The design of a tool for the measurement of occupations in websurveys using a global index of occupations

Occupation is a key variable in socio-economic research, used in a wide variety of studies, but the measurement of occupations is a major challenge. In case of open-ended survey questions, websurveys pose extra challenges, as respondents are more likely to key in odd text compared to other survey modes, particularly those with an interviewer. Websurveys however offer new opportunities for closed survey questions with self-identification of occupations, particularly when using semantic matching and a database with large numbers of coded occupational titles. This paper details the design requirements for such a database to facilitate surveys in multiple countries. First, this paper describes how the WISCO Database of Occupations has developed since its first use in 2000, when the database was applied in the WageIndicator websurvey on work and wages. By the end of 2015 the websurvey and the database had expanded to 85 countries. In these fifteen years, the number of occupations in the database had increased from 55 to 1,896 and the languages covered from 1 to 43. The paper then presents an overview of the ISCO occupational classification with four hierarchical levels and their coding. It also reviews how occupations can be measured in websurveys in open-ended or closed survey questions. For the closed question three approaches are detailed, notably scrolling, search trees and semantic matching. Given that any national labour market easily cover 10,000 or more occupational titles, the semantic matching is considered the best approach provided that the look-up tables include 5,000 or more occupational titles for each country. Finally, the paper details the design principles in the database used for semantic matching. It discusses the size of the source list in relation to the ISCO coding. It details the issue of male and female titles and the use of start or end years for occupations It specifies how the database copes with highly aggregated occupational titles such as clerk or manager, with abbreviations and organisation specific job titles, with synonyms, with skill levels within and across occupations, with occupations in the corporate hierarchy, with composite jobs, with handicraft workers, and with subsistence farmers and hunters. Next, it details how to cope with respondents indicating that their job title is not in the database. The paper ends with a future outlook for a programme to test the validity and reliability of occupational measurement