Time-Varying Agglomeration Externalities in UK Counties between 1841 and 1971

Using dynamic panel data methods on UK counties (1841-1971), we investigate long-term employment dynamics in seven distinct local industries. We study how industries benefit from specialised environments (MAR), diverse local economies (Jacobs’) and large local markets (urbanization), and, in contrast to most other authors, test if the strength of MAR, Jacobs’ and urbanization externalities changes over time. We find declining MAR and rising Jacobs’ externalities since the mid-nineteenth century, questioning the adequacy of a static framework when studying agglomeration externalitiesagglomeration, dynamic externalities, Jacobs’ externalities, MAR externalities, urbanization externalities

Seeds of regional structural change. The role of entrepreneurs and expanding firms in shaping local path dependencies

This article studies path dependent regional structural change using a quantitative framework. Based on an inter-relatedness indicator, the degree to which local skill-bases exist and force local economies onto a path-dependent development trajectory is studied. The main question is into which local industries new plants enter, while distinguishing between the plants of entrepreneurs and firms. Using a dataset on Swedish individuals and municipalities, it is found that entrepreneurs tend to reinforce established local industrial specializations, whereas new plants of already existing firms do less so. Moreover, outside actors deepen local economy's core specialization more than do local actors.structural change, economic geography, path dependence, entrepreneurship, skill-relatedness, human capital

Inter-industry linkages in local economies

We investigate the extent to which a local industry is affected by an overrepresentation of related industries in the local economy. We focus on two types of inter-industry relatedness, namely, the degree to which two industries can employ a similarly skilled labor force and the degree to which two industries are connected in the value chain. We decompose changes in the employment of a local industry into the employment generated or destroyed in incumbent plants and the employment changes due to plant entry and exit. Furthermore, we classify new plants by the type and geographical origins of the plants’ founders. We find that entrepreneurs have a stronger tendency than existing firms to set up plants in local industries that can draw on a strong local presence of labor market and value chain linked industries. The same holds for local founders compared to founders from outside the region. In the second part of the paper, we investigate the relative importance of the two relatedness types and whether the two types reinforce each other. We find that, in general, the growth of old plants and the employment generated in new plants is more strongly associated with the relatedness through the labor market. Moreover, for in new plant formation, the two relatedness types indeed tend to reinforce each other. In fact, local value chain linkages seem to be only important if client and supplier firms can also engage in labor sharing.

Human Capital Mismatches along the Career Path

Human capital is transferable across occupations, but only to a limited extent because of differences in occupational skill-profiles. Higher skill overlap between occupations renders less of individuals' human capital useless in occupational switches. Current occupational distance measures neglect that differences in skill complexities between occupations yield skill mismatch asymmetric in nature. We propose characterizing occupational switches in terms of human capital shortages and redundancies. This results in superior predictions of individual wages and occupational switches. It also allows identifying career movements up and down an occupational complexity ladder, and assessing the usefulness of accumulated skill-profiles at an individual's current job.skill mismatch, skill transferability, occupational change, human capital, wages

Revealed Relatedness: Mapping Industry Space

In this paper we measure technological relatedness between industries using a dataset on product portfolios of plants. For this purpose we first develop a general methodology to extract data on co-occurrences of classes (e.g. industries) in a single entity (e.g. a plant) to construct estimates of the relatedness between the classes. The core assumption, in line with the concept of economies of scope, is that if two products are produced in the same plant, this is an indication of relatedness between the industries the two products are a part of. Unlike earlier methods, we arrive at a Revealed Relatedness (RR) index that can be interpreted on a ratio scale, allows for the use of indirect (i.e. not directly observed) information on industry relatedness, and conceptualizes relatedness as being asymmetric or directed. Direction of relatedness provides information on, for example, the most likely direction of spillovers between two classes. We also graph the RR matrices using methods borrowed from social network analysis. The result is a visualization of the “industry space” and how that changes over time with structural transformation of the economy. In order to test the validity of the framework, the industry space is used to plot structural transformation paths of regions. It is shown that the RR matrix indeed has significant explanatory power for the composition and change of a regions portfolio of manufacturing industries, in spite of the fact that regional information played no role in its derivation. This confirms the quality of our RR estimates.technological relatedness, industry relations, industry space, revealed relatedness

How do regions diversify over time? Industry relatedness and the development of new growth paths in regions

