How Do Regions Diversify over Time? Industry Relatedness and the Development of New Growth Paths in Regions

Abstract

The question of how new regional growth paths emerge has been raised by many leading economic geographers. From an evolutionary perspective, there are strong reasons to believe that regions are most likely to branch into industries that are technologically related to the preexisting industries in the regions. Using a new indicator of technological relatedness between manufacturing industries, we analyzed the economic evolution of 70 Swedish regions from 1969 to 2002 with detailed plant‐level data. Our analyses show that the long‐term evolution of the economic landscape in Sweden is subject to strong path dependencies. Industries that were technologically related to the preexisting industries in a region had a higher probability of entering that region than did industries that were technologically unrelated to the region's preexisting industries. These industries had a higher probability of exiting that region. Moreover, the industrial profiles of Swedish regions showed a high degree of technological cohesion. Despite substantial structural change, this cohesion was persistent over time. Our methodology also proved useful when we focused on the economic evolution of one particular region. Our analysis indicates that the Linköping region increased its industrial cohesion over 30 years because of the entry of industries that were closely related to its regional portfolio and the exit of industries that were technologically peripheral. In summary, we found systematic evidence that the rise and fall of industries is strongly conditioned by industrial relatedness at the regional level.

On firms’ product space evolution: the role of firm and local product relatedness

“…On the one hand, regional competencies matter for firm innovation when they are cognitively close to the new products. We, thus, corroborate previous evidence which discloses the positive role of existing local diversification in technologically related sectors on the economic performance of regions and firms Neffke et al, 2011;Boschma et al, 2012Boschma et al, , 2013. On the other hand, a large existing local production scale is not a necessary condition to develop new products in a region.…”

“…This hints at important complementarities between geographical and cognitive proximity in the spur of knowledge, although the work shows that regional capabilities favour the maintenance rather than the development of comparative advantages. Neffke et al (2011) analyse the economic evolution of 70 Swedish regions during the period 1969-2002 and find strong path dependence in their diversification process. Their results confirm that technological relatedness-measured by a Revealed Relatedness indicator based on the ratio between industries' co-occurrences in regions' industrial structures and their predicted value-is important in rising regions' technological cohesion.…”

“…A recent body of literature has highlighted the role of technological relatedness for starting a new sector in a country (Hausmann and Hidalgo, 2009;Hidalgo, 2009), a region (Boschma and Iammarino, 2009;Neffke et al, 2011;Boschma et al, 2012Boschma et al, , 2013 or a firm (Breschi et al, 2003;Poncet and de Waldemar, 2012;Neffke and Henning, 2013). In particular, empirical work in economic geography has shown that knowledge spillovers can spur innovation and growth across economic units located in space, as long as the right-not too little, not too much (Nooteboom, 2000;Boschma, 2005)-extent of cognitive proximity exists among the relevant economic actors.…”

Regional economic development in Europe: the role of total factor productivity

“…The analysis could be further extended to the sectoral level and could also be used to make comparisons over time. Future research could also compare TFP levels with more disaggregate regional characteristics such as regional diversity (Frenken, van Oort, & Verburg, 2007), spatial diversification patterns (Neffke, Henning, & Boschma, 2011), and workforce mobility patterns and information on their spatial networks (Huber, 2012). Moreover, one could further explore how the spatial dimension of technology diffusion may differ depending on the innovation being embodied (i.e., new products and or services) or disembodied (i.e., superior measurement practices), and how the rents extracted from these types of innovation may have different spatial implications (Rodríguez-Pose & Crescenzi, 2008;Keller, 2004).…”

The Spatial Patterns of Dairy Farming In Molise

“…The uneven distribution of milk production can also be explained by other positive spatial agglomeration externalities, which are benefits that firms derive from being located close to other economic actors (Neffke et al, 2011). It is customary to distinguish between localisation and urbanisation economies (Glaeser et 8 Using a well-known categorisation that can be traced back to the work of Marshall, location economies may derive from within-sector pecuniary (static) and non-pecuniary (dynamic) externalities.…”