WP2 workshop, NIESR, November 24-25, 2005 Labour quality

What types of labour? We initially proposed in our –No gender split –Age - experience is likely to be important we recommended three age bands –15-29 –30-49 –50+ –Skills groups –Variable over national education systems –More detail than high, medium and low –Generally, around 5 skill groups

Gender –General agreement that a gender split picks up something other than differences in marginal products; however, –Some partners were keen to include it for its analytical power, to observe differences in discrimination across member states. Relatively easy to collect? Useful for the analytical model?

Age We agree with the comment made that the start age for our youngest age group should be 15, not 16. There was a suggestion that the middle age group should run only until 45. Are there strong feelings about this in the group? There was a suggestion that the final age class should be cut off at 65 rather than leaving it open ended, however, this was rejected due to complications for future data gathering, as changes in working ages and demographics feed into the economy

Skill how many groups? –University graduate –Higher education below degree –Intermediate vocational plus advanced education –Low intermediate plus low education –No skills Is Occupation a reasonable alternative to skills?

Skill - Comparability across countries Do we attempt to match skills across countries? First alternatives – use International Standard Classification of Education system (ISCED-97) to place qualifications/educational attainment into groups 1.Primary 2.Lower Secondary 3.Upper Secondary 4.Post Secondary-non Tertiary 5.First stage Tertiary 6.Second stage Tertiary OECD implementation manual available

Comparability across countries Alternative – do not attempt to match all categories For growth rates use conventional Tornqvist index For levels comparisons match one category, (university graduates, ISCED group 6) and convert all other qualifications to university equivalents using relative wages as weights More flexible than using international coding since only matching one group Experience suggests results are sensitive to which group is put in which category

Sample sizes How to deal with small sample sizes Assume labour and wage bill shares are constant across sub-sectors Use econometric estimation for wage impacts Combine a range of alternative sources