Multidimensional Skills on LinkedIn Profiles: Measuring Human Capital and the Gender Skill Gap

Fuente: arXiv
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Main Authors: Dorn, David, Schoner, Florian, Seebacher, Moritz, Simon, Lisa, Woessmann, Ludger
Format: Preprint
Published: 2024
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_version_ 1866916724259946496
author Dorn, David
Schoner, Florian
Seebacher, Moritz
Simon, Lisa
Woessmann, Ludger
author_facet Dorn, David
Schoner, Florian
Seebacher, Moritz
Simon, Lisa
Woessmann, Ludger
contents We measure human capital using the self-reported skill sets of nearly 9 million U.S. college graduates from professional profiles on LinkedIn. We aggregate skill strings into 48 clusters of general, occupation-specific, and managerial skills. Multidimensional skills can account for several important labor-market patterns. First, the number and composition of skills are systematically related to measures of human-capital investment such as education and work experience. The number of skills increases with experience, and the average age-skill profile closely resembles the well-established concave age-earnings profile. Second, workers who report more skills, especially specific and managerial ones, hold higher-paid jobs. Skill differences account for more earnings variation than detailed measures of education and experience. Third, we document a sizable gender gap in skills. While women and men report nearly equal numbers of skills shortly after college graduation, women's skill count increases more slowly with age subsequently. A simple quantitative exercise shows that women's slower skill accumulation can be fully accounted for by reduced work hours associated with motherhood. The resulting gender differences in skills rationalize a substantial proportion of the gender gap in job-based earnings.
format Preprint
id arxiv_https___arxiv_org_abs_2409_18638
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multidimensional Skills on LinkedIn Profiles: Measuring Human Capital and the Gender Skill Gap
Dorn, David
Schoner, Florian
Seebacher, Moritz
Simon, Lisa
Woessmann, Ludger
General Economics
Economics
We measure human capital using the self-reported skill sets of nearly 9 million U.S. college graduates from professional profiles on LinkedIn. We aggregate skill strings into 48 clusters of general, occupation-specific, and managerial skills. Multidimensional skills can account for several important labor-market patterns. First, the number and composition of skills are systematically related to measures of human-capital investment such as education and work experience. The number of skills increases with experience, and the average age-skill profile closely resembles the well-established concave age-earnings profile. Second, workers who report more skills, especially specific and managerial ones, hold higher-paid jobs. Skill differences account for more earnings variation than detailed measures of education and experience. Third, we document a sizable gender gap in skills. While women and men report nearly equal numbers of skills shortly after college graduation, women's skill count increases more slowly with age subsequently. A simple quantitative exercise shows that women's slower skill accumulation can be fully accounted for by reduced work hours associated with motherhood. The resulting gender differences in skills rationalize a substantial proportion of the gender gap in job-based earnings.
title Multidimensional Skills on LinkedIn Profiles: Measuring Human Capital and the Gender Skill Gap
topic General Economics
Economics
url https://arxiv.org/abs/2409.18638