Regional competitiveness is as much debated by politicians and policy makers as it is doubted by academics. For politicians and policy makers, it offers a fairly fuzzy umbrella concept that covers aspects that matter to the firms and residents of a region. It tends to focus on measurable differences between regions which fall (partly) under the control of public authorities, without employing any clear political or conceptual framework.
Despite accusations that regional competitiveness is embedded in a neo-liberal ideology (Bristow 2010), the concept, as adopted in the present work, neither assumes nor supports a minimal state. On the contrary, this new Index, as with most other measures of
competitiveness, gives the Nordic regions some of the highest scores despite having
economies in which the public sector accounts for some of the highest shares of GDP in the world.
We adopt a simple definition of regional competitiveness which responds pragmatically to current issues raised in the literature and allows us to consider how these issues can guide indicator selection.
2.1. The concept and definition
A broad notion of competitiveness refers to the inclination and skills to compete, to win and retain a position in the market, to increase market share and profitability, and eventually to consolidate commercially successful activities (Filó, 2007). The World Economic Forum (WEF) produces one of the best known competitiveness indices – the Global
Competitiveness Index (GCI). The Forum defines national competitiveness as the 'set of institutions, policies and factors that determine the level of productivity of a country' (Schwab and Sala-I-Martin, 2012; Schwab and Porter, 2007). The WEF definition links micro- (firm-level) to macro- (country-level) competitiveness. The framework describing a firm’s capacity to compete, grow and be profitable (Martin et al., 2006) is relatively
uncontested, but applying the same concept to countries or regions has been subject to much debate. The implicit analogy between firms and nations has been widely criticised because a country cannot go out of business and because competition between countries can
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benefit both, while competition between companies in the same sector is more likely to be a zero sum game (Krugman, 1996).
Between the micro and the macro levels stands the concept of regional competitiveness. A region is neither a simple aggregation of firms nor a scaled version of nations (Gardiner et al., 2004). Meyer-Stamer (2008) states that: ‘We can define (systemic) competitiveness of a territory as the ability of a locality or region to generate high and rising incomes and improve the livelihoods of the people living there.’ In contrast to the WEF definition focussed on the concept of productivity, this definition is based entirely on the benefits to people living in a region. It assumes a close link between competitiveness and prosperity. It characterises competitive regions not only by using output-related terms such as productivity but also by determining the sustained or improved level of comparative prosperity (Bristow, 2005).
Along the same lines we propose a definition of regional competitiveness which integrates the perspective of both firm and of residents (Dijkstra et al., 2011):
Regional competitiveness can be defined as the ability to offer an attractive and sustainable environment for firms and residents to live and work.
Sustainable in this definition is not used in the purely ecological-environmental sense, but in the sense of a region’s capacity to provide an attractive environment in both the short- and long-term. This means that a region which reduces taxes to such a degree that it can no longer maintain the quality of its public infrastructure and services does not provide a sustainable, attractive environment.
These definitions cover issues which benefit both firms and residents, such as good
institutions, and issues where their interests may conflict, such as wages. We strive to balance the most important aspects of an attractive environment by combining the goals of
commercial success with personal well-being.
One important difference compared to the Meyer-Stamer definition is that our working definition refers to a point in time and not to changes over time. Likewise, all the indicators included in the Index refer to the situation at one point in time and not to changes over time.
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2.2. What regional level: Functional economic or Political regions?
The literature raises two issues related to the selection of the appropriate regional level. First, competitiveness should be calculated for functional economic regions. The second is that the region should have an important political and administrative role. In most countries, however, functional regions are not administrative and vice-versa. Thus in practice, these two recommendations can be rarely combined.
The RCI index focuses on NUTS 2 regions in the European Union. NUTS 2 regions are administrative or statistical regions which do not take into account functional economic links.
For example, London and Paris are both cities of approximately the same size (7.7 and 6.7 million respectively). Paris is included in the NUTS 2 region of Ile de France with 12 million inhabitants. This has the benefit that it includes the commuter belt around Paris. Greater London, on the contrary, is spilt into two NUTS 2 regions: Inner London (3 million) and Outer London (4.7 million) although both fall under the same mayor. In addition, these two NUTS 2 regions do not cover the commuter belt around London. This problem arises for a number of cities: London, Brussels, Prague, Berlin, Amsterdam and Vienna.
