Revisiting the dynamic interactions between economic growth and environmental pollution in Italy: evidence from a gradient descent algorithm
| Autor: | Nicolas Schneider, Floriana Nicolai, Cosimo Magazzino, Marco Mele |
|---|---|
| Přispěvatelé: | Mele, Marco, Magazzino, Cosimo, Schneider, Nicola, Nicolai, Floriana |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Q43
020209 energy Health Toxicology and Mutagenesis Environmental pollution 02 engineering and technology 010501 environmental sciences CO2 emissions 01 natural sciences Outcome (game theory) Machine learning 0202 electrical engineering electronic engineering information engineering Econometrics Environmental Chemistry Environmental policy C32 Economic growth 0105 earth and related environmental sciences Mathematics N55 General Medicine Carbon Dioxide economic growth Pollution Stochastic gradient descent Italy Multilayer perceptron Economic Development environmental pollution Gradient descent Environmental Pollution Nexus (standard) B22 Algorithms gradient descent algorithm Research Article |
| Zdroj: | Environmental Science and Pollution Research International |
| ISSN: | 1614-7499 0944-1344 |
| Popis: | Although the literature on the relationship between economic growth and CO2 emissions is extensive, the use of machine learning (ML) tools remains seminal. In this paper, we assess this nexus for Italy using innovative algorithms, with yearly data for the 1960–2017 period. We develop three distinct models: the batch gradient descent (BGD), the stochastic gradient descent (SGD), and the multilayer perceptron (MLP). Despite the phase of low Italian economic growth, results reveal that CO2 emissions increased in the predicting model. Compared to the observed statistical data, the algorithm shows a correlation between low growth and higher CO2 increase, which contradicts the main strand of literature. Based on this outcome, adequate policy recommendations are provided. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-14264-z. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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