A multidimensional analysis to measure social exclusion of foreign people in Italy

Cinzia Castagnaro, Instituto Nazionale di Statistica (ISTAT)
Giorgia Capacci, Instituto Nazionale di Statistica (ISTAT)
Luca Salvati, Instituto Nazionale di Statistica (ISTAT)

Starting from the beginning of the 1990s the term poverty, in Western countries, has often been replaced by the concept of social exclusion. It is a new type of poverty, due to both the lack of income as well as new privations which involve the main spheres of human life. The main goal of this study is to define a territorial mapping of social exclusion of foreign population living and working in Italy in order to point out in what territories the foreign population is more prone to poverty and deprivation and what citizenships are more ‘excluded’. The measurement takes into account different determinants affecting social exclusion, including housing, education, and labour. For each aspect we’ll consider different variables that synthesize social exclusion, calculated from the last General Population and Housing Census (2001). In this study we used the Social Exclusion Indicator according to the methodology applied to built up the Human Development Index. Furthermore with this methodology we obtain three Partial Social Exclusion Indicators, based on different research areas, such as unemployment, low education and problem in housing. The spatial unit of analysis is the 103 NUTS-3 provinces considering the whole foreign population resident in Italy and the 20 NUTS-2 regions, considering the 20 citizenships accounting for the highest number of residents in Italy. The Synthetic Index we’ll be built up using a weighting system based on a Concave Average method in order to give a higher value in correspondence to a greater distance of the spatial unit to point out the most ‘excluded’ people. Finally, we’ll obtain a synthetic evaluation of the spatial patterns of SEI index - according to the different citizenships considered - by a multivariate approach based on a Cluster analysis procedure in order to create a map of deprivation according to the different citizenships.