Matrix Completion of World Trade

@article{Gnecco2021MatrixCO,
  title={Matrix Completion of World Trade},
  author={Giorgio Gnecco and Federico Nutarelli and Massimo Riccaboni},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.03930}
}
This work applies Matrix Completion (MC) – a class of machine-learning methods commonly used in the context of recommendation systems – to analyze economic complexity. MC is applied to reconstruct the Revealed Comparative Advantage (RCA) matrix, whose elements express the relative advantage of countries in given classes of products, as evidenced by yearly trade flows. A high-accuracy binary classifier is derived from the MC application, with the aim of discriminating between elements of the… Expand

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