Measuring occupations: respondent’s self- identification from a large database

Most surveys use an open-ended question to measure occupation, followed by office coding. This is expensive and time-consuming, and some texts can be coded only highly aggregated or not at all. Alternatively, in web-surveys or during the interview respondents can self-identify their occupation from a large database of coded occupational titles. For the coding quality the size of the database is important, given that a national labour market easily has 10,000’s of job titles. The paper details the database.For many years, the worldwide WageIndicator websites on work and wages apply this self-identification method. In its Salary Check web-visitors can identify their occupation and view the related salaries. In its web survey respondents are asked to self-identify their occupation. Both applications use the same multilingual database of approximately 1,600 occupational titles, all coded ISCO08 at five digits. Users can navigate the database by means of a 3-level search tree or by text string matching. Nine in ten use the latter.As part of WorkPackage 8 of SERISS, the database is extended to 5,000 occupational titles, coded ISCO08 5-digit for approximately 35 languages, using the coding indexes from National Statistical Offices. These occupations are translated into English and their codes are compared. The subsequent solutions for ‘same occupation–different code’ problems are detailed. An API (Application Programming Interface) is designed for the survey holders (free of charge during the SERISS project). For some countries, the database includes a gender filter, showing (fe)male titles to (fe)male respondents. A life demo of the database will be shown. WP8 facilitates an occupation>>industry prediction algorithm for respondents’ easy self-identification of industry, as the majority of occupations are industry-bound. The API shows respondents a list of the five most likely industries, including an option ‘other’, which then allows respondents to search an industry database.