In this paper, researchers A. Patelli, L. Pietronero, and A. Zaccaria present an integrated database suitable for the investigation of the economic development of countries by using the Economic Fitness and Complexity framework.
They first implement machine learning techniques to reconstruct the export flow of services and then combine it with the export flow of the physical goods, generating a complete view of the international market, denoted by the Integrated database. Successively, they support the technical quality of the database by computing the main metrics of the Economic Fitness and Complexity framework: (i) they build a statistically validated network of economic activities, where preferred paths of development and clusters of High-Tech industries naturally emerge; (ii) they evaluate the Economic Fitness, an algorithmic assessment of the competitiveness of countries, removing the unexpected misbehavior of economies under-represented by the sole consideration of the export of the physical goods.
Read the full paper at: https://doi.org/10.1038/