Network constraints on worker mobility

How do skills shape career mobility and access to cities’ labor markets? Here we model career pathways as an occupation network constructed from the similarity of occupations’ skill requirements within each US city. Using a nationally representative survey and three resume datasets, skill similarity predicts transition rates between occupations and predictions improve with increasingly granular skill data. Thus, a measure for skill specialization based on a workers’ position in their city’s occupation network may predict future career dynamics. Job changes that decrease workers’ network embeddedness also increased wages, and workers tend to decrease their embeddedness over their careers. Further, city pairs with dissimilar job embeddedness have greater census migration and increased flows of enplaned passengers according to the US Bureau of Transportation Statistics. This study directly connects workplace skills to workers’ career mobility and spatial mobility, thus offering insights into skill specialization, career mobility and urbanization.