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The scientific community has been studying for some time a measure capable of quantifying and monitoring the well-being of the population in the territories; this measure cannot be represented exclusively by economic components but also by dimensions that represent different domains of a mainly demographic-social nature. This paper aims to consider well-being from a multidimensional point of view and measure it for the 7983 Italian municipalities in order to highlight differences and similarities. To go down to such a fine territorial detail, it was necessary to use indicators implemented by administrative sources collected in a recently published portal. The application of composite indices allows a one-dimensional measurement that makes a complex phenomenon such as well-being more readable. From a territorial point of view, moreover, the work aims to overcome the administrative division already criticized in literature because it does not allow a reading corresponding to the real behaviors and lifestyles of citizens, embracing a classification more appropriate to the objective of the study. Since the elementary indicators taken into consideration are in some way influenced by reasons of proximity and/or territorial conformation, it was decided to use the classification in Ecoregions of Italy to assess whether the well-being, within the same municipality, "moves" in relation to the municipalities ecologically homogeneous. The results of the analyses present numerous aspects of originality in which the Ecoregions draw an interesting geography of the country. [ABSTRACT FROM AUTHOR]

Inclusive and equitable education and the promotion of lifelong learning opportunities for all are important targets in the 2030 Agenda for Sustainable Development. Deprivation in education, read also as deprivation of opportunities and rights i.e. health, culture, participation, social relations, referred to as educational poverty (EP), has attracted interest of researchers, which highlighted its complexities and consequences, such as being excluded from acquiring the skills needed to live in a world characterized by knowledge-based economy, rapidity and innovation. In the last few years, the Italian National Statistical Institute started to measure it by a multidimensional index, the composite educational poverty index (EPI). The index is based on survey direct estimates, which are reliable only at regional (NUTS 2) level, while to monitor and contrast the phenomenon it is important to obtain information at a finer geographical level. In this paper small area estimation models are applied to the unidimensional indicators which compose the multidimensional EPI. The aim is to enhance the knowledge of the spatial distribution of EP at local level in Italy, separating urban and non urban areas and focusing on peripheries in Italian Regions, using DEGURBA classification in order to help the policy maker to address resources towards the areas where the phenomenon is strongly present. [ABSTRACT FROM AUTHOR]