Skill Relatedness Networks: Portraits of Developed and Developing Countries

SERGIO ANDRÉS DE RACO; SEMESHENKO, VIKTORIYA

Montevideo

Congreso; Knowledge, Innovation and Regional Development in South America (KIRDSA); 2024

UDELAR

We build Skill-Relatedness Networks (SRNs), that represent significant labor flows in terms of non-random occurrence, which allows the representation of inter-industrial connections with information on skill exchange revealed in job-switchings. Using data from Argentina (ARG), Germany (DEU) and Sweden (SWE), we compare their SRNs utilizing an information-theoretic method that permits to compare networks of non-aligned nodes using portraits, a fingerprint of structural measures based on contrasting the divergence between the distributions of their shortest paths. This allows to analyze in conjunction the structural connectivity with the information provided by Skill Relatedness (SR), about the existence and degree of significance of its interconnections, shaping the productive network. We find that, in the case of ARG, structural connectivity is very different from their counterpart in DEU and SWE, but through the glass of SR the distances analysed are substantially more alike. This appears to show information on the SR indicator showing some hidden dimension different from connectivity alone.