Energy Intensity Convergence among Chinese Provinces: A Theil Index Decomposition Analysis
China, the world’s largest carbon emitter, has one of the most stringent provincial emissions reduction programs, incorporated into its Five-Year National Plan to reduce carbon emissions. However, the widening energy intensity gap between provinces poses a great challenge for carbon reduction. In th...
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| Format: | text |
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Archīum Ateneo
2024
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| Online Access: | https://archium.ateneo.edu/asog-pubs/298 https://archium.ateneo.edu/context/asog-pubs/article/1300/viewcontent/s43621_024_00297_0.pdf |
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| Institution: | Ateneo De Manila University |
| Summary: | China, the world’s largest carbon emitter, has one of the most stringent provincial emissions reduction programs, incorporated into its Five-Year National Plan to reduce carbon emissions. However, the widening energy intensity gap between provinces poses a great challenge for carbon reduction. In this study, we analyze the convergence of Energy intensity (EIC), i.e., the time-dependent decrease of differences among regional energy intensity over time focusing on a data set of 30 Chinese provinces from 2000 to 2015. Our goal is to identify the provinces that are responsible for the observed divergence in energy intensity and identify the factors causing that divergence in each individual case. The Theil index is used to capture inter-provincial energy inequality. We use the LMDI decomposition analysis to identify the drivers of energy inequality (energy consumption structure, energy efficiency, and industrial structure). The results suggest that reducing energy intensity in Inner Mongolia, Xinjiang, and Hebei is the key to solving China's increasing energy intensity “gap” dilemma. The factors causing the energy intensity divergence in Inner Mongolia and Xinjiang are related to lagging economic growth and low energy efficiency, which impedes carbon emission reductions significantly. The factors causing the divergence of energy intensity in Hebei are rooted in its heavy industrial structure. Our findings are directly applicable to crafting regional energy policy with more targeted and practical emission reduction programs. |
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