Unravelling the forces underlying urban industrial agglomeration

TL;DR

This paper introduces a network-based method using community detection to analyze and quantify the different Marshallian forces driving urban industrial clustering, providing insights into industry co-agglomeration patterns.

Contribution

It presents a novel hierarchical, network-based approach to disentangle and measure the relative importance of Marshallian channels in industry co-agglomeration.

Findings

Industry clusters show distinct reliance on specific Marshallian channels.

The method effectively decomposes industry co-agglomeration patterns.

Provides a new tool for urban economic analysis and policy-making.

Abstract

As early as the 1920's Marshall suggested that firms co-locate in cities to reduce the costs of moving goods, people, and ideas. These 'forces of agglomeration' have given rise, for example, to the high tech clusters of San Francisco and Boston, and the automobile cluster in Detroit. Yet, despite its importance for city planners and industrial policy-makers, until recently there has been little success in estimating the relative importance of each Marshallian channel to the location decisions of firms. Here we explore a burgeoning literature that aims to exploit the co-location patterns of industries in cities in order to disentangle the relationship between industry co-agglomeration and customer/supplier, labour and idea sharing. Building on previous approaches that focus on across- and between-industry estimates, we propose a network-based method to estimate the relative importance of each Marshallian channel at a meso scale. Specifically, we use a community detection technique to construct a hierarchical decomposition of the full set of industries into clusters based on co-agglomeration patterns, and show that these industry clusters exhibit distinct patterns in terms of their relative reliance on individual Marshallian channels.