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 region. Employing a new indicator of technological relatedness between manufacturing industries, we analyze the economic evolution of 70 Swedish regions during the period 1969-2002 using 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 pre-existing industries in a region had a higher probability to enter the region, as compared to unrelated industries. And unrelated industries had a higher probability to exit the region. Moreover, we found that industrial profiles of Swedish regions showed a high degree of technological coherence. Despite substantial structural change, this coherence was very persistent over time. Our methodology also proved useful when focusing on the economic evolution of one particular region. Our analysis showed that the Linkˆping region increased its industrial coherence during 30 years, due to the entry of industries that were closely related to its regional portfolio on the one hand, and the exit of industries that were technologically peripheral to its regional portfolio on the other hand. In sum, we find systematic evidence that the rise and fall of industries is strongly conditioned by industrial relatedness at the regional level.technological relatedness, related variety, regional branching, regional diversification

Surviving in agglomerations: Plant evolution and the changing benefits of the local environment

Cities vary with regard to the characteristics of their economic life. A formal model by Duranton and Puga (2001) suggests a division of labour between diversified and specialized cities. Diversified cities (the “nursery cities”) provide a fertile environment for search and innovation. Specialized cities, by contrast, are better equipped to facilitate mass-production. In essence, this spurs firms to re-locate as they mature from the exploratory set-up stage to mass-production. In this article, we empirically test the assumptions behind this model by means of survival analysis using Swedish plant level data of over 11 000 plants. More specifically, we investigate the effects of local specialization and local diversity on plant survival at different ages of a plant and for different size categories of plants. Not all types of local diversity will be of value to a plant. Rather, we expect plants to benefit especially from local diversity in related industries. In a similar vein, cities with a large concentration of a broad range of activities in related trades may confer larger benefits than cities with a narrow specialization in the plant’s own industry. To quantify the degree of relatedness between industries, we use a new measure, Revealed Relatedness. This serves to identify technological relatedness by measuring economies of scope as implied by the structure of production portfolios of plants. The findings suggest that regional characteristics strongly influence the chances of a plant to survive. In general, the hypothesized specialization effects are only found when we look at related specialization. Large plants at high stages of maturity form the only exception to this. However, diversity effects are only visible when we take all local diversity into account, not just diversity in related industries. Moreover, it is only young firms that benefit from regional diversity. This indicates that the “nursery city” metaphor holds as much for small, prototype plants as for large mass-production plants.agglomeration economies, revealed relatedness, industry relations, Sweden

Revealed Relatedness: Mapping Industry Space

In this paper we measure technological relatedness between industries using a dataset on product portfolios of plants. For this purpose we first develop a general methodology to extract data on co-occurrences of classes (e.g. industries) in a single entity (e.g. a plant) to construct estimates of the relatedness between the classes. The core assumption, in line with the concept of economies of scope, is that if two products are produced in the same plant, this is an indication of relatedness between the industries the two products are a part of. Unlike earlier methods, we arrive at a Revealed Relatedness (RR) index that can be interpreted on a ratio scale, allows for the use of indirect (i.e. not directly observed) information on industry relatedness, and conceptualizes relatedness as being asymmetric or directed. Direction of relatedness provides information on, for example, the most likely direction of spillovers between two classes. We also graph the RR matrices using methods borrowed from social network analysis. The result is a visualization of the “industry space” and how that changes over time with structural transformation of the economy. In order to test the validity of the framework, the industry space is used to plot structural transformation paths of regions. It is shown that the RR matrix indeed has significant explanatory power for the composition and change of a regions portfolio of manufacturing industries, in spite of the fact that regional information played no role in its derivation. This confirms the quality of our RR estimates.

Making foreign direct investment work for innovation clusters

How do new centres of technological excellence emerge? Research and Development (R&D) activities of foreign multinationals can act as powerful boosters of local innovation and growth in the cities where they invest. However, for the most innovative multinational companies, the risk of leaking knowledge to local competitors often outweighs the benefits of learning from those same competitors, thus reducing the incentives of ‘very innovative multinationals’ to embed themselves fully into the local innovation system. Riccardo Crescenzi, Arnaud Dyèvre, and Frank Neffke write that second-tier multinationals—those outside the top 20% of innovating firms—that start R&D activities in foreign regions generate more knowledge spillovers than higher ranking multinationals and consequently, foster greater growth in local innovation