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Examining inefficiency in countries with high energy consumption: A benchmarking approach

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  • Valadkhani, Abbas
  • Moradi-Motlagh, Amir

Abstract

This study introduces a minimum distance non-radial model, derived from Weighted Russell Directional Distance Model (WRDDM), to assess inefficiency across 40 countries representing 90 % of global energy consumption in 2019. We analyze energy consumption per capita (input), GDP per capita (desirable output), and CO2 emissions per capita (undesirable output) for 2007 and 2019. The countries are divided into two groups: OECD (Organisation for Economic Cooperation and Development) and non-OECD. Our methodological innovation combines WRDDM with closest target models to estimate overall inefficiency and decompose it into GDP, energy consumption, and CO2 emissions per capita, enabling dollar-value comparisons. We found evidence for the “paradox of plenty,” where oil and gas-rich countries show high energy and CO2 inefficiencies. The results provide valuable insights for establishing equitable and practical benchmarks, fostering international cooperation, and addressing the resource curse. Our findings suggest that reducing per capita energy consumption and CO2 emissions is both feasible and economically justified for enhancing overall efficiency. Inter alia, we found that while OECD countries improved their energy and CO₂ emission efficiencies between 2007 and 2019, only a few non-OECD countries achieved comparable progress.

Suggested Citation

  • Valadkhani, Abbas & Moradi-Motlagh, Amir, 2025. "Examining inefficiency in countries with high energy consumption: A benchmarking approach," Energy Economics, Elsevier, vol. 145(C).
  • Handle: RePEc:eee:eneeco:v:145:y:2025:i:c:s0140988325003111
    DOI: 10.1016/j.eneco.2025.108487
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    Keywords

    Energy consumption; CO2 emissions; Per capita GDP; Efficiency; Data envelopment analysis; Closest target; Climate action;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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