# 18.14 Why do industries coagglomerate? How Marshallian externalities differ by industry and have evolved over time

Dario Diodato and Frank Neffke and Neave O’Clery

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Abstract: The fact that firms benefit from close proximity to other firms with which they can exchange inputs, skilled labor or know-how helps explain why many industrial clusters are so successful. Studying the evolution of coagglomeration patterns, we show that which type of agglomeration benefits firms has drastically changed over the course of a century and divers markedly across industries. Whereas, at the beginning of the twentieth century, industries tended to colocate with their value chain partners, in more recent decades the importance of this channels has declined and colocation seems to be driven more by similarities industries’ skill requirements. By calculating industry-specific Marshallian agglomeration forces, we are able to show that, nowadays, skill-sharing is the most salient motive in location choices of services, whereas value chain linkages still explain much of the colocation patterns in manufacturing. Moreover, the estimated degrees to which labor and input-output linkages are reflected in an industry’s coagglomeration patterns help improve predictions of city-industry employment growth.

# 16.26 Agglomeration economies: the heterogeneous contribution of human capital and value chains

Dario Diodato, Frank Neffke, Neave O’Clery

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We document the heterogeneity across sectors in the impact labor and input-output links have on industry agglomeration. Exploiting the available degrees of freedom in coagglomeration patterns, we estimate the industry-specific benefits of sharing labor needs and supply links with local firms. On aggregate, coagglomeration patterns of services are at least as strongly driven by input-output linkages as those of manufacturing, whereas labor linkages are much more potent drivers of coagglomeration in services than in manufacturing. Moreover, the degree to which labor and input-output linkages are reflected in an industry’s coagglomeration patterns is relevant for predicting patterns of city-industry employment growth.