Reinterpreting Economic Complexity: A co-clustering approach
Carlo Bottai, Jacopo Di Iorio, Martina Iori

TL;DR
This paper reinterprets the Economic and Product Complexity Indices by demonstrating they identify co-clusters of similar countries and products, reconciling spectral clustering with original interpretations and highlighting their role in economic development.
Contribution
It introduces a co-clustering perspective that unifies spectral clustering and the original method, enhancing understanding of economic complexity indicators.
Findings
Indices identify co-clusters of countries and products.
Reconciles spectral clustering with original interpretation.
Highlights the role of specific products in economic development.
Abstract
Economic growth results from countries' accumulation of organizational and technological capabilities. The Economic and Product Complexity Indices, introduced as an attempt to measure these capabilities from a country's basket of exported products, have become popular to study economic development, the geography of innovation, and industrial policies. Despite this reception, the interpretation of these indicators proved difficult. Although the original Method of Reflections suggested a direct interconnection between country and product metrics, it has been proved that the Economic and Product Complexity Indices result from a spectral clustering algorithm that separately groups similar countries or similar products, respectively. This recent approach to economic and product complexity conflicts with the original one and treats separately countries and products. However, building on…
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Taxonomy
TopicsEconomic and Technological Innovation
MethodsSparse Evolutionary Training · Spectral Clustering
