Monetary integration in South America: Elección of candidates through unsupervised machine learning

Abstract

Applying Unsupervised Machine Learning techniques to a set of nominal variables (based on the optimum currency area [OCA] theory and the Maastricht Treaty criteria) and industrial indicators (based on similar production patterns), this paper aims to identify potential candidates for a monetary integration in South America (SA). The main conclusion is that, according to the clustering of the nominal and industrial indicators, the countries in best position for a hypothetical monetary integration in SA are Chile, Colombia, and Perú (and Ecuador to a lesser extent); countries that are generally members of the same cluster. This group of economies, which belong to the Pacific Alliance, are in a better position to meet various criteria for regional monetary integration, such as nominal convergence and similar production patterns.

The fourth industrial revolution in South America: a bibliometric study with data mining tools

“…In 2019, Moreira, et al [14] employed remote sensing to estimate water balances of hydrological events in the Amazon and for dating the driest seasons. Remote sensing is also performed in optical images for the detection of peat bogs in the Ecuadorian mountains, leading to more sustainable controls [17]. Meanwhile, deep learning is used in Peru to diagnose tuberculosis by utilizing mobile technologies and a database of X-ray images, combined with the symptomatology data delivered by sick persons [15,18,19].…”