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Scaling and Hierarchy in Urban Economies
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In several recent publications, Bettencourt, West and collaborators claim that properties of cities such as gross economic production, personal income, numbers of patents filed, number of crimes committed, etc., show super-linear power-scaling with total population, while measures of resource use show sub-linear power-law scaling. Re-analysis of the gross economic production and personal income for cities in the United States, however, shows that the data cannot distinguish between power laws and other functional forms, including logarithmic growth, and that size predicts relatively little of the variation between cities. The striking appearance of scaling in previous work is largely artifact of using extensive quantities (city-wide totals) rather than intensive ones (per-capita rates). The remaining dependence of productivity on city size is explained by concentration of specialist service industries, with high value-added per worker, in larger cities, in accordance with the long-standing economic notion of the "hierarchy of central places".
Forward citations
Cited by 3 Pith papers
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The third dimension of cities - relating building height, urban area, and population
Across 2,903 cities, population size tracks total building area but essentially not average building height, implying vertical development adds little capacity for residents.
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Tomography of scaling
A pairwise local exponent and a benchmark-city effective exponent are proposed as fitting-free diagnostics for scaling, yielding new insights on urban datasets.
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How the geometry of cities explains urban scaling laws and determines their exponents
City scaling exponents are claimed to follow from the ratio of the fractal dimensions of streets and 3D population, with super-linear exponents equal to two minus the sub-linear one.
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