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The Local Regression Approach As a Tool to Improve Place-Based Policies: the Case of Molise (southern Italy)

Spatial Demography(2024)

University of Naples Federico II | University of Molise

Cited 0|Views7
Abstract
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.
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Spatial demography,Place-based policy,Local regression approach,Depopulation,Southern Italy
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要点】:本文探讨了地理加权回归(GWR)模型在辅助定义干预区域的应用,并以意大利南部地区莫利塞的人口变化为例,证明了地方性方法在理解人口动态中的重要性。

方法】:研究采用了地理加权回归模型,这是一种考虑地理位置对数据关系影响的地方性回归方法。

实验】:通过对莫利塞地区2011-2019年各市镇年均人口变化率的依赖变量,以及与各市镇社会经济概况相关的独立变量的分析,实验结果表明女性劳动力市场活动率是影响莫利塞地区人口动态的关键变量,这一变量导致的空间不稳定性是全局方法无法检测到的。数据集名称未在摘要中提及。