Using geodesic distances on complete Swedish kinship networks to estimate occupational clustering

Ole Hexel , Max Planck Institut für demografische Forschung
Yann Renisio , CNRS
Tobias Dalberg, Uppsala University

The distribution of resources in a given society is often evaluated via the Gini coefficient. This measure, however, ignores the social embeddedness of individuals, assuming that it does not matter to any given individual what resources (and how much of them) other socially close individuals hold. This notably abstracts away intergenerational and marital transmission of resources. We propose a way to account for the distribution of resources across social space using kinship networks. Using Swedish register data, we create multigenerational kinship networks. Social space can then be mapped by relating social groups or attributes to each other via summary measures of geodesic distances between individuals. Using a network of 565,000 individuals, we show how this new perspective could enlighten debates on occupational proximity and economic inequality.

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 Presented in Session P1. Postercafe