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The relationship between nuclear energy consumption and economic growth: evidence from Switzerland

Author

Listed:
  • Cosimo Magazzino

    (ROMA TRE - Università degli Studi Roma Tre = Roma Tre University)

  • Marco Mele

    (UniTE - Università degli Studi di Teramo)

  • Nicolas Schneider
  • Guillaume Vallet

    (CREG - Centre de recherche en économie de Grenoble - UGA - Université Grenoble Alpes)

Abstract

This study aims to investigate the relationship between nuclear energy consumption and economicgrowth in Switzerland over the period 1970–2018. We use data on capital, labour, and exportswithin a multivariate framework. Starting from the consideration that Switzerland has decided tophase out nuclear energy by 2034, we examine the effect of this structural economic-energy changein the country. To do so, two distinct estimation tools are performed. The first model, using atime-series approach, analyze the relationship between bivariate and multivariate causality. Thesecond, using a Machine Learning methodology, test the results of the econometric modellingthrough an Artificial Neural Networks process. This last empirical procedure represents ouroriginal contribution with respect to the previous energy-GDP papers. The results, in thelogarithmic propagation of neural networks, suggest a careful analysis of the process that will leadto the abandonment of nuclear energy in Switzerland to avoid adverse effects on economic growth.

Suggested Citation

  • Cosimo Magazzino & Marco Mele & Nicolas Schneider & Guillaume Vallet, 2020. "The relationship between nuclear energy consumption and economic growth: evidence from Switzerland," Post-Print halshs-02951860, HAL.
    • Handle: RePEc:hal:journl:halshs-02951860
    DOI: 10.1088/1748-9326/abadcd
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02951860
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    Citations

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    Cited by:

    1. Cosimo Magazzino & Marco Mele & Fabio Gaetano Santeramo, 2021. "Using an Artificial Neural Networks Experiment to Assess the Links among Financial Development and Growth in Agriculture," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    2. Magazzino, Cosimo & Drago, Carlo & Schneider, Nicolas, 2023. "Evidence of supply security and sustainability challenges in Nigeria’s power sector," Utilities Policy, Elsevier, vol. 82(C).
    3. Marco Mele & Cosimo Magazzino & Nicolas Schneider & Antonia Rosa Gurrieri & Hêriş Golpira, 2022. "Innovation, income, and waste disposal operations in Korea: evidence from a spectral granger causality analysis and artificial neural networks experiments," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 39(2), pages 427-459, July.
    4. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2021. "A D2C algorithm on the natural gas consumption and economic growth: Challenges faced by Germany and Japan," Energy, Elsevier, vol. 219(C).
    5. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2021. "A machine learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO2 emissions," Renewable Energy, Elsevier, vol. 167(C), pages 99-115.
    6. Magazzino, Cosimo & Mele, Marco & Morelli, Giovanna & Schneider, Nicolas, 2021. "The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries," Utilities Policy, Elsevier, vol. 72(C).
    7. Tomiwa Sunday Adebayo & Festus Victor Bekun & Ilhan Ozturk & Murat Ismet Haseki, 2023. "Another outlook into energy‐growth nexus in Mexico for sustainable development: Accounting for the combined impact of urbanization and trade openness," Natural Resources Forum, Blackwell Publishing, vol. 47(2), pages 334-352, May.
    8. Opeoluwa Seun Ojekemi & Mehmet Ağa & Cosimo Magazzino, 2023. "Towards Achieving Sustainability in the BRICS Economies: The Role of Renewable Energy Consumption and Economic Risk," Energies, MDPI, vol. 16(14), pages 1-18, July.
    9. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2022. "A new artificial neural networks algorithm to analyze the nexus among logistics performance, energy demand, and environmental degradation," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 315-328.
    10. Soytas, Ugur & Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2022. "Economic and environmental implications of the nuclear power phase-out in Belgium: Insights from time-series models and a partial differential equations algorithm," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 241-256.
    11. Cosimo Magazzino & Marco Mele & Giovanna Morelli, 2021. "The Relationship between Renewable Energy and Economic Growth in a Time of Covid-19: A Machine Learning Experiment on the Brazilian Economy," Sustainability, MDPI, vol. 13(3), pages 1-22, January.
    12. Abdul Rehman & Hengyun Ma & Magdalena Radulescu & Crenguta Ileana Sinisi & Loredana Maria Paunescu & MD Shabbir Alam & Rafael Alvarado, 2021. "The Energy Mix Dilemma and Environmental Sustainability: Interaction among Greenhouse Gas Emissions, Nuclear Energy, Urban Agglomeration, and Economic Growth," Energies, MDPI, vol. 14(22), pages 1-21, November.
    13. Abbasi, Kashif Raza & Shahbaz, Muhammad & Jiao, Zhilun & Tufail, Muhammad, 2021. "How energy consumption, industrial growth, urbanization, and CO2 emissions affect economic growth in Pakistan? A novel dynamic ARDL simulations approach," Energy, Elsevier, vol. 221(C).
    14. Magazzino, Cosimo & Alola, Andrew Adewale & Schneider, Nicolas, 2021. "The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: a quantile regression evidence," LSE Research Online Documents on Economics 117654, London School of Economics and Political Science, LSE Library.

    More about this item

    Keywords

    nuclear energy consumption; GDP; employment; capital stock; time-series; artificial neural networks;
    All these keywords.

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