Abstract
A well‐developed perspective in the study of urban systems is that cities are complex systems that manifest as networks of interdependent economic units. These units might be occupations, industries, labor skills, patent technologies, etc. Much research has focused on describing the nature of these networks, quantifying their links, and suggesting applications for policymakers. In this paper, we examine the US skill network, focusing on the relationship between network centrality and economic performance. Here, nodes are represented by individual labor skills, and edge weights are derived from the colocation pattern of skill pairs among 384 US metropolitan statistical areas. The centrality of skills, using three centrality measures, is then aggregated to the occupational and metropolitan level. We find that occupations with higher skill centrality are associated with greater annual salaries, and metropolitan areas with higher skill centrality have higher productivity rates. Overall, these results suggest that the application of traditional network metrics to this view of cities as complex networks can offer new insights into the dynamics of regional economies.
Highlights
Cities are among the most discussed complex systems
Complex systems are composed of numerous independent parts [1] and exhibit “nontrivial emergent and self-organizing behaviors” [2], which are commonly characterized by fat-tailed distributions [3]. us, a characteristic of any complex system is that structure emerges from disaggregated, but interconnected, interacting parts. e myriad of independent agents working and interacting in a city results in a macrostructure that is unlikely to have been deduced if one was to examine component individuals, the hallmark of complex systems. is is especially true given that these agents are embedded in nested subsystems, such as infrastructure, governance, and ecosystems, each of which is a complex network of interacting parts [4]
To calculate the interdependence of skills, we begin by mapping O ∗ Net skill levels, l, to the number of workers, w, in an occupation, o, in a given metropolitan statistical areas (MSAs), m. is captures the total skill level, s, each MSA has for any individual skill, i
Summary
Cities are among the most discussed complex systems. Complex systems are composed of numerous independent parts [1] and exhibit “nontrivial emergent and self-organizing behaviors” [2], which are commonly characterized by fat-tailed distributions [3]. us, a characteristic of any complex system is that structure emerges from disaggregated, but interconnected, interacting parts. e myriad of independent agents working and interacting in a city results in a macrostructure that is unlikely to have been deduced if one was to examine component individuals, the hallmark of complex systems. is is especially true given that these agents are embedded in nested subsystems, such as infrastructure, governance, and ecosystems, each of which is a complex network of interacting parts [4].e intractability of modeling the multilayered complexities of cities has given rise to the view of cities as complex systems [5,6,7,8,9,10] and the growing application of complexity economics [11]. Is paper contributes to the literature on cities as complex systems by analyzing how the centrality of skills in a skills network impacts occupation and the cities that comprise these skills. Occupations with skills that occupy unique roles in the skill network may allow occupations with highly central skills to command higher wages, resulting in greater output at the regional level.
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