A New Interpretation of the Economic Complexity Index
36 Pages Posted: 27 Nov 2017 Last revised: 21 Sep 2018
Date Written: February 4, 2018
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. We show that the ECI is, in fact, equivalent to a spectral clustering algorithm, which partitions a similarity graph into two parts. When applied to country-export data, the ECI represents a ranking of countries that places countries with similar exports close together in the ordering. More generally, the ECI is a dimension reduction tool, which gives the optimal one-dimensional ordering that minimizes the distance between nodes in a similarity graph. We discuss this new interpretation of the ECI with reference to the economic development literature. Finally, we illustrate stark differences between the ECI and diversity with two empirical examples based on regional data.
Keywords: Economic Complexity, Spectral Clustering, Economic Development, Networks
JEL Classification: C60, C80, O14, O57, F47
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