Occupation is a key variable in socio-economic research, used in a wide variety of studies, but its measurement is a major challenge.  The national stocks of job titles are large with 10,000’s of job titles, they are unstructured with vague boundaries between job titles, and the stock has no fixed list but instead many entries and exits over time. Measuring occupations in a multi-country survey is even a larger challenge,  because occupations with the same tasks have to be coded similarly across countries.

In 1958, the International Labour Organisation (ILO) of the United Nations developed the International Standard of Occupational Classification (ISCO) to harmonise the measurement of occupations, with revisions in 1968, 1988, and 2008. Today, ISCO has become the standard classification in many countries for their Labour Force Surveys or Censuses. ISCO-08, as was the case for its predecessors, defines a job as a set of work tasks and duties performed by one person. Jobs with the same set of main tasks and duties are aggregated into so-called 4-digit occupation units. On the basis of similarity in the tasks and duties performed, the units are grouped into 3- and 2-digit groups, which in turn on the basis of the skill level are grouped into 1-digit groups. ISCO distinguishes four skill levels, notably unskilled, semi-skilled, skilled and highly skilled, which are related to ISCED, the International Standard Classification of Education.

Most surveys use an open-ended survey question to measure occupations. The challenge relate to time-consuming and expensive office-coding. Alternatively, web surveys and CAPI surveys allow using a look-up database with occupational titles. Surveycodings provides a multilingual database of occupational titles that allow for self-identification of survey respondents, thereby tackling the challenge for  multi-country surveys  to classify job titles into ISCO-08 classification of occupations and to do so consistently across countries. The survey questions and answers for the occupation measurement, including their translations, can be found in the excel files below.

Further readings:

Tijdens, K.G. (2010) Measuring occupations in web-surveys: the WISCO database of occupations, University of Amsterdam, AIAS Working Paper 10-86

ILO (2012) International Standard Classification of Occupations ISCO-08 Volume 1 Structure, Group Definitions And Correspondence Tables. Geneva: International Labour Office

Tijdens, K.G., De Ruijter, E., De Ruijter, J. (2012) Measuring work activities and skill requirements of occupations: experiences from a European pilot study with a web-survey, European Journal of Training and Development, 36(7), 751-763

Tijdens, K.G., Vries, D., Steinmetz, S. (2013) Health workforce remuneration: comparing wage levels, ranking and dispersion of 16 occupational groups in 20 countries using survey data, Human Resources for Health, 11:11, pp.1-11

Tijdens, K.G.  (2014) Drop-out rates during completion of an occupation search tree in web-surveys, Journal of Official Statistics, 30 (1), pp. 23–43

Tijdens, K.G., De Ruijter, E., De Ruijter, J. (2014) Comparing work tasks of 160 occupations across eight European countries, Employee Relations, 36 (2), pp. 110 - 127

Castiglioni G, Tijdens KG (2014) Skills and occupational needs: labour market forecasting systems in Italy, University of Amsterdam, AIAS Working Paper 142

Tijdens KG  (2014) Reviewing the measurement and comparison of occupations across Europe, University of Amsterdam, AIAS Working Paper 149

Hunter, D. (2014) The design principles of ISCO-08: challenges for coding occupations globally. ILO Geneva. Presentation given at Amsterdam, Ingrid Workshop, February 10 2014

Tijdens KG  (2015) Self-identification of occupation in web surveys: requirements for search trees and look-up tables, Survey Methods: Insights from the Field

Tijdens KG (2015) The design of a tool for the measurement of occupations in web surveys using a global index of occupations, Working paper, Leuven, InGRID project, M21.2

Belloni M, Brugiavini A, Meschi E, Tijdens K (2016) Measurement error in occupational coding: an analysis on SHARE data , Journal of Official Statistics,  32 (4), pp. 917–945