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arXiv · 1601.05664

Defining urban agglomerations to detect agglomeration economies

Abstract

Agglomeration economies are a persistent subject of debate among economists and urban planners. Their definition turns on whether or not larger cities and regions are more efficient and more productive than smaller ones. We complement existing discussion on agglomeration economies and the urban wage premium here by providing a sensitivity analysis of estimated coefficients to different delineations of urban agglomeration as well as to different definitions of the economic measure that summarises the urban premium. This quantity can consist of total wages measured at the place of work, or of income registered at the place of residence. The chosen option influences the scaling behaviour of city size as well as the spatial distribution of the phenomenon at the city level. Spatial discrepancies between the distribution of jobs and the distribution of households at different economic levels makes city definitions crucial to the estimation of economic relations which vary with city size. We argue this point by regressing measures of income and wage over about five thousands different definitions of cities in France, based on our algorithmic aggregation of administrative spatial units at regular cutoffs which reflect density, population thresholds and commuting flows. We also go beyond aggregated observations of wages and income by searching for evidence of larger inequalities and economic segregation in the largest cities. This paper therefore considers the spatial and economic complexity of cities with respect to discussion about how we measure agglomeration economies. It provides a basis for reflection on alternative ways to model the processes which lead to observed variations, and this can provide insights for more comprehensive regional planning.

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Clementine Cottineau, Olivier Finance, Erez Hatna, Elsa Arcaute, Michael Batty. 2016-01-21. Defining urban agglomerations to detect agglomeration economies. https://doi.org/10.1177/2399808318755146

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