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Evaluating the Role of Clusters for Innovation and Growth in Europe

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Geography, Institutions and Regional Economic Performance

Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

The analysis of clusters has attracted considerable interest over the last few decades. The articulation of clusters into complex networks and systems of innovation – generally known as regional innovation systems – has, in particular, been associated with the delivery of greater innovation and growth. However, despite the growing economic and policy relevance of clusters, little systematic research has been conducted into their association with other factors promoting innovation and economic growth. This chapter addresses this issue by looking at the relationship between innovation and economic growth in 152 regions of Europe during the period between 1995 and 2006. Using an econometric model with a static and a dynamic dimension, the results of the analysis highlight that: (a) regional growth through innovation in Europe is fundamentally connected to the presence of an adequate socioeconomic environment and, in particular, to the existence of a well-trained and educated pool of workers; (b) the presence of clusters matters for regional growth, but only in combination with a good ‘social filter’, and this association wanes in time; (c) more traditional R&D variables have a weak initial connection to economic development, but this connection increases over time and, is, once again, contingent on the existence of adequate socioeconomic conditions.

JEL Codes: O32, O52, R11

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Notes

  1. 1.

    Another aspect is local institutions, which are, however, hard to measure at the regional level for the whole of Europe.

  2. 2.

    The detailed methodology is available directly on the website: www.clusterobservatory.eu. Only clusters with at least 1,000 workers are taken into consideration in order to “prevent the appearance of very small insignificant clusters” (Cluster Observatory website in Methodology: Evaluation of regional cluster strength).

  3. 3.

    Bulgaria, Cyprus, Denmark, Estonia, Ireland, Latvia, Lithuania, Luxembourg, Malta, Romania, Slovenia and Sweden were excluded because of lack of sufficient and/or reliable regional data on R&D expenditure.

  4. 4.

    Nomenclature of Territorial Unit for Statistics as defined by the European Commission on http://ec.europa.eu/comm/eurostat/ramon/nuts/home_regions_en.html

  5. 5.

    In addition, some specific regions have been excluded because of lack of data. This is the case of all the French Overseas Departments and Territories, and of the regions of the Åland islands (Finland), Açores and Madeira (Portugal) and the African enclaves of Ceuta and Melilla (Spain)

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Author information

Authors and Affiliations

  1. London School of Economics, London, UK

    Andrés Rodríguez-Pose

  2. College of Europe, Bruges, Belgium

    Fabrice Comptour

Authors
  1. Andrés Rodríguez-Pose
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  2. Fabrice Comptour
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Corresponding author

Correspondence to Andrés Rodríguez-Pose .

Editor information

Editors and Affiliations

  1. , Dept. of Geography and Environment, London School of Economics, Houghton Street, London, WC2A 2AE, United Kingdom

    Riccardo Crescenzi

  2. , Institutional Analysis and, Università Bocconi, via Rontgen 1, Milano, 20121, Italy

    Marco Percoco

Appendices

Appendix A. Annex 1: The Exact Formula of Specialisation and Focus

These formulas are directly extracted from the European Cluster Observatory’s website: www.clusterobservatory.eu

1.1 A.1. Specialisation Quotient

$$ S{{Q}_{{r,s}}} = \frac{{ {{{{e}_{{r,s}}}}}/{{{{E}_s}}} }}{{ {{{{E}_r}}}/{E} }} $$

  • SQr,s = the specialisation quotient for region r and cluster sector s

  • er,s = the number of employees for region r and cluster sector s

  • Es = the total number of employees in all regions for sector s

  • Er = the total number of employees in all cluster sectors for region r

  • E = the total number of employees in all regions and all cluster sectors

Put in a simpler way the Specialisation Quotient is given by

$$ \frac{{(\rm{Employment}\;\mathrm{in}\;\mathrm{a}\;\mathrm{region}\;\mathrm{in}\;\mathrm{a}\;\mathrm{category})\;/\;(\mathrm{Total}\;\mathrm{employment}\;\mathrm{in}\;\mathrm{a}\;\mathrm{region})}}{{(\rm{Employment}\;\mathrm{in}\;\mathrm{a}\;\mathrm{category}\;\mathrm{in}\;\mathrm{Europe})\;/\;(\mathrm{Total}\;\mathrm{employment}\;\mathrm{in}\;\mathrm{Europe})}} $$

1.2 A.2. Focus

$$ {{F}_{{r,s}}} = \frac{{{{e}_{{r,s}}}}}{{{{E}_r}}} $$

  • er,s = the number of employees for region r and cluster sector s

  • Er = the total number of employees in all cluster sectors for region r

Appendix B. Annex 2: PCA Analysis

In this annex, the results of the three Principal Components Analyses are given

2.1 B.1. Principal Component Analysis for Social Filter

Table A.5 Eigenanalysis of the correlation matrix: social filter
Full size table
Table A.6 Coefficients of the PCA: social filter
Full size table

2.2 B.2. Principal Component Analysis for Clusterisation Index

Table A.7 Eigenanalysis of the correlation matrix: clusterisation index
Full size table
Table A.8 Coefficients of the PCA: clusterisation index
Full size table

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Rodríguez-Pose, A., Comptour, F. (2013). Evaluating the Role of Clusters for Innovation and Growth in Europe. In: Crescenzi, R., Percoco, M. (eds) Geography, Institutions and Regional Economic Performance. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33395-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-33395-8_11

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