Ecological efficiency in China and its influencing factors—a super-efficient SBM metafrontier-Malmquist-Tobit model study

被引:0
|
作者
Xiaojun Ma
Changxin Wang
Yuanbo Yu
Yudong Li
Biying Dong
Xinyu Zhang
Xueqi Niu
Qian Yang
Ruimin Chen
Yifan Li
Yihan Gu
机构
[1] Dongbei University of Finance and Economics,School of Statistics
[2] Liaoning University,Asia Australia Business College
[3] University of California-Los Angeles,College of Letters and Science
[4] Shenyang Agricultural University,School of Economics and Management
关键词
Ecological efficiency; Super efficiency SBM model; Malmquist index; Metafrontier-Malmquist index; Technology gap ratio; Influence factors;
D O I
暂无
中图分类号
学科分类号
摘要
Ecological problem is one of the core issues that restrain China’s economic development at present, and it is urgently needed to be solved properly and effectively. Based on panel data from 30 regions, this paper uses a super efficiency slack-based measure (SBM) model that introduces the undesirable output to calculate the ecological efficiency, and then uses traditional and metafrontier-Malmquist index method to study regional change trends and technology gap ratios (TGRs). Finally, the Tobit regression and principal component analysis methods are used to analysis the main factors affecting eco-efficiency and impact degree. The results show that about 60% of China’s provinces have effective eco-efficiency, and the overall ecological efficiency of China is at the superior middling level, but there is a serious imbalance among different provinces and regions. Ecological efficiency has an obvious spatial cluster effect. There are differences among regional TGR values. Most regions show a downward trend and the phenomenon of focusing on economic development at the expense of ecological protection still exists. Expansion of opening to the outside, increases in R&D spending, and improvement of population urbanization rate have positive effects on eco-efficiency. Blind economic expansion, increases of industrial structure, and proportion of energy consumption have negative effects on eco-efficiency.
引用
收藏
页码:20880 / 20898
页数:18
相关论文
共 50 条
  • [1] Ecological efficiency in China and its influencing factors-a super-efficient SBM metafrontier-Malmquist-Tobit model study
    Ma, Xiaojun
    Wang, Changxin
    Yu, Yuanbo
    Li, Yudong
    Dong, Biying
    Zhang, Xinyu
    Niu, Xueqi
    Yang, Qian
    Chen, Ruimin
    Li, Yifan
    Gu, Yihan
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2018, 25 (21) : 20880 - 20898
  • [2] The Efficiency of China's Hub Economy and Its Influencing Factors: A Two-Stage Analysis Based on the Super SBM-Malmquist-Tobit Model
    Fan, Xueru
    Yao, Guanxin
    Yang, Yang
    COMPLEXITY, 2024, 2024
  • [3] Industrial water consumption efficiency and driving factors based on the super-efficient SBM and Tobit approach
    Haixia Duo
    Ning Wang
    Yunfeng Qiao
    Zhao Li
    Guang Yang
    Hongguang Liu
    Gang Chen
    Fadong Li
    Scientific Reports, 15 (1)
  • [4] Ecological efficiency of hog scale production under environmental regulation in China: based on an optimal super efficiency SBM-Malmquist–Tobit model
    Qianrong Wu
    Lanzhuang Xu
    Xianhui Geng
    Environmental Science and Pollution Research, 2022, 29 : 53088 - 53106
  • [5] Ecological efficiency of hog scale production under environmental regulation in China: based on an optimal super efficiency SBM-Malmquist-Tobit model
    Wu, Qianrong
    Xu, Lanzhuang
    Geng, Xianhui
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (35) : 53088 - 53106
  • [6] Ecological efficiency in the development of circular economy of China under hard constraints based on an optimal super efficiency SBM-Malmquist-Tobit model.
    Ma, Xiao-Jun
    Li, Yu-Dong
    Wang, Chang-Xin
    Yu, Yuan-Bo
    Zhongguo Huanjing Kexue/China Environmental Science, 2018, 38 (09): : 3584 - 3593
  • [7] Exploring the Measurement of Regional Forestry Eco-Efficiency and Influencing Factors in China Based on the Super-Efficient DEA-Tobit Two Stage Model
    Tan, Junlan
    Su, Xiang
    Wang, Rong
    FORESTS, 2023, 14 (02):
  • [8] China's artificial intelligence efficiency and its influencing factors: Based on DEA-Malmquist and Tobit regression model
    Dong, Yan-Yan
    Wang, Dong-Qiang
    DECISION SCIENCE LETTERS, 2023, 12 (04) : 729 - 738
  • [9] A study on the measurement and influencing factors of the urban wastewater treatment efficiency in China based on the superefficiency SBM-Tobit model
    Tao, Tingyu
    Zhang, Hao
    Hu, Zikun
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2024, 12
  • [10] Research on Environmental Performance Measurement and Influencing Factors of Key Cities in China Based on Super-Efficiency SBM-Tobit Model
    Xue, Lirong
    Qu, Aiyu
    Guo, Xiurui
    Hao, Chunxu
    SUSTAINABILITY, 2024, 16 (11)