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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.

Suggested Citation

  • 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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    References listed on IDEAS

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    1. Coppi, Renato & D'Urso, Pierpaolo, 2006. "Fuzzy unsupervised classification of multivariate time trajectories with the Shannon entropy regularization," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1452-1477, March.
    2. Nicholas Charron & Lewis Dijkstra & Victor Lapuente, 2015. "Mapping the Regional Divide in Europe: A Measure for Assessing Quality of Government in 206 European Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 315-346, June.
    3. Heungsun Hwang & Wayne Desarbo & Yoshio Takane, 2007. "Fuzzy Clusterwise Generalized Structured Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 181-198, June.
    4. Blanca L. Delgado-Márquez & Marcos García-Velasco, 2018. "Geographical Distribution of the European Knowledge Base Through the Lens of a Synthetic Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(2), pages 477-496, April.
    5. Livia De Giovanni & Francesca G.M.Sica, 2014. "Attrattività e competitività dei territori italiani - I risultati: le dimensioni dell’attrattività territoriale," Rivista di Politica Economica, SIPI Spa, issue 4, pages 115-234, Oct.-Dec..
    6. Luis García-Escudero & Alfonso Gordaliza & Carlos Matrán & Agustín Mayo-Iscar, 2010. "A review of robust clustering methods," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(2), pages 89-109, September.
    7. Willem Heiser & Patrick Groenen, 1997. "Cluster differences scaling with a within-clusters loss component and a fuzzy successive approximation strategy to avoid local minima," Psychometrika, Springer;The Psychometric Society, vol. 62(1), pages 63-83, March.
    8. Nicholas Charron & Lewis Dijkstra & Victor Lapuente, 2015. "Erratum to: Mapping the Regional Divide in Europe: A Measure for Assessing Quality of Government in 206 European Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(3), pages 1059-1059, December.
    9. Renato Coppi & Pierpaolo D'Urso, 2002. "Fuzzy K-means clustering models for triangular fuzzy time trajectories," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 21-40, February.
    10. Dino Pinelli & Roberta Torre & Lucianajulia Pace & Laura Cassio & Alfonso Arpaia, 2017. "The Recent Reform of the Labour Market in Italy: A Review," European Economy - Discussion Papers 072, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    11. Paola Annoni & Lewis Dijkstra, 2017. "Measuring and monitoring regional competitiveness in the European Union," Chapters, in: Robert Huggins & Piers Thompson (ed.), Handbook of Regions and Competitiveness, chapter 3, pages 49-79, Edward Elgar Publishing.
    12. Renato Coppi & Pierpaolo D’Urso & Paolo Giordani, 2010. "A Fuzzy Clustering Model for Multivariate Spatial Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 54-88, March.
    13. Coppi, Renato & D'Urso, Pierpaolo, 2003. "Three-way fuzzy clustering models for LR fuzzy time trajectories," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 149-177, June.
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