Abstract With respect to the fulfillment of the objectives of the Europe 2020 strategy, the threat of poverty and social exclusion has not been sufficiently reduced in the European Union (EU) over the past decade, and large regional disparities persist. Young people are the most affected by the problems of income poverty, material deprivation and labour market exclusion, which are the three dimensions of poverty and social exclusion. In this article, we focus on comparing the EU countries in terms of the three listed dimensions, while revealing similarities and differences in the incidence and severity of these social phenomena among youth. In addition to measuring dimensions by the currently used AROPE (at risk of poverty or social exclusion) rate, we also use a larger spectrum of relevant indicators for a more comprehensive analysis. While the AROPE aggregate indicator uses the same methodology for the population of young people as for the whole population, our approach includes indicators that are specific to young people. We assume that all dimensions affect each other, so we apply multidimensional statistical methods such as principal components and cluster analysis to analyse them. These methods have revealed that some dimensions affect poverty and social exclusion to a greater extent and others to a lesser extent than might appear to be the case, based on AROPE’s partial rates. Moreover, we present quantified integral indicators that together with the results of the multivariate methods, provide a rather complex picture concerning the geographical distribution of poverty and social exclusion, as well as their dimensions in the EU, for the population of persons aged 18–24 years in 2008 and 2017.

中文翻译：

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2008年至2017年间欧盟成员国中青年贫困和社会排斥的地理分布变化

摘要关于实现欧洲2020年战略的目标，在过去十年中，欧盟（EU）尚未充分减轻贫困和社会排斥的威胁，并且仍然存在巨大的地区差异。年轻人最受收入贫困，物质匮乏和劳动力市场排斥等问题的影响，这是贫困和社会排斥的三个方面。在本文中，我们将重点从列出的三个方面对欧盟国家进行比较，同时揭示年轻人中这些社会现象的发生率和严重性的异同。除了通过当前使用的AROPE（处于贫困或遭受社会排斥的风险）比率来衡量维度之外，我们还使用了更大范围的相关指标来进行更全面的分析。尽管AROPE总指标对年轻人口使用的方法与对整个人群相同，但我们的方法包括针对年轻人的指标。我们假设所有维度都相互影响，因此我们应用多维统计方法（例如主成分和聚类分析）对其进行分析。这些方法表明，根据AREOP的部分税率，某些方面对贫困和社会排斥的影响更大，而其他方面则较小。此外，我们提供了量化的整体指标，这些指标与多元方法的结果一起，对贫困和社会排斥的地理分布及其在欧盟的规模提供了相当复杂的描述，