  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.
