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AbstractComposite indicators are often used to assess the structure of urban deprivation to promote sustainable development. However, the refined spatial scale of analysis poses problems related to data availability. In this paper, we define a spatial deprivation index in the province of Milan, using both census data and areal interpolation. Disaggregation methods are applied to obtain variables at lower spatial level, and a geographically weighted principal component analysis is applied to measure socio‐economic deprivation at local level. Components of deprivation are investigated in their spatial structure and some policy implications deriving from the application of a spatial approach are discussed.

AbstractSince some decades, inequality has been attracting a growing interest within political debate as well as in theoretical and empirical studies. Considering inequality at a regional level offers useful insights for policy makers, facilitating the assessment of the effectiveness of strategies aimed at reducing regional disparities and helping in developing place‐based actions. The study of regional inequality poses some relevant issues related to the spatial nature of data. In fact, dealing with georeferenced data implies the opportunity of considering the spatial interactions among regional units that are likely to play a role in shaping the inequality dynamics. Some studies have highlighted the importance of incorporating spatial effects in a traditional measure of inequality such as the Gini index. These studies are based on the definition of a proximity structure, which allows one to discriminate between the spatial and the non‐spatial component of inequality. Different definitions of the proximity structure are likely to influence the spatial component of inequality. Those aspects are analysed in the present paper to offer more detailed insights in the territorial dimension of inequality. The measures and their decompositions are discussed in the case of European NUTS 3 regions.