Competitiveness through integration in the European Union Strategy for the Alpine Region: a ‘balanced development’ approach

ABSTRACT

In the last 10 years, the European Union has devoted specific attention and resources to the establishment of macro-regional strategies, with the objective of joining together transnational areas to favour the effective and organized management of common challenges. In most macro-regions, however, the identification of strategies to increase competitiveness is a rather difficult task, given the extreme internal diversity in economic activities. Focusing on the youngest macro-regional strategy – EUSALP – this paper highlights the specific combinations of territorial growth assets that allow to overcome the inefficient use of local abundant strategic resources, in line with a ‘balanced development’ approach. The results, obtained on the basis of a database gathered at NUTS3 level, are useful to provide policy suggestions to support the competitiveness of EUSALP through synergies and complementarities, according to a cooperation networks perspective.

KEYWORDS:

• Macro-regional strategy
• EUSALP
• balanced development
• cooperation networks

Acknowledgements

The authors gratefully acknowledge comments and suggestions by Professor Roberto Camagni (Politecnico di Milano).

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Roberta Capello http://orcid.org/0000-0003-0438-6900

Silvia Cerisola http://orcid.org/0000-0001-6283-8982

Notes

1 European Commission, accessed 18 October 2018 at http://ec.europa.eu/regional_policy/it/policy/cooperation/macro-regional-strategies/.

2 ‘Resources’ and ‘assets’ are used as synonyms within the present work and relate to the production factors that are necessary for a specific area economic system to produce a given output.

3 Territorial assets, or production factors, are of different nature. Some of them are tangible (material) like natural resources and infrastructure. More recently the literature has highlighted the great importance that intangible (non-material) assets, like values, trust and institutions, have in the regional growth (see Camagni, 2009).

4 A vast literature exists on the ‘milieu innovateur’ theory. See, e.g., Aydalot (1986), Aydalot and Keeble (1988), Camagni (1991), Maillat, Quévit, and Senn (1993), Camagni (1995), RERU (1999), Camagni and Capello (2002), Camagni and Maillat (2006).

5 Data on employment by sector and size class were retrieved through the National Statistical Offices. For further details on the empirical identification of the development patterns, please refer to Capello and Cerisola (2018b).

6 Table A.1 in Appendix reports the measures chosen at the NUTS3 level for the different resources.

7 The choice of using such dummy variable is indeed related to the fact that, basically, abundant strategic resources can be used more or less efficiently. We intend to focus on the cases in which a relevant endowment of strategic resources is in fact inefficiently exploited, in order to be able to highlight the context conditions that could improve such situation, allowing to overcome inefficiencies. The final aim is to suggest possible actions to push the competitive performance.

8 Productivity is computed as real GDP/employment and the period under consideration is determined by the fact that the specific development patterns are identified on the basis of the 2011 sectoral structure of the employment and depending on data availability at NUTS3 level.

9 Table A.2 in Appendix displays descriptive statistics on the distribution of the development patterns and of the strategic resources.

10 The Moran index (Moran, 1950), the Lagrange multiplier and the robust Lagrange multiplier (Anselin, 1988) are all measures of spatial autocorrelation, which occurs when given elements correlate with other nearby elements across a spatial area. The statistical insignificance of the tests shows that spatial autocorrelation is not relevant in our analyses (or that it is suitably taken into account through the clustering of the error terms at the country level).

11 The high-tech SMEs development pattern was not taken into account in this analysis since it already shows an efficient use of its abundant strategic resource (see Table 1).

12 According to the approach used within the ESPON project 1.3.3 (data source) the presence of cultural events can be interpreted as a measure of identity since only ‘those events with certain characteristics which stress their connection with the local cultural identity’ were included (see https://www.espon.eu/programme/projects/espon-2006/thematic-projects/impacts-cultural-heritage-and-identity, accessed November 20 2018).

13 Patent activities is one of the possible measures for the creation of new knowledge. It captures the creation of formal new knowledge, typical of large firms, while it is not able to catch informal and tacit new know-how, which is instead a typical way of creating knowledge by small firms.

14 The present work substantially differs from Capello and Cerisola (2018a), since the latter is a descriptive work aimed at providing a picture of the EUSALP macro-region, highlighting its strengths and weaknesses but not including any theoretical identification of different development patterns and any econometric inference. It also substantially differ from Capello and Cerisola (2018b) in that the analysis of the overcoming of the inefficient use of strategic resources is totally missing in the (2018b) work.

15 European Commission (2015) Action Plan accompanying the document Report of the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions concerning the European Union Strategy for the Alpine Region, SWD (2015) 147 final.

16 Specific ‘action groups’ are already working to implement suitable strategies for pursuing the objectives of the Action Plan. In addition, although with a slightly different geographical definition, the Interreg Alpine Space programme has also been established to facilitate the cooperation between economic, social and environmental key players in the area; in particular, the programme has ‘innovation’ among its priorities. The results of our work can clearly support the identification of proper policies to be designed within the above organizational frameworks.

17 Patent data are from the OECD REGPAT Database (Feb. 2016 edition), cumulated from 2006 to 2011. Conversion between the technological IPC classification and the sectoral NACE classification was carried out according to the concordance table provided by the Eurostat (2014). Traditional sectors were again identified on the basis of OECD (2011).

18 In particular, this is the food, beverages and tobacco industry.

19 According to the OECD, biotechnology patents are considered those associated to the following IPC categories: A01H1/00, A01H4/00, A61K38/00, A61K39/00, A61K48/00, C02F3/34, C07G(11/00, 13/00, 15/00), C07K(4/00, 14/00, 16/00, 17/00, 19/00), C12M, C12N, C12P, C12Q, C12S, G01N27/327, G01N33/(53, 54, 55, 57, 68, 74, 76, 78, 88, 92).

20 European Commission, COM(2013) 468 final.

Additional information

Funding

This work is partially based on a research project carried out by the authors for the Directorate General for Regional Policy under Expert Contract no. [2017CE160AT118] on a first version of this study is gratefully acknowledged.