On lagging versus leading regions in the European Union by competitiveness-density-vitality predictors

Abstract

PURPOSE: This paper aims to develop a comparable and robust framework for assessing human development at the NUTS 3 regional level within the European Union, addressing both measurement and classification challenges.

DESIGN/METHODOLOGY/APPROACH: The study constructs a Regional Human Development Index (RHDI) based on three core dimensions—economic capital, socio-human capital, and health—drawing on EUROSTAT data. Unlike the traditional UNDP Human Development Index, the proposed index employs factor score aggregation to reduce compensatory effects among dimensions. In addition, a typology of regions is developed using cluster analysis, enabling a multidimensional classification of regions into categories such as lagging, middle-developed, and leading regions. The validity of both the index and typology is tested through multivariate analysis using predictors related to competitiveness, density, and demographic vitality.

FINDINGS: The results reveal significant spatial disparities in human development across the European Union at the NUTS 3 level. Lagging regions are predominantly located in Eastern and South-Eastern Europe, while leading regions are concentrated in Northern and Western member states. The analysis confirms that higher levels of competitiveness, population density, and demographic vitality are strongly associated with higher regional human development. Furthermore, the typological approach provides additional explanatory power by capturing qualitative differences between regions that are not fully reflected in indexbased measures.

PRACTICAL IMPLICATIONS: The proposed framework offers policymakers a more granular and analytically robust tool for identifying regional inequalities and targeting cohesion policies. By combining index measurement with typological classification, the study supports more nuanced, place-based policy interventions within the European Union.

ORIGINALITY/VALUE: This research represents one of the first comprehensive attempts to measure and classify human development at the NUTS 3 level across the EU using a data-driven aggregation method. It contributes to the literature by integrating index and typology approaches and by introducing the competitiveness–density–vitality (CDV) framework.