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Center for Nonlinear Studies |
Scaling relationship of population size and urban properties have shown to be an important indicator of urban dynamics. While super-linear scaling regimes are associated to social dynamics that result in the creation of information and wealth, linear and sub-linear scaling regimes respond to individual requirements and optimization processes. As such, indicators of productivity such as Gross Domestic Product and mean annual wages exhibit super-linear scaling regime resulting in a 10% increase in larger cities. Other indicators related to urban diversity have largely been portrayed as central properties of urbanization economies but have failed, so far, to be directly associated to the increased productivity of larger cities. This is partly due to the saturating relation observed with population size. I have analyzed the relation between diversity of occupations and city size for the USA between 1998 and 2010 using the full dataset available from the United States Bureau of Labor and Statistics. While a sub-linear scaling regime is observed, a paradoxical saturating relation, shows that maximum diversity of employment would quickly be attained in medium-sized cities (~150,000). We resolve this paradox assuming that the observed saturation is an outcome of a finite scaling artifact upon the classification scheme in which occupations are classified. Hence, after making such correction, we establish that diversity of employment has in fact a sub-linear scaling relationship with city size and conclude that previously observed saturation is most likely an artifact of the employed classification scheme. We finally propose that diversity has an important role in productivity-related properties of increasingly larger cities.
Host: Kipton Barros, T-4 and CNLS