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A Three-Way Approach for Defining Competitiveness Indexes of the European Regions (NUTS-2)

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Abstract

In the analysis of the competitiveness of the European regions a three-way approach is used to define indexes which prove to be a valid alternative and integration to the Regional Competitiveness Index (RCI). The STATIS method, which is a generalization of the Principal Component Analysis for three-way data, is applied to take into account the data structure in three macro-pillars (Basic, Efficiency, Innovation) which represent different facets of the competitiveness. STATIS searches for a common “compromise" of the macro-pillars by explicitly taking into account the similarity structure between both European regions and competitiveness indicators. The projection of the NUTS-2 European regions in a low-dimensional space spanned by the compromise allows to analyse similarities as well as disparities at regional level and provide useful and easy-to-read map to visualise both the regions and the indicators. The results largely reflect the 2019 edition of the RCI and its sub-indexes provided by Eurostat with the great advantage of not using an exogenous weighting system necessary in defining the RCI.

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Notes

  1. NUTS = Nomenclature of Units for Territorial Statistics. The RCI follows the NUTS 2016 revision (https://ec.europa.eu/eurostat/web/nuts/background).

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Acknowledgements

The authors wish to express particular thanks to Dr. Paola Annoni who provided useful information on the theoretical framework of Eurostat Regional Competitiveness. The authors thank the Editor and the referees for their useful comments and suggestions which helped to improve the quality and presentation of this manuscript.

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Authors and Affiliations

  1. Dipartimento di Scienze Sociali ed Economiche, Sapienza Università di Roma, Rome, Italy

    Laura Bocci, Pierpaolo D’Urso & Vincenzina Vitale

  2. Dipartimento di Scienze Statistiche, Sapienza Università di Roma, Rome, Italy

    Donatella Vicari

Authors
  1. Laura Bocci
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  2. Pierpaolo D’Urso
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  3. Donatella Vicari
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  4. Vincenzina Vitale
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Correspondence to Laura Bocci.

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Appendices

Appendix 1

Tables 3, 4, 5, 6, 7, 8 and 9 are reported in this Appendix.

Table 3 List of indicators
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Table 4 European regions: label and contribution (%) to the first (I) and second (II) component of the compromise
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Table 5 Indicators having Pearson correlations with the first component of the compromise larger than |0.8| and with the second component of the compromise larger than |0.5|
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Table 6 Best and worst ten regions according to the Overall competitiveness index based on the first component scores of the compromise space
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Table 7 Pearson correlations of the indicators with the partial factor scores of the first (I) and second (II) component for the Basic macro-pillar
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Table 8 Pearson correlations of the indicators with the partial factor scores of the first (I) and second (II) component for the Efficiency macro-pillar
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Table 9 Pearson correlations of the indicators with the partial factor scores of the first (I) and second (II) component for the Innovation macro-pillar
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Appendix 2

Figures 11, 12, 13 and 14 are reported in this Appendix.

Fig. 11
figure 11

Eurostat Regional Competitiveness Index (RCI)

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Eurostat Basic sub-index

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Fig. 13
figure 13

Eurostat Efficiency sub-index

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Fig. 14
figure 14

Eurostat Innovation sub-index

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Bocci, L., D’Urso, P., Vicari, D. et al. A Three-Way Approach for Defining Competitiveness Indexes of the European Regions (NUTS-2). Soc Indic Res (2021). https://doi.org/10.1007/s11205-021-02839-9

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