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Things versus People: Gender Differences in Vocational Interests and in Occupational Preferences

Andreas Kuhn and Stefan Wolter

Journal of Economic Behavior & Organization, 2022, vol. 203, issue C, 210-234

Abstract: Occupational choices remain strongly segregated by gender, for reasons not yet fully understood. In this paper, we use detailed information on the cognitive requirements in 130 distinct learnable occupations in the Swiss apprenticeship system to describe the broad job content in these occupations along the things-versus-people dimension. We first show that our occupational classification along this dimension closely aligns with actual job tasks, taken from an independent data source on employers job advertisements. We then document that female apprentices tend to choose occupations that are oriented towards working with people, while male apprentices tend to favor occupations that involve working with things. In fact, our analysis suggests that this variable is by any statistical measure among the most important proximate predictors of occupational gender segregation. In a further step, we replicate this finding using individual-level data on both occupational aspirations and actual occupational choices for a sample of adolescents at the start of 8th grade and the end of 9th grade, respectively. Using these additional data, we finally show that the gender difference in occupational preferences is largely independent of a large number of individual, parental, and regional controls.

Keywords: Occupational choice; Occupational segregation; Things versus people; Preferences; Gender differences; Job content (search for similar items in EconPapers)
JEL-codes: D91 J16 J24 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:203:y:2022:i:c:p:210-234

DOI: 10.1016/j.jebo.2022.09.003

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Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.

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