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  Quantifying Agglomeration Productivity Premiums Associated With Spatial Organization In Cities And Across System Of Cities


   Department of Civil and Structural Engineering

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  Dr Hadi Arbabi  No more applications being accepted  Self-Funded PhD Students Only

About the Project

Scaling framework and models of systems of cities provide a unique approach for unifying the response of cities across a range of characteristics. These models often rely on a network formulation of the interpersonal interactions and the cities’ infrastructure as the underlying mechanism deriving various macro-level behaviours from economic productivity to the cities morphology and the spatial organization of their people, activities, and mobility costs associated with them.

This project focuses on quantifying a sense of productivity premium that may be associated with a change in spatial organization and connectivity of small-area neighborhoods relative to their existing spatial layout. This is achieved by modeling the underlying spatial network within cities based on attractivity of individuals to one another as a function of their average income/qualifications characteristics, their distance, and the ease by which these distances can be traversed.

Chemistry (6) Engineering (12)

Funding Notes

We are seeking a PhD candidate with a strong background in STEM or those with a background in urban/regional economics/planning and strong numerical and GIS skills. Familiarity with relevant software and programming languages (e.g. Python, QGIS, etc.) would be highly desirable.
Interested candidates should apply with a CV that responds to the candidate specification above and a single-page project idea on the above project statement.

References

Arbabi, H., Mayfield, M., & McCann, P. (2020). Productivity, infrastructure and urban density—An allometric comparison of three European city regions across scales. Journal of the Royal Statistical Society: Series A (Statistics in Society), 183(1), 211–228. https://doi.org/10.1111/rssa.12490
Bettencourt, L. M. A., Yang, V. C., Lobo, J., Kempes, C. P., Rybski, D., & Hamilton, M. J. (2020). The interpretation of urban scaling analysis in time. Journal of The Royal Society Interface, 17(163), 20190846. https://doi.org/10.1098/rsif.2019.0846
Yakubo, K., Saijo, Y., & Korošak, D. (2014). Superlinear and Sublinear Urban Scaling in Geographical Networks Modeling Cities. Physical Review E, 90(2). https://doi.org/10/gc4nz4

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