The Relationship between Renewable Energy and Economic Growth in a Time of Covid-19: A Machine Learning Experiment on the Brazilian Economy

Cosimo Magazzino (), Marco Mele and Giovanna Morelli
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Marco Mele: Department of Political Sciences, Roma Tre University, 00145 Rome, Italy
Giovanna Morelli: Faculty of Political Sciences, University of Teramo, 64100 Teramo, Italy

Sustainability, 2021, vol. 13, issue 3, 1-22

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.

Keywords: renewable energy; economic growth; Covid-19; Artificial Neural Networks; Brazil (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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