Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/319214 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
CESifo Working Paper No. 11846
Verlag: 
CESifo GmbH, Munich
Zusammenfassung: 
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.
Schlagwörter: 
skills
human capital
gender
education
experience
social media
online professional network
labor market
tasks
earnings.
JEL: 
I26
J16
J24
J31
Dokumentart: 
Working Paper
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