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Cross Sectional and Longitudinal Fuzzy Clustering of the NUTS and Positioning of the Italian Regions with Respect to the Regional Competitiveness Index (RCI) Indicators with Contiguity Constraints

Author

Listed:
  • Pierpaolo D’Urso

    (Sapienza University of Rome)

  • Livia De Giovanni

    (LUISS Guido Carli and CEFOP-LUISS)

  • Riccardo Massari

    (Sapienza University of Rome)

  • Francesca G. M. Sica

    (Confindustria and CEFOP-LUISS)

Abstract

In socio-economical clustering often the empirical information is represented by time-varying data generated by indicators observed over time on a set of subnational (regional) units. Usually among these units may exist contiguity relations, spatial but not only. In this paper we propose a fuzzy clustering model of multivariate time-varying data, the longitudinal fuzzy C-Medoids clustering with contiguity constraints. The temporal aspect is dealt with by using appropriate measures of dissimilarity between time trajectories. The contiguity among units is dealt with adding a contiguity matrix as a penalization term in the clustering model. The cross sectional fuzzy C-Medoids clustering with contiguity constraints is obtained considering one instant of time. The model is applied to the classification of the European NUTS on the basis of the observed dynamics of the Basic, Efficiency and Innovation subindexes of the Regional Competitiveness Index (RCI) 2013 and 2016. The positioning of the Italian regions is analyzed through the values of the medoids of the clusters and shows the peculiarities of the regions with respect to the subindexes either in single times or in the dynamic. Two contiguity constraints, one based on the European Western, Southern, Central and Northern geographic areas and one on the level of GDP—taken into account in the computation of the RCI—are also introduced in the models.

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  • Pierpaolo D’Urso & Livia De Giovanni & Riccardo Massari & Francesca G. M. Sica, 2019. "Cross Sectional and Longitudinal Fuzzy Clustering of the NUTS and Positioning of the Italian Regions with Respect to the Regional Competitiveness Index (RCI) Indicators with Contiguity Constraints," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(3), pages 609-650, December.
    • Handle: RePEc:spr:soinre:v:146:y:2019:i:3:d:10.1007_s11205-019-02134-8
    DOI: 10.1007/s11205-019-02134-8
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    3. Alaimo, Leonardo Salvatore & Nigri, Andrea, 2024. "The gender gap in life expectancy and lifespan disparity as social risk indicators for international countries: A fuzzy clustering approach," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
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    5. Maria Gabriella Grassia & Marina Marino & Rocco Mazza & Michelangelo Misuraca & Emma Zavarrone & Martha Friel, 2024. "Regional Competitiveness: A Structural-Based Topic Analysis on Recent Literature," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 173(1), pages 83-108, May.

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