Comparing Skill-Relatedness Networks: Structural Linkages vs. Relatedness in Labor Mobility

Abstract

In this paper, we compare Skill-Relatedness Networks (SRNs) across selected countries, representing statistically significant interindustrial interactions that capture latent skill exchanges derived from observed labor flows. Using data from Argentina (ARG), Germany (DEU), and Sweden (SWE), we analyze their SRNs through an information theoretic method designed to compare networks with non-aligned nodes, a crucial aspect for cross-country comparisons. By extracting network portraits—structural fingerprints based on shortest path distributions we measure pairwise divergences to contrast differences in binary connectivity and weighted skill-relatedness across countries.
Our findings reveal that ARG’s SRN structural connectivity differs significantly from those of DEU and SWE, while at the same time also contrast with each other. These findings suggest that the fundamental structure of skill-related interconnections is country specific. However, when viewed through the lens of the SR indicator, the differences between countries become less pronounced, suggesting a universal phenomenon in skill exchanges, highlighting a structured pattern of labor mobility across sectors in any national economy. These findings support the idea that historical and cultural factors shape SRNs, but structural connectivity remains country-specific. While skill intensity patterns (weighted SRNs) appear consistent across economies, the topological structure (binary SRNs) varies sharply, highlighting distinct labor market dynamics, patterns of specialization and pools of skills in each country.