The European Union spends a substantial fraction of its budget on regional policy with the goal of reducing inequality, particularly for those European regions hardest hit by unemployment and structural change. Designing regional policy, however, is not a simple matter. Regions vary widely and there is no comprehensive theoretical framework to guide policymakers toward the single policy or set of policies appropriate for each region. Differences between regions are complex, encompassing variation in physical endowments, population density, and industrial concentration, to name just a few. Consequently, it is not possible for politicians to maximise overall welfare without the risk of neglecting some regions’ needs and thereby increasing inequality. Accordingly, policy needs to be focused on developing weak regions, while interfering less with more prosperous places. By contrast, economic theory is more interested in explaining the forces that drive the development of dynamic regions. Eventually, this leads to a simple but yet important conclusion: policy implications derived from economic theory usually depend on certain assumptions and ignoring these assumptions may induce a step in the wrong direction. Investments are more productive when structural characteristics of the regional economy that determine receptiveness to different types of spillovers are considered.
Cities, regions, and industry
A body of literature on the evolution of cities finds that diversity and inter-industry knowledge spillovers – i.e., Jacobs externalities – are crucial to the development of a dynamic economy (cf. Glaeser, Kallal, Scheinkman, and Shleifer 1992; Feldman and Audretsch 1999; Henderson 2005). Jacobs externalities are rooted in Jane Jacobs’ (1969) theory that urban diversity is more conducive to the generation of new ideas and provides the variety of experience that spurs innovation. Gilles Duranton and Diego Puga (2001) contribute to the literature by defining another prototypical region – specialised industrial agglomerations. They argue that new products are developed in diversified cities, where it is possible to experiment with processes borrowed from other co-located activities. Upon discovering their ideal process, firms switch to mass production and relocate to a specialised area (i.e., industrial agglomerations) where production costs are lower. Industrial agglomerations flourish, in part, due to intra-industry knowledge spillovers (Marshall-Arrow-Romer externalities). These externalities are most likely to result from firm relations along the supply chain where shared routines and knowledge allow for productivity-enhancing (process) innovations.
The regions that fall between these two prototypical regions—diversified cities and specialised industrial agglomerations—have also attracted the attention of researchers. For example, Paul Krugman (1991) introduced a ‘core-periphery model’ in which the core consists of dynamic growth regions while periphery describes stagnating regions. Models constructed in this manner assume that peripheral regions profit from spillovers from neighbouring dynamic regions. Thus, according to this argument, it is only necessary to devise policy aimed at stimulating growth in core regions because spillovers from the cores will eventually lead to development in peripheral regions.
However, another line of literature argues for the so-called Italian industrial districts (Becattini 1979; Piore and Sable 1984). The dynamics of these regions are specific and native to the regions themselves, or in other words, endogenous, and are not rooted in or dependent on spillovers from neighbouring dynamic regions. These industrial districts comprised of small and medium-sized firms are highly specialised in one niche market (e.g., the leather processing industry in northern Italy or metal processing in southern Germany) where their market competitiveness results from mutual trust and strong social ties that support regional cooperation in the production of new knowledge.
Taking these observations as a starting point, our research devises a classification of regions based on a large variety of factors to support our theory of the lifecycle of regions (Audretsch, Falck, Feldman, and Heblich 2008). We distinguish four different phases of the regional lifecycle, dependent on its externalities in knowledge production – i.e., inter- or intra-industrial spillovers – and its method of commercialising new knowledge. The four phases of the regional lifecycle are:
- The initial entrepreneurial phase, during which Jacobs externalities and inter-industry startups prevail. This phase requires economically diverse regions, usually urban agglomerations, where a variety of R&D laboratories – either private or public – “spill” knowledge out into the air. This environment creates an atmosphere comprised of a variety of intellectual externalities just waiting to be absorbed by spinoffs or startups.
- The routinised phase, during which innovation takes place within top-performing incumbents. Once a dominant product is established, production becomes more specialised and shifts to industrial agglomerations where R&D effort becomes much more focused. Large firms produce knowledge in specialised research laboratories for their own use and accordingly there are fewer spillovers.
- A second entrepreneurial phase, which is characterised by Marshall-Arrow-Romer (MAR) externalities, leading to intra-industry startups in niche markets. An increasing routinisation eventually opens the door for niche producers providing custom-tailored sophisticated products and solutions. Here, former industry experience can uncover incremental product variations, resulting in niche markets that complement incumbents. Thus, these product niches offer entrepreneurial opportunities where intra-industry spillovers (MAR externalities) prevail. Usually, such niche producers are located in regions characterised by a closely linked structure of small and medium enterprises.
- A second routinisation phase, which is a time of structural change during which no further innovation takes place. Existing knowledge is exploited in these regions but they lack a large enough or appropriate stock of regional knowledge that could act as the basis for a new, competitive industry. Unsurprisingly, residents of this type of region have a very low propensity for starting a business. Nonetheless, former industry experience and the little MAR externalities could support at least some dynamics. However, to recover successfully and start a new lifecycle, previous industry experience needs to be broadened by combining it with the latest high-tech knowledge (e.g., former cloth producers who have a great deal of experience with textiles could combine this experience with new technology to produce high-tech textiles for the aerospace industry).
These findings have important implications for both research and regional policy. Our empirical results link region’s fortunes to their industrial structure and warrant further exploring regularities in the evolution of regional lifecycless. For practitioners, these findings reinforce the need for differentiated regional policies and suggest each region needs policy tailored to its unique characteristics and its position along the regional lifecycle. It follows that such a policy can only be designed by those intimately acquainted with the region – in other words, at the regional level by regional politicians rather than instituted top-down by supra-national institutions. Regional policymakers need to act as entrepreneurial designers of their own regional policy.
Audretsch, D., Falck, O., Feldman, M. and Heblich, S. 2008. The Lifecycle of Regions. CEPR Discussion Paper 6757.
Becattini, G. (1979). Dal Settore Industriale al Distreto Industriale. Alcune consideración sull’unitá di indagine dell economía industriale, Revista di Economia e Politica Industriale, 1, 1–8.
Duranton, G., and D. Puga (2001). Nursery Cities: Urban Diversity, Process Innovation, and the Life Cycle of Products, American Economic Review, 91, 1454–1477.
Feldman M., and D. Audretsch (1999). Innovation in Cities: Science-Based Diversity, Specialization and Localized Competition, European Economic Review, 43, 409–429.
Glaeser, E., H. Kallal, J. Scheinkman, and A. Shleifer (1992). Growth in Cities, Journal of Political Economy, 100, 1126–1152.
Henderson, J. V. (2005). Urbanization and Growth, in: Aghion, P., S. Durlauf (eds.) Handbook of Economic Growth. Amsterdam: Elsevier, 1543–1591.
Jacobs, J. (1969). The Economy of Cities. New York: Random House.
Krugman, P. (1991). Geography and Trade. Cambridge, MA: MIT Press.
Piore, M., and C. Sabel (1984). The Second Industrial Divide. Possibilities for Prosperity. New York: Basic Books Inc.