https://orcid.org/0000-0002-7436-0055
![Sample our Geography journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5937/TOC-Subject-Sample-2021-Geography.jpg"})
ABSTRACT
The Smart Specialisation Strategy (S3) is at the core of the 2014–20 European Cohesion Policy, supporting regions to identify the technologies and economic sectors that might comprise sustainable growth paths. This paper provides an early attempt to assess empirically, for the whole European Union, whether the choices made by regions in selecting S3 target sectors are consistent with their current or potential specialization patterns. Results show only a few regions selected S3 paths rooted in both their current specializations and related activities, most of them prioritized different combinations of unspecialized or unrelated sectors, thus limiting the growth potential of their S3 policy choices.
ACKNOWLEDGEMENTS
The authors thank two anonymous referees and the associate editor of the journal for helpful suggestions and insights. They also thank Donato Iacobucci for helpful comments on an earlier version of this paper.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
FUNDING
David Rigby acknowledges funding from the Visiting Professor programme, sponsored by the Regione Autonoma della Sardegna (RAS), for his visiting period at the University of Cagliari in February 2020.
Notes
1. See https://s3platform.jrc.ec.europa.eu/home. For a detailed description of the platform, see Sörvik and Kleibrink (Citation2015). McCann and Ortega-Argilés (Citation2016) provide a first overview of the regions’ choices.
2. The economic dimension is classified according to the NACE rev2, the scientific dimension thanks to NABS 2007 and the policy dimension by referring to EU objectives.
3. We have aggregated the S3 defined at the NUTS-3 level for Sweden and Finland to the corresponding NUTS-2.
4. In six countries (Austria, Denmark, Germany, Greece, Poland and Portugal) the S3 carried out at the regional level was complemented with national projects effective for the whole country. We have excluded these national priorities to avoid the overlapping of different decision levels.
5. Four macro-sectors (A, Agriculture; K, Financial and insurance services; O-P, Public administration, education, health; and R-T, Arts, entertainment, recreation) are not available in the SBS, and the corresponding employment levels were retrieved from Eurostat Regional Accounts.
6. We excluded three small countries, Cyprus, Luxembourg and Malta, due to missing data for employment.
7. The use of the entire set of 243 regions allows us to obtain a more accurate measure of the proximity parameters, which, however, does not differ remarkably (correlation coefficient = 0.94) when it is computed using the set of 166 regions involved in the S3 policy.
8. The results are robust with respect to the use of the RCA values rather than their transformation into binary values: the correlation with the S3 matrix is 0.15.
9. Similar results are obtained by estimating the conditional probability of selecting an S3 sector given the current RCA based on logit models.
10. This distribution may explain why Deegan et al. (Citation2021) find that regions in their subsample (with all Southern countries and Romania) are inclined to choose related diversification strategies.
11. Table A3 in the supplemental data online reports detailed information on variable definitions and data sources.
12. We have also included additional indicators for the production structure, for example, the specialization in high- and medium-tech manufacturing, but the results remain unchanged.
13. In a preliminary analysis, we replaced the two territorial dummies with a set of 15 national dummies for the largest countries included in the sample. Although the results are remarkably similar, we opt to report in the more parsimonious specification with the two territorial dummies described above.
14. All results are available from the authors upon request.
15. For robustness, we also carried out the regression analysis on the composite coherence indicator obtained as the average of the normalized single indicators; the results, not reported to save space, are very similar.