[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/biw/wpaper/47.html
   My bibliography  Save this paper

Multi-directional efficiency analysis-based regional industrial environmental performance evaluation of China

Author

Listed:
  • Ke Wang
  • Shiwei Yu
  • Mo-Jie Li
  • Yi-Ming Wei

    (Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology)

Abstract
This study evaluates the environmental efficiency of industrial sectors of Chinese major cities. The Multi-directional efficiency analysis (MEA) approach are utilized for evaluation, thus both the integrated MEA efficiency levels and the efficiency patterns, which are represented by the variable specific MEA efficiency according to each type of the industrial pollutant emission or discharge, of Chinese major city are detected. In addition the industrial energy conservation and pollutant reduction potentials are measured and the relationship between environmental pressure and income are explored at the regional level of China. The main findings include: (i) The MEA environmental efficiency increases of the economic less developed cities were faster than the cities in the well-developed region, which indicates that the inequitable nationwide industrial developments of Chinese cities have started to alleviate. (ii) Although some Chinese cities show similar environmental efficiency levels, the undesirable output variable specific efficiency patterns of these cities are diversified, and according to the variable specific efficiency, the most possible efficiency increase potential of each Chinese major city can be identified. (iii) An N-shaped Environmental Kuznets Curve exists in the industrial sectors of Chinese major cities. (iv) Different Chinese cities should have different industrial pollutant reduction priorities, which east China cities should pay more attention on their industrial waste gas emissions and industrial waste water discharges, while west China cities should mainly focus on their industrial soot and dust emissions, and solid waste discharges.

Suggested Citation

  • Ke Wang & Shiwei Yu & Mo-Jie Li & Yi-Ming Wei, 2013. "Multi-directional efficiency analysis-based regional industrial environmental performance evaluation of China," CEEP-BIT Working Papers 47, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    • Handle: RePEc:biw:wpaper:47
    as

