  Devising strategies for economic development in a globally competitive
landscape requires a solid and unbiased understanding of countries
technological advancements and similarities among export products. Both can be
addressed through the bipartite representation of the International Trade
Network. In the present paper, we apply the recently proposed grand canonical
projection algorithm to uncover country and product communities. Contrary to
past endeavors, our methodology, based on information theory, creates
monopartite projections in an unbiased and analytically tractable way. Single
links between countries or products represent statistically significant
signals, which are not accounted for by null-models such as the Bipartite
Configuration Model. We find stable country communities reflecting the
socioeconomic distinction in developed, newly industrialized, and developing
countries. Furthermore, we observe product clusters based on the aforementioned
country groups. Our analysis reveals the existence of a complicate structure in
the bipartite International Trade Network: apart from the diversification of
export baskets from the most basic to the most exclusive products, we observe a
statistically significant signal of an export specialization mechanism towards
more sophisticated products.
