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A Study of Carbon Emission Efficiency in Chinese Provinces Based on a Three-Stage SBM-Undesirable Model and an LSTM Model

Author

Listed:
  • Huayong Niu

    (International Business School, Beijing Foreign Studies University, Beijing 100089, China)

  • Zhishuo Zhang

    (International Business School, Beijing Foreign Studies University, Beijing 100089, China)

  • Yao Xiao

    (International Business School, Beijing Foreign Studies University, Beijing 100089, China)

  • Manting Luo

    (International Business School, Beijing Foreign Studies University, Beijing 100089, China)

  • Yumeng Chen

    (Liaoning Banking and Insurance Regulatory Bureau, Shenyang 110013, China)

Abstract

As a major carbon-emitting country, there is an urgent need for China to reduce carbon emissions. Studying the carbon emission efficiency of each province helps us to learn about the characteristics and evolution of regional carbon emissions, which is important for proposing effective and targeted measures to achieve the carbon peaking and carbon neutrality goals. This paper measures the carbon emission efficiency of 30 Chinese provinces from 2006 to 2019 based on a three-stage SBM-undesirable model and explores external drivers using stochastic frontier models. The results of the SBM-undesirable model show that the inter-provincial carbon emission efficiency is unevenly distributed and shows a big difference. From the results of the stochastic frontier model analysis, external drivers such as the intensity of finance in environmental protection, the level of economic development, the industrial structure, the level of urbanization, the degree of openness and the level of science as well as technology innovation all have an impact on the emission efficiency. In terms of LSTM model prediction, the model shows an excellent fitting effect, which provides a possible path for carbon emission efficiency prediction. Finally, based on the empirical results and the actual situation of each province in China, this paper proposes relevant feasible suggestions.

Suggested Citation

  • Huayong Niu & Zhishuo Zhang & Yao Xiao & Manting Luo & Yumeng Chen, 2022. "A Study of Carbon Emission Efficiency in Chinese Provinces Based on a Three-Stage SBM-Undesirable Model and an LSTM Model," IJERPH, MDPI, vol. 19(9), pages 1-19, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5395-:d:804873
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    References listed on IDEAS

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    Cited by:

    1. Pan Jiang & Mengyue Li & Yuting Zhao & Xiujuan Gong & Ruifeng Jin & Yuhan Zhang & Xue Li & Liang Liu, 2022. "Does Environmental Regulation Improve Carbon Emission Efficiency? Inspection of Panel Data from Inter-Provincial Provinces in China," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    2. Huayong Niu & Zhishuo Zhang & Manting Luo, 2022. "Evaluation and Prediction of Low-Carbon Economic Efficiency in China, Japan and South Korea: Based on DEA and Machine Learning," IJERPH, MDPI, vol. 19(19), pages 1-28, October.
    3. Mei Zhang & Hanye Zhang & Yun Deng & Chuanqi Yi, 2024. "Effects of Conservation Tillage on Agricultural Green Total Factor Productivity in Black Soil Region: Evidence from Heilongjiang Province, China," Land, MDPI, vol. 13(8), pages 1-23, August.
    4. Min Zhou & Hua Zhang & Zixuan Zhang & Hanxiaoxue Sun, 2023. "Digital Financial Inclusion, Cultivated Land Transfer and Cultivated Land Green Utilization Efficiency: An Empirical Study from China," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    5. Rongbang Xu & Fujie Yang & Sanmang Wu & Qinwen Xue, 2024. "Spatio-Temporal Evolution and Drivers of Carbon Emission Efficiency in China’s Iron and Steel Industry," Sustainability, MDPI, vol. 16(12), pages 1-22, June.
    6. Jih-Shong Wu, 2023. "Measuring Economic Development and Carbon Dioxide Emissions Inefficiency," SAGE Open, , vol. 13(1), pages 21582440231, February.

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