An Uncertainty Thermometer to Measure the Macroeconomic-Financial Risk in South American Countries
Corresponding Author
Marcela Guachamín
Polytechnic National University, Quito, Ecuador and Univ. Lyon, UJM Saint-Etienne, CNRS, GATE L-SE UMR 5824, Saint-Etienne, France
Correspondence to: Marcela Guachamin, Polytechnic National University, Quito, Ecuador and Univ. Lyon, UJM Saint-Etienne, CNRS, GATE L-SE UMR 5824, Saint-Etienne, France.
E-mail: marcela.guachamin@univ-st-etienne.fr;marcela.guachamin@epn.edu.ec
Search for more papers by this authorDiana Ramírez-Cifuentes
Communication and Information Technologies Department, Universitat Pompeu Fabra, Barcelona, Spain
Search for more papers by this authorCorresponding Author
Marcela Guachamín
Polytechnic National University, Quito, Ecuador and Univ. Lyon, UJM Saint-Etienne, CNRS, GATE L-SE UMR 5824, Saint-Etienne, France
Correspondence to: Marcela Guachamin, Polytechnic National University, Quito, Ecuador and Univ. Lyon, UJM Saint-Etienne, CNRS, GATE L-SE UMR 5824, Saint-Etienne, France.
E-mail: marcela.guachamin@univ-st-etienne.fr;marcela.guachamin@epn.edu.ec
Search for more papers by this authorDiana Ramírez-Cifuentes
Communication and Information Technologies Department, Universitat Pompeu Fabra, Barcelona, Spain
Search for more papers by this authorAbstract
This paper aims to develop an uncertainty thermometer to identify and measure the macro-social-financial risk of 10 SA countries from 1978 to 2014. This thermometer is based on the early warning models to facilitate systemic risk monitoring. Contrary to other studies, we build a macroeconomic-social-financial vulnerability index composed of macroeconomic, social development, liquidity, solvency and market vulnerability sub-indicators through the partial least squares structural equation model. We identify high (unmanageable, intolerable and unstable) and low (manageable, moderate, stable and strong) risk levels using machine learning methods. Our results are robust and consistent, because the macroeconomic-social-financial index captures periods of high uncertainty presented in the region. © 2020 John Wiley & Sons, Ltd.
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