A min-cut approach to functional regionalization, with a case study of the Italian local labour market areas

In several economical, statistical and geographical applications, a territory must be subdivided into functional regions. Such regions are not fixed and politically delimited, but should be identified by analyzing the interactions among all its constituent localities. This is a very delicate and important task, that often turns out to be computationally difficult. In this work we propose an innovative approach to this problem based on the solution of minimum cut problems over an undirected graph called here transitions graph. The proposed procedure guarantees that the obtained regions satisfy all the statistical conditions required when considering this type of problems. Results on real-world instances show the effectiveness of the proposed approach

Determinazione di aree economiche per la valutazione dell’impatto sul sistema produttivo italiano delle misure di contrasto all’epidemia da Covid-19

The paper proposes a new geography of nested economic areas that shape the Italian economy. These economic areas, named economic regions and economic macro-regions, are an upper tier integration of Local Labour Systems (LLS) obtained using a Community Detection algorithm called INFOMAP. This approachdetermines the optimal number of regions and the assignment of LLS to them, minimizing a function known as MAP Equation. In the paper, these economic areas are the unit of analysis for impact assessment on the Italian economy of control measures implemented by the government to counteract the epidemic from Covid-19. Moreover, if the purpose is to contain new epidemic hotbeds of Covid-19, these areas are the most suitable tool for doing so, because of their extremely high self-containment, much higher than that of LLSs. Finally, the paper suggests their utility for both epidemiological and socio-economic monitoring