The relationship between nuclear energy consumption and economic growth
Evidence from Switzerland
Bibliographic Data
| ID | 15550368 |
|---|---|
| Authors | Cosimo Magazzino (0000-0002-3176-9838, Roma Tre University, corresponding author), Marco Mele (0000-0002-1477-1071, University of Teramo, corresponding author), Nicolas Schneider (0009-0006-6190-4830, Sorbonne Université), Guillaume Vallet (0000-0002-8359-649X, Université Grenoble Alpes, corresponding author) |
| Year | 2020 |
| Volume | 15 |
| Issue | 9 |
| Pages | 0940a5-0940a5 |
| Publication date | 2020-08-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/abadcd |
| OpenAlex | W3048890906 |
| Language | EN |
| Citations received | 5 |
| References cited | 26 |
This study aims to investigate the relationship between nuclear energy consumption and economic growth in Switzerland over the period 1970–2018. We use data on capital, labour, and exports within a multivariate framework. Starting from the consideration that Switzerland has decided to phase out nuclear energy by 2034, we examine the effect of this structural economic-energy change in the country. To do so, two distinct estimation tools are performed. The first model, using a time-series approach, analyze the relationship between bivariate and multivariate causality. The second, using a Machine Learning methodology, test the results of the econometric modelling through an Artificial Neural Networks process. This last empirical procedure represents our original contribution with respect to the previous energy-GDP papers. The results, in the logarithmic propagation of neural networks, suggest a careful analysis of the process that will lead to the abandonment of nuclear energy in Switzerland to avoid adverse effects on economic growth
Bivariate analysis · Causality (physics · Consumption (sociology · Econometrics · Economics · Energy (signal processing · Energy consumption · Estimation · Granger causality · Multivariate statistics · Process (computing · Statistics · Computer Science · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth · Engineering · Environmental Impact and Sustainability · Mathematics
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| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2023 (3) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 5 |