What are the consequences of not merging regions which have strong functional economic links?
• It does not take into account the qualifications of the people working in the city but living in a neighbouring region. Educational attainment is measured where people live, not where they work. For example, the educational attainment rates of Brabant Wallon and Vlaams-Brabant are much higher than that of Brussels. Half of the people working in Brussels live outside the city.
• It distorts GDP per head. Comparing GDP per head or per person employed for Inner London with the one for Ile de France is not meaningful. Inner London concentrates the financial industry and has a GDP per head of 328 (EU=100), while Ile de France has a GDP of 180. But Greater London has a GDP per head of 187. This distortion is due to commuting patterns (people who work there, but not live there contribute to GDP but not the population) and the concentration of certain industries.
The effect of commuting can be avoided by measuring GDP per person employed, but this will still not solve the problem of the concentration of a small part of the urban economy in
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one place. For example: GDP per person employed of Inner London is 305 (EU=100), while Ile de France is 160. In Greater London it is 176.
How was this problem solved? We used the new OECD-EC definition of a city and its commuting zone. In this definition, cities are identified by the presence of a high-density cluster or urban centre with a population of at least 50 000 inhabitants. This high-density cluster or urban centre is defined using a population grid with cells of 1 sq km. Once the cities have been defined, the commuting patterns are analysed. A commuting zone of a city consists of all contiguous municipalities that send 15% or more of their working residents to the city. Municipalities that fall below this threshold but are surrounded by municipalities that are above this threshold are also included. This avoids having commuting zones with internal "holes".
How are the NUTS 2 regions selected to merge? If a region has at least 40% of its
population inside the commuting zone, it is added to the region which contained the city.
This criterion is applied to all NUTS 2 regions, but only a few NUTS 2 regions with the capital had neighbouring regions with a high-share of its population in the commuting zone of the capital.
This approach is a novelty with respect to the 2010 edition of the index. Compared to the 2010 version, more capital regions are merged with one or more of their neighbouring regions: Wien (AT), Brussels (BE), Praha (CZ), Berlin (DE), Amsterdam (NL) and London (UK), see Table 2. The remaining NUTS 2 regions may contain multiple functional urban areas, but they do break up a single functional urban area in to distinct parts.
Do all the regions in the RCI 2013 have an important political role?
Many regions used in the RCI do not have an important political role. The level of
decentralization is quite varied within Europe and in Central and Eastern Member States in particular, centralization is still quite high. The goal of the competitiveness index, however, is not to follow the geography of decision-making. This would mean that in a highly
centralized country, the RCI had to be national. The goal is to measure spatial variations in issues that influence the attractiveness for firms and residents.
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1.3. Factors of competitiveness and the reach of public policies
Theories about economic growth or competitiveness consider issues or assets which fall outside the scope of public policies, or which can hardly be affected by public intervention, for example, the land area of a country, the presence of natural resources such as oil or gas, the presence of a port or a large city or the (meteorological) climate. Although in a global perspective these features may go some way to accounting for GDP levels per head or GDP growth, this paper does not include such indicators in the Regional Competitiveness Index.
As the economies in the EU are all moderately to highly developed, this study follows the recommendation of Combes (2008) to put aside most natural differences between regions such as raw materials, geographical specificities or climate – i.e. what Cronon (1991) calls
‘first nature’. The Index targets Cronon's ‘second nature’, which is the result of human actions, modifications and improvements.
Nevertheless, some indicators will still be influenced by geography, topography and population density. For example, the indicators on access to flights, potential road
accessibility or potential GDP will all be influenced by an island location, mountain ranges or the presence of large cities. While islands, mountains and cities are fairly permanent features of a region, this analysis did not want to assume that they would automatically influence competitiveness. All three examples above are also influenced by the quality of the road network, the demand for flights and changes in productivity. These influences do change over time and are sensitive to public policies.
To summarise, this work does not claim the death of distance or that geography does not matter, but it only considers the impact of distance or geography to the extent that it
changes a number of features which are important location factors for firms and enterprises.
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