A carregar...
Publicação
Rethinking Child Poverty in the EU: A cluster-based alternative to AROPE
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.59 MB | Adobe PDF |
Orientador(es)
Resumo(s)
This thesis develops a multidimensional, child-specific typology of poverty and social exclusion across European Union Member States using harmonised national-level indicators from Eurostat. While the EU’s official measure, AROPE, plays a central role in social monitoring, it relies on household-level income and employment metrics that overlook key disadvantages experienced by children. To address this limitation, the study constructs a dataset of nine child-focused indicators capturing housing deprivation, economic insecurity, and early education access. After standardisation and targeted imputation, two clustering techniques, Ward’s hierarchical method and k-means, are applied to identify cross-country deprivation profiles. The analysis yields a four-cluster structure that distinguishes low, moderate, and high levels of child deprivation, including two extreme profiles corresponding to Greece and the Bulgaria–Romania group. In parallel, the AROPE components are disaggregated into seven mutually exclusive intersections and subjected to the same analytical pipeline, producing a simpler three-cluster typology characterised by a large low-risk group and a sharply isolated high-risk cluster. PaCMAP embeddings provide additional insight into the geometric structure of the data, revealing that the child-specific indicators form a dispersed and multidimensional landscape, whereas the AROPE components generate a compressed configuration with limited internal variation. Overall, the findings demonstrate that child-focused indicators capture structural patterns of disadvantage that remain invisible under income-based measures alone, underscoring the importance of multidimensional approaches for monitoring child well-being and informing EU social policy.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
Palavras-chave
AROPE Child Poverty Cluster Analysis European Union Multidimensional Deprivation PaCMAP