Analysis of energy intensity of GDP in the N-11: Examining the role of low carbon energy transition and energy access

Energy efficiency has become a pressing concern for economies undergoing rapid industrialisation while simultaneously managing growing energy demand. This study investigates how low carbon energy transition and energy access affect the energy intensity of GDP across the Next Eleven (N-11) economies over the period 1990–2024. Energy intensity is defined as total primary energy consumption per unit of real economic output. Low carbon energy transition is proxied by the combined share of natural gas, nuclear energy, and renewable energy in total energy consumption. Energy access is measured by the proportion of the national population with access to electricity. The study incorporates carbon emissions, population size, urbanisation, gross fixed capital formation, and trade openness as additional control variables. Panel data for all eleven N-11 countries were sourced from the World Bank, the International Energy Agency, and Our World in Data. To account for heterogeneous effects at different points of the energy intensity distribution, the empirical analysis applies the Method of Moments Quantile Regression technique. Preliminary diagnostic tests confirm cross-sectional dependence, slope heterogeneity, mixed orders of integration, and long-run cointegration among the study variables. Several findings emerge from the estimation. Energy access exerts a positive and statistically significant effect on energy intensity across most quantiles. This result is not surprising: expanding electricity access tends to raise aggregate energy demand in the near term, before any accompanying efficiency gains have time to take hold. Low carbon energy transition, by contrast, reduces energy intensity, which is consistent with the argument that cleaner energy sources raise the productive efficiency of energy use. Carbon emissions are positively associated with energy intensity, while gross fixed capital formation contributes to efficiency by lowering it. Urbanisation and population produce effects that vary across the energy intensity distribution rather than following a single direction. Overall, these findings point to a structural tension in development-oriented energy policy. Expanding access without coordinating efficiency measures risks locking in high energy intensity at precisely the moment when N-11 economies have the most to gain from low carbon transition.

Authors

Institutions

Publication Details

Journal
Next Energy
Published
2026-11-02
DOI
https://doi.org/10.1016/j.nxener.2026.101171
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of energy intensity of GDP in the N-11: Examining the role of low carbon energy transition and energy access

Leonard Nnaemeka Ezeh, Stephen Obinozie Ogwu, Precious Muhammed Emmanuel, Chijioke Richie Ezekwube
1 links
Next Energy
Energy, Environment, Economic Growth
article

Analysis of energy intensity of GDP in the N-11: Examining the role of low carbon energy transition and energy access

Leonard Nnaemeka Ezeh, Stephen Obinozie Ogwu, Precious Muhammed Emmanuel, Chijioke Richie Ezekwube
article en

Abstract

Energy efficiency has become a pressing concern for economies undergoing rapid industrialisation while simultaneously managing growing energy demand. This study investigates how low carbon energy transition and energy access affect the energy intensity of GDP across the Next Eleven (N-11) economies over the period 1990–2024. Energy intensity is defined as total primary energy consumption per unit of real economic output. Low carbon energy transition is proxied by the combined share of natural gas, nuclear energy, and renewable energy in total energy consumption. Energy access is measured by the proportion of the national population with access to electricity. The study incorporates carbon emissions, population size, urbanisation, gross fixed capital formation, and trade openness as additional control variables. Panel data for all eleven N-11 countries were sourced from the World Bank, the International Energy Agency, and Our World in Data. To account for heterogeneous effects at different points of the energy intensity distribution, the empirical analysis applies the Method of Moments Quantile Regression technique. Preliminary diagnostic tests confirm cross-sectional dependence, slope heterogeneity, mixed orders of integration, and long-run cointegration among the study variables. Several findings emerge from the estimation. Energy access exerts a positive and statistically significant effect on energy intensity across most quantiles. This result is not surprising: expanding electricity access tends to raise aggregate energy demand in the near term, before any accompanying efficiency gains have time to take hold. Low carbon energy transition, by contrast, reduces energy intensity, which is consistent with the argument that cleaner energy sources raise the productive efficiency of energy use. Carbon emissions are positively associated with energy intensity, while gross fixed capital formation contributes to efficiency by lowering it. Urbanisation and population produce effects that vary across the energy intensity distribution rather than following a single direction. Overall, these findings point to a structural tension in development-oriented energy policy. Expanding access without coordinating efficiency measures risks locking in high energy intensity at precisely the moment when N-11 economies have the most to gain from low carbon transition.

Next EnergyVol. 14
Covenant University (NG), Nnamdi Azikiwe University (NG), Ostim Technical University (TR), Dennis Osadebay University (NG), Miva Open University (NG)
Climate action, Industry, innovation and infrastructure, Affordable and clean energy, Reduced inequalities, Decent work and economic growth
Openalex Percentile: Top 11%
Energy, Environment, Economic Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon