The methodology for the construction process of composite indicators is reviewed in a step-by-step approach ranging from the ex-ante definition of the latent variable that is intended to be measure, through the construction process of the composite indicators. We focus particularly on four aggregations methods in order analayze weighting and aggregation approach, Distance P_2, Principal Component Analysis, Data Envelopment Analysis and Mazziotta-Pareto Index. An empirical comparison among them is provided and the composite indices divergences are shown.

The European Union Cohesion Policy for the period 2021–2027 focuses on five goals to make the European Union smarter, greener, more connected, more social and closer to citizens. However, a macroeconomic index is proposed as the predominant criterion for allocating the Structural Funds among regions. In this paper, we hypothesise that it is possible to take into account new, complementary criteria that better reflect citizens’ quality of life. To that end, we build a composite index of socio-economic vulnerability for the 233 regions. The results show that following our multidimensional approach for allocating the Structural Funds, there are remarkable differences in the maps of priority regions. In addition, the COVID-19 pandemic represents a threat to well-being. Are all regions equally exposed to COVID-19 in terms of their socio-economic vulnerability? To address this issue, we estimate multilevel models which indicate that country characteristics interact with regions’ characteristics to alter patterns of vulnerability. More specifically, increases in government expenditures in education and an improvement in political stability would reduce the regional vulnerability or foster the capacity for resilience, whereas increases in poverty would be associated with greater vulnerability. Likewise, more vulnerable regions would be the most exposed to the negative socio-economic effects of COVID-19. However, it is remarkable that several regions of Sweden and Finland would be among the group of regions whose socio-economic vulnerability would be the most negatively affected.