Tijdens, K.G. (2022).The importance of occupation coding quality: lessons for EU-SILC from SHARE and other international surveys. Ch 29 (pp 413-426) in European Commission, Eurostat, Improving the measurement of poverty and social exclusion in Europe : reducing non-sampling errors : 2022 edition, Lyberg, L.(editor), Lynn, P.(editor), Publications Office of the European Union, 2022, https://data.europa.eu/doi/10.2785/18803
Access the full book:
ABSTRACT OF THE ARTICLE:
Occupation is a key variable in socioeconomic research because occupation is equally as important for an individual’s identity as for their working life, earnings capacity, social life, friendships and social status. In many surveys, including EU-SILC, respondents are asked for their occupation, and occupations are classified according to the worldwide International Standard Classification of Occupations (ISCO). Although this classification is used widely and is the standard in the EU, the academic
literature about occupational coding is predominantly country specific. Cross-national reliability of coding is important when drafting conclusions about occupational careers, occupational earnings, occupational entry levels, occupational certification, occupational boundaries and other labour market features in a European or wider context (e.g. Meng et al., 2020).
This chapter will discuss the implications of national findings for multicountry surveys, with the aim of outlining lessons for EU-SILC regarding the measurement of occupations in multicountry surveys. The chapter first sets the scene by describing the dynamics of job titles in labour markets and their implications for the measurement of occupations (Section 29.2). The chapter then reviews the details and logic of occupational classifications (Section 29.3). This is followed by an overview of occupational measurement by means of open versus closed survey questions (Section 29.4). Occupational coding is discussed in Section 29.5, including ex post coding and coding during the interview. Occupational coding is error prone, and therefore reliability is discussed, as are issues specific to occupational coding in multicountry surveys. The chapter ends with lessons for EU-SILC (Section 29.6).