Mapping industrial patterns and structural change in exports

Charlotte Guillard

#2020-005

This paper proposes a new methodology for identifying patterns in the organisation of industries and their evolution over time, based on the temporal network structure of the product space. To do this, I apply a community detection algorithm on 5-year snapshots of the product space from 1975 to 2000. This exercise enables us to identify different clusters of related products and to follow their evolution over time. I find that the product space is highly modular, that is it contains well delimited clusters of products. The community structure and its evolution show that the factors explaining industrial patterns and structural change are more complex than the traditional divide between low, medium and high-tech industries. Several common drivers can be identified to explain the emergence and evolution of different communities including the experience in a technological domain, factor abundance, scale economies as well as global value chains and vertical integration. Moreover, I find that technological domains and boundaries between industries are not always clear-cut and can evolve over time.

Keywords: Structural change, Capabilities, Economic Complexity, Networks, Community Structure, Exports

JEL Classification: O11, O14, O33, O25, P40, E14

  


UNU-MERIT