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Low Carbon Economy Assessment in China Using the Super-SBM Model

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  • Yanhong Ding
  • Yu Han
  • Zaoli Yang

Abstract

This review proposes a performance evaluation system of low-carbon economic development based on multiobjective analysis in low-carbon environment. This is a modeling method combining super efficiency and relaxation-based measurement model (super-SBM model), which can effectively measure green innovation efficiency with unexpected outputs and traditional innovation efficiency without unexpected outputs. Using the Malmquist–Luenberger index method to dynamically analyze the efficiency of green innovation, a multiobjective model is obtained, including economic scheduling target considering wind power cost and low-carbon scheduling target considering carbon trading. The efficiency of green innovation considering unexpected output is obviously lower than that of traditional innovation without considering unexpected output. This phenomenon is more pronounced in some areas of central and western China. Technical efficiency improves the innovation level of environmental protection economy in China and the impact of technological progress is greater than that of technical efficiency. In this review, the output super SBM model is used to study the development of China's low-carbon industry, and the correlation between the prediction model and the performance change of low-carbon economic development is analyzed. The Malmquist–Luenberger (ML) index of environmental protection product development efficiency in China is not less than 1. Due to the improvement of the efficiency of scientific and technological development, the combination of the two will eventually lead to the improvement of the development of green products and environmental economic products in China. Combining with the empirical analysis, this paper puts forward some methods to promote the low-carbon economy in the economic zone.

Suggested Citation

  • Yanhong Ding & Yu Han & Zaoli Yang, 2022. "Low Carbon Economy Assessment in China Using the Super-SBM Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-9, May.
  • Handle: RePEc:hin:jnddns:4690140
    DOI: 10.1155/2022/4690140
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    Cited by:

    1. Maria Gouveia & Carla Henriques & Ana Amaro, 2022. "Is the Cohesion Policy Efficient in Supporting the Transition to a Low-Carbon Economy? Some Insights with Value-Based Data Envelopment Analysis," Sustainability, MDPI, vol. 14(18), pages 1-24, September.
    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.

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