Occupation coding during the interview

Journal of the Royal Statistical Society: Series A (Statistics in Society)
,
vi, 379–407 S.
,
2018,

Schierholz, Malte, Miriam Gensicke, Nikolai Tschersich, Frauke Kreuter
ISSN: 1467-985X (online)
DOI: 
10.1111/rssa.12297
Abstract

Currently, most surveys ask for occupation with open-ended questions. The verbal responses are coded afterwards, which is error prone and expensive. We present an alternative approach that allows occupation coding during the interview. Our new technique uses a supervised learning algorithm to predict candidate job categories. These suggestions are presented to the respondent, who in turn can choose the most appropriate occupation. 72.4% of the respondents selected an occupation when the new instrument was tested in a telephone survey, entailing potential cost savings. To aid further improvements, we identify some factors for how to increase quality and to reduce interview duration.

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