Traditional measures of geographical concentration of industries based on regional data (such as Gini, Herfindhal, and Ellison–Glaeser indices) do not consider the information about the spatial positions of regions. This implies their insensitivity to regions’ spatial order and inability to account for neighboring effects. As an attempt to cope with this limitation, a recent stream of literature has focused on developing measures that quantify the degree of concentration of an industry while adjusting for spatial connections among regions. Following the idea that a single measure cannot fully describe the characteristics of an industry in terms of both concentration and spatial interactions, this paper proposes an alternative approach that measures the two dimensions jointly and allows for the classification of economic sectors into meaningful types of geographical configurations.

An Empirical Tool to Classify Industries by Regional Concentration and Spatial Polarization / Giuliani, Diego; Dickson, Maria Michela; Santi, Flavio; Espa, Giuseppe. - 467:(2024), pp. 247-256. [10.1007/978-3-031-65699-6_23]

An Empirical Tool to Classify Industries by Regional Concentration and Spatial Polarization

Giuliani, Diego
Primo
;
Dickson, Maria Michela
Secondo
;
Santi, Flavio
Penultimo
;
Espa, Giuseppe
Ultimo
2024-01-01

Abstract

Traditional measures of geographical concentration of industries based on regional data (such as Gini, Herfindhal, and Ellison–Glaeser indices) do not consider the information about the spatial positions of regions. This implies their insensitivity to regions’ spatial order and inability to account for neighboring effects. As an attempt to cope with this limitation, a recent stream of literature has focused on developing measures that quantify the degree of concentration of an industry while adjusting for spatial connections among regions. Following the idea that a single measure cannot fully describe the characteristics of an industry in terms of both concentration and spatial interactions, this paper proposes an alternative approach that measures the two dimensions jointly and allows for the classification of economic sectors into meaningful types of geographical configurations.
2024
Advanced Methods in Statistics, Data Science and Related Applications: SIS 2022, Caserta, Italy, June 22–24
Cham, CH
Springer
9783031656989
Giuliani, Diego; Dickson, Maria Michela; Santi, Flavio; Espa, Giuseppe
An Empirical Tool to Classify Industries by Regional Concentration and Spatial Polarization / Giuliani, Diego; Dickson, Maria Michela; Santi, Flavio; Espa, Giuseppe. - 467:(2024), pp. 247-256. [10.1007/978-3-031-65699-6_23]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/447113
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