Inferring Networks of Interdependent Labor Skills to Illuminate Urban Economic Structure

Entropy 2020, 22(10), 1078; https://doi.org/10.3390/e22101078

33 Pages Posted: 19 Jun 2020 Last revised: 1 Oct 2020

See all articles by Shade T. Shutters

Shade T. Shutters

Arizona State University (ASU) - School of Complex Adaptive Systems

Keith Waters

George Mason University - Schar School of Policy and Government

Date Written: June 1, 2020

Abstract

Cities are among the best examples of complex systems. The adaptive components of a city, such as its people, firms, institutions, and physical structures, form intricate and often non-intuitive interdependencies with one another. These interdependencies can be quantified and represented as links of a network that give visibility to otherwise cryptic structural elements of urban systems. Here we use aspects of information theory to elucidate the interdependence network among labor skills, illuminating parts of the hidden economic structure of cities. Using pairwise interdependencies we compute an aggregate, skills-based measure of system “tightness” of a city’s labor force, capturing the degree of integration or internal connectedness of a city’s economy. We find that urban economies with higher tightness tend to be more productive in terms of higher GDP per capita. However, related work has shown that cities with higher system tightness are also more negatively affected by shocks. Thus, our skills-based metric may offer additional insights into a city’s resilience. Finally, we demonstrate how viewing the web of interdependent skills as a weighted network can lead to additional insights about cities and their economies.

Keywords: Urban Science, Regional Science, Cities, Workforce, Resilience, Panarchy, Information Theory, Interdependence, Co-Occurrence

JEL Classification: R1, O1, J01

Suggested Citation

Shutters, Shade T. and Waters, Keith, Inferring Networks of Interdependent Labor Skills to Illuminate Urban Economic Structure (June 1, 2020). Entropy 2020, 22(10), 1078; https://doi.org/10.3390/e22101078, Available at SSRN: https://ssrn.com/abstract=3615836 or http://dx.doi.org/10.2139/ssrn.3615836

Shade T. Shutters (Contact Author)

Arizona State University (ASU) - School of Complex Adaptive Systems ( email )

PO Box 872701
Tempe, AZ 85287-2701
United States

Keith Waters

George Mason University - Schar School of Policy and Government ( email )

Founders Hall, Fifth Floor
3351 Fairfax Drive, MS 3B1
Arlington, VA 22201
United States

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