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Assessing carbon dioxide emission reduction potential using a cost approach

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  • Ayouba, Kassoum
  • Boussemart, Jean-Philippe
  • Parvulescu, Raluca

Abstract

Departing from traditional approaches that treat carbon dioxide (CO2) emissions as a bad output, therefore relying on the weak disposability assumption, this paper considers CO2 emissions as a cost to minimise, thus preserving the materials balance condition. In particular, we extend the pollution cost approach (Coelli et al., 2007) by evaluating peer countries on their carbon intensity per total energy consumption, in addition to their energy use. The proposed methodology is then applied to estimate the extent to which a selection of 33 OECD and BRICS countries can reduce their CO2 emissions, given their gross domestic products and populations over the 2001–2019 period. Our results indicate that the period mean reduction potential for CO2 emissions of 60 % (i.e. an efficiency level of 40 %) can be decomposed into a 33 % reduction in energy intensity and a 40 % decrease in the carbon intensity of energy (i.e. efficiencies of 67 % and 60 %, respectively).

Suggested Citation

  • Ayouba, Kassoum & Boussemart, Jean-Philippe & Parvulescu, Raluca, 2026. "Assessing carbon dioxide emission reduction potential using a cost approach," European Journal of Operational Research, Elsevier, vol. 331(2), pages 629-644.
  • Handle: RePEc:eee:ejores:v:331:y:2026:i:2:p:629-644
    DOI: 10.1016/j.ejor.2025.10.018
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    JEL classification:

    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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