IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/55380.html
   My bibliography  Save this paper

基于非径向bml-Dea模型的中国地区工业环境绩效测度
[The measurement of regional industrial Environmental Performance——based on non-radial BML-DEA model]

Author

Listed:
  • Tang, Liwei
  • Hu, Zongyi
  • Zhang, Yongjun

Abstract

Combining the characteristics of BM direction distance function, non- radial DEA model and Luenberger productivity indicators, we develop a non-radial BML-DEA model to measure Environmental Performance. And by using the panel data of 30 provinces from 1997 to 2011 in China, we measure and analysis the regional industrial eco-efficiency. The results show that the overall growth of industrial Environmental Performance of the region comes mainly from technological progress rather than efficiency improvements, the highest average annual growth rate of areas are Beijing, Shanghai, Jiangsu and Guangdong. The effect from three pollutants on industrial Environmental Performance by descending is SO2, CO2 and Smoker, and the contribution of the three pollutants deal more balanced. There are significant differences among industrial Environmental Performance and its decomposition ingredients in different regions. The growth rate of industrial Environmental Performance in east is significantly higher than other regions, but the growth rate of efficiency is not superior to the center and west, and even slightly lower than the center. Therefore, regions need to enhance the efficiency in using the resources.

Suggested Citation

  • Tang, Liwei & Hu, Zongyi & Zhang, Yongjun, 2014. "基于非径向bml-Dea模型的中国地区工业环境绩效测度 [The measurement of regional industrial Environmental Performance——based on non-radial BML-DEA model]," MPRA Paper 55380, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:55380
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/55380/1/MPRA_paper_55380.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    2. Lee, Hsuan-Shih & Chu, Ching-Wu & Zhu, Joe, 2011. "Super-efficiency DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 212(1), pages 141-147, July.
    3. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    4. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    5. Kortelainen, Mika, 2008. "Dynamic environmental performance analysis: A Malmquist index approach," Ecological Economics, Elsevier, vol. 64(4), pages 701-715, February.
    6. Pastor, Jesús T. & Asmild, Mette & Lovell, C.A. Knox, 2011. "The biennial Malmquist productivity change index," Socio-Economic Planning Sciences, Elsevier, vol. 45(1), pages 10-15, March.
    7. Andrés J. Picazo-Tadeo & Juana Castillo & Mercedes Beltrán-Esteve, 2013. "A dynamic approach to measuring ecological-economic performance with directional distance functions: greenhouse gas emissions in the European Union," Working Papers 1304, Department of Applied Economics II, Universidad de Valencia.
    8. 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.
    9. Mariam Camarero & Juana Castillo-Giménez & Andrés Picazo-Tadeo & Cecilio Tamarit, 2014. "Is eco-efficiency in greenhouse gas emissions converging among European Union countries?," Empirical Economics, Springer, vol. 47(1), pages 143-168, August.
    10. Chang, Tzu-Pu & Hu, Jin-Li & Chou, Ray Yeutien & Sun, Lei, 2012. "The sources of bank productivity growth in China during 2002–2009: A disaggregation view," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1997-2006.
    Full references (including those not matched with items on IDEAS)

    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. hu, zongyi & tang, liwei & su, jin, 2013. "区域环境绩效测度及收敛性分析 [Regional eco-performance measure and its convergence]," MPRA Paper 60367, University Library of Munich, Germany.
    2. Picazo-Tadeo, Andrés J. & Castillo-Giménez, Juana & Beltrán-Esteve, Mercedes, 2014. "An intertemporal approach to measuring environmental performance with directional distance functions: Greenhouse gas emissions in the European Union," Ecological Economics, Elsevier, vol. 100(C), pages 173-182.
    3. 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.
    4. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    5. Tianqun Xu & Ping Gao & Qian Yu & Debin Fang, 2017. "An Improved Eco-Efficiency Analysis Framework Based on Slacks-Based Measure Method," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    6. Li, Shuangmei & Zhu, Xuehong & Zhang, Tao, 2023. "Optimum combination of heterogeneous environmental policy instruments and market for green transformation: Empirical evidence from China's metal sector," Energy Economics, Elsevier, vol. 123(C).
    7. Zhong, Shen & Li, Junwei & Chen, Xi & Wen, Hongmei, 2022. "A multi-hierarchy meta-frontier approach for measuring green total factor productivity: An application of pig breeding in China," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    8. Chunbin Zhang & Rong Zhou & Jundong Hou & Mengtong Feng, 2022. "Spatial-Temporal Evolution and Convergence Characteristics of Agricultural Eco-Efficiency in China from a Low-Carbon Perspective," Sustainability, MDPI, vol. 14(24), pages 1-24, December.
    9. Mohsen Afsharian & Heinz Ahn, 2017. "Multi-period productivity measurement under centralized management with an empirical illustration to German saving banks," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 881-911, July.
    10. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2019. "Is Social Capital Green? Cultural Features and Environmental Performance in the European Union," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(3), pages 795-822, March.
    11. Barnabé Walheer, 2022. "Global Malmquist and cost Malmquist indexes for group comparison," Journal of Productivity Analysis, Springer, vol. 58(1), pages 75-93, August.
    12. Víctor Giménez & Claudio Thieme & Diego Prior & Emili Tortosa-Ausina, 2019. "Comparing the Performance of National Educational Systems: Inequality Versus Achievement?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(2), pages 581-609, January.
    13. Manello, Alessandro, 2017. "Productivity growth, environmental regulation and win–win opportunities: The case of chemical industry in Italy and Germany," European Journal of Operational Research, Elsevier, vol. 262(2), pages 733-743.
    14. Zuoren Sun & Chao An & Huachen Sun, 2018. "Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China," Sustainability, MDPI, vol. 10(7), pages 1-28, July.
    15. Bonfiglio, Andrea & Arzeni, Andrea & Bodini, Antonella, 2017. "Assessing eco-efficiency of arable farms in rural areas," Agricultural Systems, Elsevier, vol. 151(C), pages 114-125.
    16. Ke Wang & Yujiao Xian & Yi-Ming Wei & Zhimin Huang, 2016. "Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function," CEEP-BIT Working Papers 91, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    17. Lan-Bing Li & Cong-Cong Zhang & Jin-Li Hu & Ching-Ren Chiu, 2021. "Disaggregate productivity growth sources of regional industries in China," Empirical Economics, Springer, vol. 60(3), pages 1531-1557, March.
    18. Jens J. Krüger & Moritz Tarach, 2022. "Greenhouse Gas Emission Reduction Potentials in Europe by Sector: A Bootstrap-Based Nonparametric Efficiency Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(4), pages 867-898, April.
    19. Mohsen Afsharian & Heinz Ahn, 2015. "The overall Malmquist index: a new approach for measuring productivity changes over time," Annals of Operations Research, Springer, vol. 226(1), pages 1-27, March.
    20. Christian Stetter & Johannes Sauer, 2022. "Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 617-647, March.

    More about this item

    Keywords

    Environmental Performance; infeasible solution; slacks; non- radial BML-DEA model;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

    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:pra:mprapa:55380. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.