The Local Regression Approach as a Tool to Improve Place‑Based Policies: The Case of Molise (Southern Italy)

The implementation of place-based policies entails the construction of intervention areas (spatially contiguous areas in which the policies are adopted). Many approaches can be adopted for the definition of such areas. This paper reflects on the use of geographically weighted regression (GWR) models as a tool capable of supporting the definition process. The case study concerns Molise, a region in Southern Italy particularly affected by persistent and deep-rooted processes of depopulation. The dependent variable is the average annual rate of population change of municipalities of Molise across the 2011–2019. The independent variables are related to socio-economic profiles of each municipality. The results, contextualised using a broad overview of the Italian case, show that a key variable in the demographic dynamics of the municipalities of Molise is the labour market activity rate of women and that this variable drives a spatial instability that cannot be detected using global approaches and models. This proves the urgent need to expand the use of local thinking for the benefit of both applied demography and society.