This paper examines the relationship between renewable energy consumption and economic growth in Brazil, in the Covid-19 pandemic. Using an Artificial Neural Networks (ANNs) experiment in Machine Learning, we tried to verify if a more intensive use of renewable energy could generate a positive GDP acceleration in Brazil. This acceleration could offset the harmful effects of the Covid-19 global pandemic. Empirical findings show that an ever-greater use of renewable energies may sustain the economic growth process. In fact, through a model of ANNs, we highlighted how an increasing consumption of renewable energies triggers an acceleration of the GDP compared to other energy variables considered in the model.

Magazzino, C., Mele, M., & Morelli, G. (2021). The relationship between renewable energy and economic growth in a time of Covid-19: A Machine Learning experiment on the Brazilian economy. SUSTAINABILITY, 13(3) [10.3390/su13031285].

The relationship between renewable energy and economic growth in a time of Covid-19: A Machine Learning experiment on the Brazilian economy

Magazzino, Cosimo
;
Mele, Marco;Morelli, Giovanna
2021

Abstract

This paper examines the relationship between renewable energy consumption and economic growth in Brazil, in the Covid-19 pandemic. Using an Artificial Neural Networks (ANNs) experiment in Machine Learning, we tried to verify if a more intensive use of renewable energy could generate a positive GDP acceleration in Brazil. This acceleration could offset the harmful effects of the Covid-19 global pandemic. Empirical findings show that an ever-greater use of renewable energies may sustain the economic growth process. In fact, through a model of ANNs, we highlighted how an increasing consumption of renewable energies triggers an acceleration of the GDP compared to other energy variables considered in the model.
Magazzino, C., Mele, M., & Morelli, G. (2021). The relationship between renewable energy and economic growth in a time of Covid-19: A Machine Learning experiment on the Brazilian economy. SUSTAINABILITY, 13(3) [10.3390/su13031285].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/378338
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