Analysis of properties of the global trade network has generated new insights into the patterns of economic development across countries. The Economic Complexity Index (ECI), in particular, has been successful at explaining cross-country differences in GDP/capita and economic growth. The ECI aims to infer information about countries productive capabilities by making relative comparisons across countries’ export baskets. However, there has been some confusion about how the ECI works: previous studies compared the ECI to the number of exports that a country has revealed comparative advantage in (‘diversity’) and to eigenvector centrality. This paper shows that the ECI is, in fact, equivalent to a spectral clustering algorithm, which partitions a similarity graph into two parts.
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