Analysis of the multidimensional energy poverty in Italy using the partially ordered set
本文首次采用非补偿性偏序集方法，利用2004-2018年意大利面板数据分析多维能源贫困，发现严重能源贫困率从4.75%降至2.56%，为精准政策制定提供新工具。
Adequate warmth, cooling, lighting, and electrical device use are indispensable in upholding suitable living standards, health, and social inclusion. The energy crisis that followed the COVID-19 pandemic and exacerbated by rising energy prices due to the Russian-Ukrainian war has pushed energy poverty to the forefront of the EU political agenda. Although it is largely contingent upon the availability and affordability of energy services, the predominant energy expenditure approach only emphasizes the latter. Recognizing the phenomenon's multidimensionality and accurately assessing its incidence and severity are crucial for effective mitigation. However, compensation and dichotomisation of energy dimensions involved in the standard dual cut-off identification procedure may result in a loss of information. This limitation becomes more pronounced when using ordinal data, which is increasingly common in measuring multidimensional deprivation. Analyzing order relations in discrete mathematics, this paper adopts the non-compensative partially ordered set approach for the first time to examine multidimensional energy poverty in Italy using panel data for 2004–2018 from the EU_SILC database. Results show that severe energy poverty has affected at least 4.75 % of Italian households, progressively decreasing to 2.56 % in 2018, suggesting the need for the official adoption of new multidimensional measurement tools for more precise targeted policies.