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Compositional regression analysis of the energy mix and its determinants

  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigates the determinants of national energy mixes across 182 countries from 1990 to 2019 using an adapted IPAT framework and a dual-model approach combining fractional logit and compositional linear models. The analysis highlights the critical roles of resource dependency, economic development, population growth, and technological advancements in shaping energy transitions. Key findings include: (1) resource-rich countries exhibit strong dependencies on hydroelectricity, biomass, and fossil fuels. In resource-rich scenarios, fossil fuel dependency persists with oil, natural gas, and coal shares increasing by 0.9 %–14.8 %, while renewable energy adoption remains limited, with hydroelectricity, biomass, and solar and geothermal shares rising modestly (0.3 %–7.6 %); (2) income growth drives diversification, with higher-income countries transitioning to natural gas, nuclear energy, and renewables, while lower-income countries remain reliant on fossil fuels and biomass due to structural barriers. Highincome countries with abundant renewables, such as Iceland, achieve notable carbon intensity reductions, with solar and geothermal electricity reaching 65.7 % of their energy mix; and (3) population growth impedes modern renewable adoption, particularly in lower-income contexts, underscoring the need for targeted policies. These findings provide globally representative, evidence-based insights for policymakers aiming to balance sustainability, economic growth, and energy security.

Original languageEnglish
Article number136015
JournalEnergy
Volume324
DOIs
StatePublished - 1 Jun 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Keywords

  • Carbon intensity
  • Compositional data analysis
  • Energy mix
  • Energy transitions
  • IPAT framework
  • Renewable energy adoption
  • Resource dependency

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