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A new machine learning algorithm to explore the CO2 emissions-energy use-economic growth trilemma

Author

Listed:
  • Cosimo Magazzino

    (Roma Tre University)

  • Marco Mele

    (Roma Tre University)

Abstract

The aim of this study is to explore the nexus among CO2 emissions, energy use, and GDP in Russia using annual data ranging from 1970 to 2017. We first conduct time-series analyses (stationarity, structural breaks, and cointegration tests). Then, we present a new D2C algorithm, and we run a Machine Learning experiment. Comparing the results of the two approaches, we conclude that economic growth causes energy use and CO2 emissions. However, the critical analysis underlines how the variance decomposition justifies the qualitative approach of using economic growth to immediately implement expenses for the use of alternative energies able to reduce polluting emissions. Finally, robustness checks to validate the results through a new D2C algorithm are performed. In essence, we demonstrate the existence of causal links in sub-permanent states among these variables.

Suggested Citation

  • Cosimo Magazzino & Marco Mele, 2025. "A new machine learning algorithm to explore the CO2 emissions-energy use-economic growth trilemma," Annals of Operations Research, Springer, vol. 345(2), pages 665-683, February.
    • Handle: RePEc:spr:annopr:v:345:y:2025:i:2:d:10.1007_s10479-022-04787-0
    DOI: 10.1007/s10479-022-04787-0
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    More about this item

    Keywords

    CO2 emissions; Energy use; Economic growth; Machine learning; D2C algorithm; Time-series; Russia;
    All these keywords.

    JEL classification:

    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • N55 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - Asia including Middle East
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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