GDP was never designed to be a comprehensive measure of prosperity and well-being. Finding alternative indicators of progress, wealth and well-being, more inclusive of environmental and social aspects, have become a mainstream issue in the public and scientific debate.
The Equitable and Sustainable Well-being (BES) project, led by Istat, is a crucial source of information for researchers and policy makers in Italy, and many studies describing several aspects of well-being in Italy have been published based on these data.
The main aim of the project is to develop statistical procedures useful to analyse the evolution of well-being over time in Italy, to find patterns or similarities in the geographical areas and to highlight their main characteristics across space and time, a problem that has not been fully investigated so far.
The research aims at developing statistical procedures for the description and the interpretation of well being with the following main objectives:
1) Inspecting the cross-sectional structure of the set of indicators at each time occasion
2) Highlighting the temporal and spatio-temporal structure of the BES data, to highlight the evolution over time of the whole set of well-being indicators, and finding groups of units that exhibit similar patterns across time; characterizing the spatial profile of well-being in the multivariate space defined by the set of indicators
3) Describing the longitudinal and spatial variation of well-being in Italy based on the BES data made available by Istat
The BES database is a crucial source of information for researchers and policy makers in Italy, and many studies describing several aspects of well-being in Italy have been published based on these data (qualche riferimento?).
Capturing the spatial variation of well-being is one of the pillars of the "Beyond GDP" framework and is of crucial interest for planning social and political interventions [10]. The major aim of the project is to develop statistical procedures useful to analyse the evolution of well-being over time in Italy, to find patterns or similarities in the geographical areas and to highlight their main characteristics across space and time, a problem that has not been fully investigated so far. Concerning the analysis of well-being indicators, the proposals in the literature suffer from being limited to cross-sectional analyses or to be based on aggregate metrics.
Analysing the spatial variation of the phenomenon, in particular searching for spatial profiles of well-being, and understanding their persistence and dynamics over time would be of great advantage to both researchers and policy makers.
Given the multi-dimensional nature of the concept of well-being, we deem our multivariate spatio-temporal approach allows a more comprehensive view of the phenomenon.
Concerning the methodological impact, the project will build on most recent advances in the literature to produce refined robust fuzzy spatio- temporal classification techniques.
The anticipated, well known, heterogeneity of the Italian territory with respect to the perceived well-being and its dynamics, that finds its extreme in the North/South gap, can be better understood by employing multidimensional fuzzy classification techniques. Incorporating the spatial structure into the fuzzy classification algorithms permits to take into account different proximities among units. Use of fuzzy medoids as proposed in this project produces a characterization of groups that offers a direct interpretation of groups in terms of well-being metrics.