISCED 3,4− high: ISCED 5,6
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Forecasting labour supply of graduates by qualification
• Participation ratio method, focusing on flows
• Predictions of:
− Flows through the education system
− Transitions from education to the labour market
• Complementary to multi-logit method by IER
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Data issues
• EU-27 (plus Norway and Switzerland)• Three levels of qualification:
− low: ISCED 1, 2, 3C− intermediate: ISCED 3,4− high: ISCED 5,6
• Fields of education whenever possible• Aggregate data 1998-2005:
Unesco/OECD/Eurostat
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Graduation rates
• Two broad age groups: 15-19 and 20-24 years old
• ‘Estimation’ of trends in graduation rates per country and education
• Use of E3ME population forecasts
• Check with IER forecasts
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Contact details for further information:
21-22 February 2008, Thessaloniki
Skills for Europe’s Future
Cedefop Skillsnet Agora conference
Rob WilsonInstitute for Employment
ResearchUniversity of WarwickCOVENTRY, CV4 7AL
United [email protected]
Tel: +(44) 2476-523530
Frank CörversResearch Centre for
Education and the Labour Market
Maastricht UniversityThe Netherlands
[email protected]: +(31) 43-3883647
Ben GardinerCambridge Econometrics
Covent GardenCB1 2HS Cambridge
United [email protected]
Tel: +44 1223 464378