Abstract

In order to promote inclusion and social cohesion, it is fundamental to focus on the measurement of territorial and socio-demographic disparities. Social exclusion has increased over the last ten years in Italy due to the economic crisis and the pandemic, with geographical inequalities playing a significant role. The talk presents how the interaction between the Academia and the Italian National Statistical Office has allowed to provide estimates of indicators of social inclusion, using small area estimation methods, which allow reliable estimates at the local level and for subgroups of the population defined by gender, nationality, and education, without increasing sample size or survey costs. In particular, using advanced statistical models to produce multidimensional indicators and integrate information from various sources, it has been possible to provide estimates at a level of detail that was not covered by official statistics. This allows the identification of disadvantaged areas and/or groups in order to inform targeted policies and ensure the monitoring of social exclusion, assess its persistence, and reduce disparities related to gender, age, and nationality.