Multivariate analysis of poverty and social exclusion across EU countries in the context of Sustainable Development Goal 1
- 1Faculty of Business Economics with seat in Košice, Bratislava University of Economics and Business, Košice, Slovak Republic
Abstract
Poverty reduction remains one of the socio-economic concerns of the international agenda. This research aims to examine the multidimensional nature of poverty across EU Member States through a multivariate analysis of selected socio-economic indicators. Ten indicators were initially selected to capture the multidimensional nature of poverty and the broader socio-economic situation encompassing income poverty and deprivation within the sustainable development goal 1, housing conditions, economic performance and digital factors. Based on the Kaiser-Meyer-Olkin test and subsequent statistical analyses, six indicators were retained for the final multivariate analysis. Data were drawn from the Eurostat Database. Univariate and multivariate statistical techniques were applied during the analyses. Pearson’s correlation coefficient was used to find linear relationships between pairs of indicators, while a principal component analysis and a cluster analysis were implemented to examine multidimensional structures and patterns. The multivariate analysis was conducted across three time spans: 2015–2019, 2020 (analysed separately as the Covid-19 pandemic disrupted economies) and 2021–2023. The results reveal a general decline in poverty; nevertheless, they also emphasise persistent regional disparities across EU Member States. Bulgaria, Greece, Romania, and Latvia form the most vulnerable cluster in the final period, whereas several countries in Northern and Western Europe show more stable trends. The results further indicate that multidimensional poverty profiles cannot be explained solely by economic performance or geographical location. In conclusion, the cluster-based approach provides a dynamic perspective on the diverse experiences of poverty in the EU. The results show the need for tailored policy responses that reflect the specificities of individual EU countries and clusters to promote sustainable and inclusive development and to strengthen resilience to potential future crises.
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BibTeX
@article{megyesiova2026multivariate,
title = {{Multivariate analysis of poverty and social exclusion across EU countries in the context of Sustainable Development Goal 1}},
author = {Silvia Megyesiova and Cecilia Olexova},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0343050},
url = {https://doi.org/10.1371/journal.pone.0343050},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Multivariate analysis of poverty and social exclusion across EU countries in the context of Sustainable Development Goal 1
AU - Silvia Megyesiova
AU - Cecilia Olexova
PY - 2026
DA - 2026/09/30
JO - PLOS One
DO - 10.1371/journal.pone.0343050
UR - https://doi.org/10.1371/journal.pone.0343050
AB - Poverty reduction remains one of the socio-economic concerns of the international agenda. This research aims to examine the multidimensional nature of poverty across EU Member States through a multivariate analysis of selected socio-economic indicators. Ten indicators were initially selected to capture the multidimensional nature of poverty and the broader socio-economic situation encompassing income poverty and deprivation within the sustainable development goal 1, housing conditions, economic performance and digital factors. Based on the Kaiser-Meyer-Olkin test and subsequent statistical analyses, six indicators were retained for the final multivariate analysis. Data were drawn from the Eurostat Database. Univariate and multivariate statistical techniques were applied during the analyses. Pearson’s correlation coefficient was used to find linear relationships between pairs of indicators, while a principal component analysis and a cluster analysis were implemented to examine multidimensional structures and patterns. The multivariate analysis was conducted across three time spans: 2015–2019, 2020 (analysed separately as the Covid-19 pandemic disrupted economies) and 2021–2023. The results reveal a general decline in poverty; nevertheless, they also emphasise persistent regional disparities across EU Member States. Bulgaria, Greece, Romania, and Latvia form the most vulnerable cluster in the final period, whereas several countries in Northern and Western Europe show more stable trends. The results further indicate that multidimensional poverty profiles cannot be explained solely by economic performance or geographical location. In conclusion, the cluster-based approach provides a dynamic perspective on the diverse experiences of poverty in the EU. The results show the need for tailored policy responses that reflect the specificities of individual EU countries and clusters to promote sustainable and inclusive development and to strengthen resilience to potential future crises.
SN - 1932-6203
ER -