Measuring the task frequencies of digit ISCO occupational units in 13 countries Brian Fabo Analyst, CELSI Data and Survey Manager, WageIndicator Bratislava Kea Tijdens Research coordinator, University of Amsterdam/AIAS

Outline  Explanation of the challenge  EurOccupations approach: Methods Results Conclusion  WageIndicator approach What is WageIndicator? How is the WI survey used Time line and data intake so far

The academic challenge  Academic relevance occupation is a key variable in social sciences cross-country comparisons based on assumption that similar occupational titles refer to same work activities yet, an empirical basis for this assumption is lacking  EurOccupations project FP6 project for developing an occupations database for comparative socio-economic research in European Union (2006–09): BEL, DEU, ESP, FRA, GBR, ITA, NLD, POL Research Objective: Are occupations similar regarding work activities >> Does an Italian plumber engage in the same activities as a plumber from France, Poland or UK?

EurOccupations methods  Measuring 10 tasks for 160 occupations 160 occupations selected from the EurOccupations database with1,440 titles Selection: variation in skill level, gender composition, number of jobholders, coverage of entire labour market Drafting 10 task descriptions (desk research) per occup.  Raters: experts and job-holders Rating task frequency on a 5 point scale (never..... daily) Recruiting experts through networks EurOccupations teams (2468 experts rated 2950 occupations) For some occupations no experts - > recruiting jobholders through national WageIndicator websites (1247 raters)

Results  Q1 Are occupations similar? 51% of occupations lack of agreement or no agreement 38% weak or moderate agreement 12% strong agreement  Q2 Are occ’s similar within countries? Spain 80%, Germany 58%, Netherl. 43%, Poland 48%  Q3 Are occ’s similar across countries? Spain strong agreement, Germany weak agreement Poland and Netherlands lack of agreement  Q4 Rate experts and jobholders similar? Experts: 35% of occ’s at least moderate agreement Jobholders: 50% of occ’s at least moderate agreement

EurOccupations conclusions  Content We assume that occupations are similar across countries, but to a large extent they are not -> how to explain?  Methods Empirical testing of task descriptions can be undertaken for a wide range of occupations across Europe, particularly when recruiting jobholders through Internet Empirical testing of skill requirements can be undertaken for a wide range of occupations across Europe, but needs skill lists per occupation -> needs further development Further research may even allow for an empirical underpinning of occupational dynamics: which processes are underlying the occupational formation?

What next: How to collect data on tasks?  WageIndicator Web Survey WageIndicator survey – Covers 80 countries, gathers 1000s of cases monthly Asks for occupation, using an extended version of the EurOccupations database (all occ’s coded according to ISCO08) In addition to wage questions about working conditions, socio-economic characteristics Tasks lists were included in the web survey, these show up depending on ticked occupation, asking to tick frequency on a 5-pt scale

Measurement of task frequency  Tasks lists in the Web Survey Tasks taken from ISCO-08 description of tasks for all 4-digit occupational units (in English) Tasks lists for 427 of 433 units were prepared For 6 so-called ‘not-elsewhere-classified occupations’ no descriptions were included In total 3237 tasks (including few duplicates) on average 7.58 tasks per occupation Tasks were translated into 7 languages for 13 countries

Time line November 2013: data collection started in: Argentina, Australia, Belarus, Belgium, Brazil, Indonesia, Kazakhstan, Mexico, Netherlands, Russia, South Africa, Spain, UK April-May 2014: first analysis

Data Intake Up to January 2014 (included) the data intake is as follows:

Thanks for attention