Measuring the spatial concentration of population: a new approach based on the graphical representation of the Gini index

Massimo Mucciardi () and Federico Benassi ()
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Massimo Mucciardi: University of Messina
Federico Benassi: University of Naples Federico II

Quality & Quantity: International Journal of Methodology, 2023, vol. 57, issue 6, No 13, 5193-5211

Abstract: Abstract The spatial concentration of population is a key dimension for demography and population studies. Often it is not easy to properly measure this dimension because of its double nature (statistical and geographical process). The article proposes a new way of measuring the spatial concentration of the population based on the graphical representation of the Gini index. A spatial version of the classic Gini index of concentration (G) is therefore proposed according to the Lorenz curve notion. This version, called the Spatial Gini Index (SGI), essentially compiles in one index the two dimensions of territorial concentration: the statistical one, based on the concept of variability, and the geographical one, based on the concept of polarization (i.e., spatial autocorrelation). The proposed index is then applied to the spatial distribution of Italian and foreign residents in Italy in 2002, 2010, and 2018. The analysis is carried out at the provincial level. Results are compared to the classic Gini index, revealing important differences, especially referring to the foreign population that in this period intensively grew and presented a strong spatial bias in its territorial distribution. This underlines the importance of grasping the spatial dimension of the territorial concentration of human population. Future challenges for deploying this index are described.

Keywords: Spatial concentration; Population; Gini index; Spatial autocorrelation; Lorenz curve; Buffer distance (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11135-022-01607-2

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