    Download full text from publisher

    File URL: http://ceep.bit.edu.cn/docs/2018-10/20181011140052070397.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Peter Bogetoft & Jens Hougaard, 1999. "Efficiency Evaluations Based on Potential (Non-Proportional) Improvements," Journal of Productivity Analysis, Springer, vol. 12(3), pages 233-247, November.
    2. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    3. Jianyi Huang & Yi Liu & Li Ma & Fei Su, 2013. "Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 115-134, January.
    4. Torben Holvad & Jens Hougaard & Dorte Kronborg & Hans Kvist, 2004. "Measuring inefficiency in the Norwegian bus industry using multi-directional efficiency analysis," Transportation, Springer, vol. 31(3), pages 349-369, August.
    5. Hua Liao, 2012. "China Country Report," Chapters, in: Shigeru Kimura (ed.), Analysis on Energy Saving Potential in East Asia, chapter 5, pages 115-130, Economic Research Institute for ASEAN and East Asia (ERIA).
    6. Murty, Sushama & Russell, R. Robert, 2010. "On modeling pollution-generating technologies," Economic Research Papers 271176, University of Warwick - Department of Economics.
    7. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    8. Yiming Wei & Lancui Liu & Gang Wu & Lele Zou (ed.), 2010. "Energy Economics: CO2 Emissions in China," CEEP-BIT Books, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology, number b1, december.
    9. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    10. Gongbing Bi & Yan Luo & Jingjing Ding & Liang Liang, 2015. "Environmental performance analysis of Chinese industry from a slacks-based perspective," Annals of Operations Research, Springer, vol. 228(1), pages 65-80, May.
    11. Auffhammer, Maximilian & Carson, Richard T., 2008. "Forecasting the path of China's CO2 emissions using province-level information," Journal of Environmental Economics and Management, Elsevier, vol. 55(3), pages 229-247, May.
    12. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    13. Hua, Zhongsheng & Bian, Yiwen & Liang, Liang, 2007. "Eco-efficiency analysis of paper mills along the Huai River: An extended DEA approach," Omega, Elsevier, vol. 35(5), pages 578-587, October.
    14. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    15. Song, Tao & Zheng, Tingguo & Tong, Lianjun, 2008. "An empirical test of the environmental Kuznets curve in China: A panel cointegration approach," China Economic Review, Elsevier, vol. 19(3), pages 381-392, September.
    16. Dinda, Soumyananda, 2004. "Environmental Kuznets Curve Hypothesis: A Survey," Ecological Economics, Elsevier, vol. 49(4), pages 431-455, August.
    17. Mette Asmild & Jens Hougaard & Dorte Kronborg & Hans Kvist, 2003. "Measuring Inefficiency Via Potential Improvements," Journal of Productivity Analysis, Springer, vol. 19(1), pages 59-76, January.
    18. Asmild, Mette & Matthews, Kent, 2012. "Multi-directional efficiency analysis of efficiency patterns in Chinese banks 1997–2008," European Journal of Operational Research, Elsevier, vol. 219(2), pages 434-441.
    19. Mette Asmild & Torben Holvad & Jens Hougaard & Dorte Kronborg, 2009. "Railway reforms: do they influence operating efficiency?," Transportation, Springer, vol. 36(5), pages 617-638, September.
    20. Auffhammer, Maximilian & Carson, Richard T., 2007. "Forecasting the Path of China's CO2 Emissions Using Province Level Information," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6d28j8rg, Department of Agricultural & Resource Economics, UC Berkeley.
    21. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qianwen Li & Ruyin Long & Hong Chen & Feiyu Chen & Xiu Cheng, 2019. "Chinese urban resident willingness to pay for green housing based on double-entry mental accounting theory," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 129-153, January.
    2. Jiawei Yang, 2023. "Disentangling the sources of bank inefficiency: a two-stage network multi-directional efficiency analysis approach," Annals of Operations Research, Springer, vol. 326(1), pages 369-410, July.
    3. Jia-Yin Yin & Yun-Fei Cao & Bao-Jun Tang, 2019. "Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 343-362, January.
    4. Manevska-Tasevska, Gordana & Hansson, Helena & Asmild, Mette & Surry, Yves, 2021. "Exploring the regional efficiency of the Swedish agricultural sector during the CAP reforms ‒ multi-directional efficiency analysis approach," Land Use Policy, Elsevier, vol. 100(C).
    5. Zhu, Ning & Wu, Yanrui & Wang, Bing & Yu, Zhiqian, 2019. "Risk preference and efficiency in Chinese banking," China Economic Review, Elsevier, vol. 53(C), pages 324-341.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, vol. 130(C), pages 617-631.
    2. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," Applied Energy, Elsevier, vol. 104(C), pages 105-116.
    3. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    4. Kapelko, Magdalena & Oude Lansink, Alfons, 2017. "Dynamic multi-directional inefficiency analysis of European dairy manufacturing firms," European Journal of Operational Research, Elsevier, vol. 257(1), pages 338-344.
    5. Zhu, Lin & Wang, Yong & Shang, Peipei & Qi, Lin & Yang, Guangchun & Wang, Ying, 2019. "Improvement path, the improvement potential and the dynamic evolution of regional energy efficiency in China: Based on an improved nonradial multidirectional efficiency analysis," Energy Policy, Elsevier, vol. 133(C).
    6. Zhu, Ning & Wu, Yanrui & Wang, Bing & Yu, Zhiqian, 2019. "Risk preference and efficiency in Chinese banking," China Economic Review, Elsevier, vol. 53(C), pages 324-341.
    7. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    8. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    9. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    10. Haider Mahmood & Maham Furqan & Muhammad Shahid Hassan & Soumen Rej, 2023. "The Environmental Kuznets Curve (EKC) Hypothesis in China: A Review," Sustainability, MDPI, vol. 15(7), pages 1-32, April.
    11. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    12. Guangyu Luo & Jia-Hsi Weng & Qianxue Zhang & Yu Hao, 2017. "A reexamination of the existence of environmental Kuznets curve for CO2 emissions: evidence from G20 countries," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 1023-1042, January.
    13. Hao, Yu & Wei, Yi-Ming, 2015. "When does the turning point in China's CO2 emissions occur? Results based on the Green Solow model," Environment and Development Economics, Cambridge University Press, vol. 20(6), pages 723-745, December.
    14. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
    15. Zhang, Qianxue & Liao, Hua & Hao, Yu, 2018. "Does one path fit all? An empirical study on the relationship between energy consumption and economic development for individual Chinese provinces," Energy, Elsevier, vol. 150(C), pages 527-543.
    16. Jalil, Abdul & Mahmud, Syed F., 2009. "Environment Kuznets curve for CO2 emissions: A cointegration analysis for China," Energy Policy, Elsevier, vol. 37(12), pages 5167-5172, December.
    17. Guglielmo Maria Caporale & Gloria Claudio-Quiroga & Luis A. Gil-Alana, 2019. "CO2 Emissions and GDP: Evidence from China," CESifo Working Paper Series 7881, CESifo.
    18. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    19. Jiawei Yang, 2023. "Disentangling the sources of bank inefficiency: a two-stage network multi-directional efficiency analysis approach," Annals of Operations Research, Springer, vol. 326(1), pages 369-410, July.
    20. Baležentis, Tomas & De Witte, Kristof, 2015. "One- and multi-directional conditional efficiency measurement – Efficiency in Lithuanian family farms," European Journal of Operational Research, Elsevier, vol. 245(2), pages 612-622.

    More about this item

    Keywords

    Environmental performance; Industrial sector; Pollutant reduction potential; Multi-directional Efficiency Analysis (MEA);
    All these keywords.

    JEL classification:

    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:biw:wpaper:47. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Zhi-Fu Mi (email available below). General contact details of provider: https://edirc.repec.org/data/cebitcn.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.