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

Author: David Dorn (University of Zurich)Florian Schoner (ifo Institute, University of Munich)Moritz Seebacher (ifo Institute, University of Munich)Lisa Simon (Revelio Labs)Ludger Woessmann (University of Munich, ifo Institute)
Posted: 2 December 2025

Abstract

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 contribute substantially to the gender gap in job-based earnings.
JEL codes: I26, J16, J24, J31
Keywords: skills, human capital, gender, education, experience, social media, online professional network, labor market, tasks, earnings