Skill Dependencies Uncover Nested Human Capital

Abstract

Modern economies require increasingly diverse and specialized skills, many of which depend on the acquisition of other skills first. Here we analyse US survey data to reveal a nested structure within skill portfolios, where the direction of dependency is inferred from asymmetrical conditional probabilities—occupations require one skill conditional on another. This directional nature suggests that advanced, specific skills and knowledge are often built upon broader, fundamental ones. We examine 70 million job transitions to show that human capital development and career progression follow this structured pathway in which skills more aligned with the nested structure command higher wage premiums, require longer education and are less likely to be automated. These disparities are evident across genders and racial/ethnic groups, explaining long-term wage penalties. Finally, we find that this nested structure has become even more pronounced over the past two decades, indicating increased barriers to upward job mobility. Hosseinioun et al. use surveys and resumes from the USA to examine patterns of skill interdependence and identify a nested hierarchy in human capital. This structure provides insights into wage disparities and long-term wage penalties across groups.

The authors' own abstract, copied from semanticscholar.org.

How to cite it

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Hosseinioun, M., Neffke, F., Zhang, L., & Youn, H. (2025). Skill Dependencies Uncover Nested Human Capital. Nature Human Behaviour. https://doi.org/10.1038/s41562-024-02093-2

Hosseinioun, Moh, et al. "Skill Dependencies Uncover Nested Human Capital." Nature Human Behaviour, 2025, https://doi.org/10.1038/s41562-024-02093-2.

@article{hosseinioun2025skill,
  title = {Skill Dependencies Uncover Nested Human Capital},
  author = {Moh Hosseinioun and Frank Neffke and Letian Zhang and Hyejin Youn},
  journal = {Nature Human Behaviour},
  year = {2025},
  url = {https://doi.org/10.1038/s41562-024-02093-2},
}

What it is

Hosseinioun and colleagues use US survey and resume data to show skills sit in a nested order — some can only be learned once others are in place — and link that structure to wage gaps and long-term wage penalties after job loss.

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