David L. Rigby

Regional resilience is high on the scientific and policy agenda. An essential feature of resilience is diversifying into new activities but little is known about whether major economic crises accelerate or decelerate regional diversification. This article shows how crises impact the development of new technological capabilities within U.S. metropolitan areas by examining three of the largest downturns in U.S. history, the Long Depression (1873–1879), the Great Depression (1929–1934) and the 1970s recession (1973–1975). We find that crises (i) reduce the pace of diversification in cities and (ii) narrow the scope of diversification to more closely related activities. This pattern seems general as it also holds for smaller, local crises. Evidence is presented that this general pattern of technological diversification strongly hampers employment growth. Additionally, we find that diverse cities generally diversify more strongly during times of crisis.

Research on geographies of knowledge sourcing examines the organizational structure of innovation activities within the firm, the mechanisms by which knowledge is extracted from various external sources and the geography of these different activities. We augment this literature by exploring knowledge sourcing within multi-plant firms operating in Europe. Analysis makes use of linked patent-firm data recording the location of knowledge production and its ownership. The results add value to existing research in three ways. First, the establishments of multi-plant firms are shown to produce different kinds of knowledge in different locations. Second, the patents generated within a firm's establishments are linked to the knowledge stocks of the regions where they operate, supporting a vision of geographical knowledge sourcing. Third, the complexity of knowledge produced within firms is positively related to the number of plants in which they innovate.

Innovation is generally regarded as critical to long-run economic growth. Recent work, at different spatial scales, suggests economies that develop more complex technologies that are related to their existing knowledge stocks enjoy a growth premium. Thus, “smarter” forms of innovation may accelerate growth. These claims are examined using Chinese patent data distributed across 286 cities over the period 1991–2015. Fixed-effects panel models report that city-level GDP growth in China has a significant and positive relationship with diversification into more related and complex technologies, after controlling for the overall pace of innovation and other covariates. Robustness checks focusing on spatial autocorrelation and endogeneity affirm the core findings.

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.

Smart Specialisation was conceived as a ‘bottom-up’ framework to identify new growth paths connected to knowledge cores within regions. Although operationalization of Smart Specialisation has proven difficult, recent mappings of technologies in terms of technological relatedness and complexity suggest a useful cost–benefit framework. We extend these ideas, locating European Union cities in a Smart Specialisation space and tracking their development of technology since 1980. Results indicate that European Union cities with the largest gains in complex and related technologies enjoy an economic performance premium over cities with smaller gains in the complexity and relatedness of their knowledge bases.

Where do businesses source the capabilities that influence their diversification? From the resource-based perspective, capabilities are located within the firm. For many economic geographers, capabilities are place-based and flow between firms in local areas. Others claim the capabilities that count emerge from non-local collaboration. The value added of this paper is a firm–establishment–patent dataset that helps identify the sources of capabilities regulating technological diversification in the establishments of multi-locational firms. Results show that capabilities located within establishments themselves are most important to the process of diversification, followed by firm capabilities and then place-based capabilities.

Related diversification has generated interest in policy (Smart Specialisation) and academic (regional branching) circles, linking path creation to regional capabilities and performance. We develop measures of occupational relatedness and complexity for local labour market areas in Sweden over the period 2002–12 to examine whether these constructs are helpful in explaining spatial and temporal variations in employment growth. The results indicate that increases in occupational relatedness are positively related to employment growth, while changes in occupational complexity have no significant impact. Separating the results either side of the global financial crisis shows that the influence of relatedness on employment is stronger pre-2008, while after the crisis building specialization in more complex occupations was positively associated with employment growth.

Do capabilities reside in firms, in regions, or in both? Within economic geography, most contemporary research on diversification examines how local structures condition regional development possibilities. The underlying logic is that capabilities are generated within regions and sometimes shared between them. We challenge that logic, exploring whether capabilities are more likely to emerge within the firm and to flow across spatial boundaries than they are to be built within the region flowing across firm boundaries. Analysis focuses on technological diversification within the establishments of multilocational firms operating across Chinese cities. Overall, the results demonstrate that the knowledge structure of firms is more important than the knowledge structure of cities in shaping diversification within establishments. We show that rates of technological diversification vary according to plant status (headquarters or not), location (core or peripheral city), and on whether plants are introducing more or less complex knowledge. The influence of plant, firm, and regional characteristics on diversification vary markedly across the analytical samples examined.

Human activities, such as research, innovation and industry, concentrate disproportionately in large cities. The ten most innovative cities in the United States account for 23% of the national population, but for 48% of its patents and 33% of its gross domestic product. But why has human activity become increasingly concentrated? Here we use data on scientific papers, patents, employment and gross domestic product, for 353 metropolitan areas in the United States, to show that the spatial concentration of productive activities increases with their complexity. Complex economic activities, such as biotechnology, neurobiology and semiconductors, concentrate disproportionately in a few large cities compared to less--complex activities, such as apparel or paper manufacturing. We use multiple proxies to measure the complexity of activities, finding that complexity explains from 40% to 80% of the variance in urban concentration of occupations, industries, scientific fields and technologies. Using historical patent data, we show that the spatial concentration of cutting-edge technologies has increased since 1850, suggesting a reinforcing cycle between the increase in the complexity of activities and urbanization. These findings suggest that the growth of spatial inequality may be connected to the increasing complexity of the economy.