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Yangtze River Basin Environmental Regulation Efficiency Based on the Empirical Analysis of 97 Cities from 2005 to 2016

Author

Listed:
  • Qian Zhang

    (School of Economics and Management, Nanjing Forestry University, Nanjing 210037, China
    School of Law and Business, Sanjiang University, Nanjing 210012, China)

  • Decai Tang

    (School of Law and Business, Sanjiang University, Nanjing 210012, China)

  • Brandon J. Bethel

    (School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

The Yangtze River Basin (YRB) is an important area for China’s economic development and environmental governance. The aim of this paper is to analyze the total factor productivity across 97 cities in the YRB from 2005 to 2016. Based on the input and output indicators from 2005 to 2016, this paper selects the SE-SBM model to measure the environmental regulation efficiency (ERE) of 97 cities in the YRB and then uses the DEA–Malmquist index to measure the total factor productivity of the region. Results suggest that the overall ERE in the YRB is weakly ineffective, while ERE in the central and eastern coastal areas is relatively high. ERE matches the economic foundation and development of the city. YRB environmental regulation efficiency was in descending order in the middle stream, upstream, and downstream. The efficiency of regional environmental regulation shows an N-type development trend, with obvious characteristics of phased development. Moreover, the total factor productivity of the YRB has shown a downward trend. The scale efficiency index and the technical efficiency index have positively boosted the total factor productivity, while the technological progress index has dragged down the total factor productivity of the area. The contribution to the total factor productivity index is in order of scale efficiency, technological progress index, and technological efficiency index in the downstream. The overall inputs and outputs of the YRB have great development potential. The inputs have not been fully utilized, the outputs have not been maximized, and the regional differentiation is significantly observable.

Suggested Citation

  • Qian Zhang & Decai Tang & Brandon J. Bethel, 2021. "Yangtze River Basin Environmental Regulation Efficiency Based on the Empirical Analysis of 97 Cities from 2005 to 2016," IJERPH, MDPI, vol. 18(11), pages 1-22, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5697-:d:562520
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    References listed on IDEAS

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    1. Yanhong Liu & Xinjian Huang & Weiliang Chen, 2019. "Threshold Effect of High-Tech Industrial Scale on Green Development—Evidence from Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(5), pages 1-21, March.
    2. Pan, Xiongfeng & Ai, Bowei & Li, Changyu & Pan, Xianyou & Yan, Yaobo, 2019. "Dynamic relationship among environmental regulation, technological innovation and energy efficiency based on large scale provincial panel data in China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 428-435.
    3. Estache, Antonio & de la Fe, Beatriz Tovar & Trujillo, Lourdes, 2004. "Sources of efficiency gains in port reform: a DEA decomposition of a Malmquist TFP index for Mexico," Utilities Policy, Elsevier, vol. 12(4), pages 221-230, December.
    4. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.
    5. Li, Hai-ling & Zhu, Xue-hong & Chen, Jin-yu & Jiang, Fei-tao, 2019. "Environmental regulations, environmental governance efficiency and the green transformation of China's iron and steel enterprises," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    6. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    7. Peng, Benhong & Chen, Hong & Elahi, Ehsan & Wei, Guo, 2020. "Study on the spatial differentiation of environmental governance performance of Yangtze river urban agglomeration in Jiangsu province of China," Land Use Policy, Elsevier, vol. 99(C).
    8. Liu, Yunqiang & Zhu, Jialing & Li, Eldon Y. & Meng, Zhiyi & Song, Yan, 2020. "Environmental regulation, green technological innovation, and eco-efficiency: The case of Yangtze river economic belt in China," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    9. Rios, Vicente & Gianmoena, Lisa, 2018. "Convergence in CO2 emissions: A spatial economic analysis with cross-country interactions," Energy Economics, Elsevier, vol. 75(C), pages 222-238.
    10. Weiliang Chen & Xinjian Huang & Yanhong Liu & Xin Luan & Yan Song, 2019. "The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    11. Benhong Peng & Yue Li & Guo Wei & Ehsan Elahi, 2018. "Temporal and Spatial Differentiations in Environmental Governance," IJERPH, MDPI, vol. 15(10), pages 1-14, October.
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