Reinterpreting Economic Complexity: A co-clustering approach

Economic growth results from countries' accumulation of organizational and\r\ntechnological capabilities. The Economic and Product Complexity Indices,\r\nintroduced as an attempt to measure these capabilities from a country's basket\r\nof exported products, have become popular to study economic development, the\r\ngeography of innovation, and industrial policies. Despite this reception, the\r\ninterpretation of these indicators proved difficult. Although the original\r\nMethod of Reflections suggested a direct interconnection between country and\r\nproduct metrics, it has been proved that the Economic and Product Complexity\r\nIndices result from a spectral clustering algorithm that separately groups\r\nsimilar countries or similar products, respectively. This recent approach to\r\neconomic and product complexity conflicts with the original one and treats\r\nseparately countries and products. However, building on previous\r\ninterpretations of the indices and the recent evolution in spectral clustering,\r\nwe show that these indices simultaneously identify two co-clusters of similar\r\ncountries and products. This viewpoint reconciles the spectral clustering\r\ninterpretation of the indices with the original Method of Reflections\r\ninterpretation. By proving the often neglected intimate relationship between\r\ncountry and product complexity, this approach emphasizes the role of a selected\r\nset of products in determining economic development while extending the range\r\nof applications of these indicators in economics.