  Intra-firm trade describes the trade between affiliated firms and is
increasingly important as global production is fragmented. However, statistics
and data on global intra-firm trade patterns are widely unavailable. This study
proposes a novel multilevel approach combining firm and country level data to
construct a set of country intra-firm trade networks for various segments of
the automotive production chain. A multilevel network is constructed with a
network of international trade at the macro level, a firm ownership network at
the micro level and a firm-country affiliation network linking the two, at the
meso level. A motif detection approach is used to filter these networks to
extract potential intra-firm trade ties between countries, where the motif (or
substructure) is two countries linked by trade, each affiliated with a firm,
and these two firms linked by ownership. The motif detection is used to extract
potential country level intra-firm trade ties. An Exponential Random Graph
Model (ERGM) is applied to the country level intra-firm trade networks, one for
each segment of the automotive production chain, to inform on the determinants
of intra-firm trade at the country level.
