A Scaling Theory Lens on Inequalities: Cities, Income, Housing

Date: Wednesday, Jun 1, 2022 | 12:00-13:00 CET

Abstract: The population size of a city has been shown to be a good predictor of its socio-economic attributes, much in the same way, as an animal’s size is a good global or first order predictor of its biological attributes. I present recent research findings on applying scaling theory towards studying income and housing costs distribution, to show that as cities grow larger, not only do they grow wealthier on average, but that they also grow more unequal. The effects work to ensure that agglomeration advantages of size accrue largely to higher income earners and has an effect on housing prices, thereby disadvantaging moderate and lower income earners. The findings inform urban policy on the debate between large and small: how should urban populations distribute over space to ensure that the economic agglomeration advantages of larger cities are maintained, while ensuring that these benefits are sustainably and equitably distributed to everybody, rather than benefiting just a few?

Speaker Biography: I am an Urban Science researcher studying spatial and socio-economic inequalities in cities. My work informs urban planning and policy by employing methods from spatial data science and modeling, geography, economics, physics, and complex systems science. I lead the Urban Science Lab and am a member of the Transport Lab, Urban Housing Lab, Smart Urbanism Lab, and the Centre for Complex Systems at the University of Sydney. I serve on the Editorial Board of Environment and Planning B: Urban Analytics and City Science. I serve as the Editor for Urban Findings.