This study explores the co-evolution of regional skill structures and labor market processes across US metropolitan statistical areas. Using median occupational wages from the Occupational Employment and Wage Statistics, we distinguished low-, middle-, and high-wage jobs and typified labor markets based on changes in their employment shares. We calculated skill relatedness from occupational skill indicators in the Occupational Information Network and constructed a skill network. Community detection identified distinct skill domains, which were then used to compute regional skill relatedness densities. We identified regional labor market dynamics as upgrading, downgrading, middling, and polarizing, with upgrading dominating in 2013–2023. Further, we grouped skills into social–cognitive and sensory–physical domains, with regions focusing on specific skill activities. However, there was no generalizable association between regional skill activities and labor market restructuring. The results indicated that labor market evolution is not shaped by deterministic skill structures but by the shifting dynamics of relatedness. In examining the co-evolution of technological change and labor markets, the evolutionary lens may provide a useful complement to deterministic perspectives. The temporal, multidimensional, and regionally contingent patterns of labor market evolution highlight the need for place-based workforce development strategies and time-sensitive policy interventions.
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