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Regional Variation in Carbon Emissions and its Driving Forces in China: An Index Decomposition Analysis

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  • Shu Yang

    (School of Management University of Science and Technology of China)

  • Dingtao Zhao

    (School of Management University of Science and Technology of China)

  • Yanrui Wu

    (University of Western Australia)

  • Jin Fan

    (School of Management University of Science and Technology of China)

Abstract

This paper aims to investigate the factors affecting carbon emissions from the perspective of residential energy consumption. Specifically, through an index decomposition analysis (IDA), it examines the influence of social and economic factors on household carbon emissions in China’s provinces. The results show that CO2 emissions associated with household consumption continued to grow during the decade of 2000-2010. In general, per capita consumption expenditure and the share of energy consumption expenditure in total consumption spending are two main factors contributing to an increase in residential carbon emissions, while the change of energy consumption structure and energy price mitigated the growth of carbon emissions. However, there are considerable regional differences. Therefore, Chinese government must consider the substantial contribution of residential consumption to carbon emissions when it aims to expand domestic consumption.

Suggested Citation

  • Shu Yang & Dingtao Zhao & Yanrui Wu & Jin Fan, 2013. "Regional Variation in Carbon Emissions and its Driving Forces in China: An Index Decomposition Analysis," Economics Discussion / Working Papers 13-34, The University of Western Australia, Department of Economics.
    • Handle: RePEc:uwa:wpaper:13-34
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    Cited by:

    1. Ling Yang & Michael L. Lahr, 2019. "The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    2. Bin Wang & Qiuxia Zheng & Ao Sun & Jie Bao & Dianting Wu, 2021. "Spatio-Temporal Patterns of CO 2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM," Mathematics, MDPI, vol. 9(21), pages 1-24, October.

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