IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v168y2016icp351-363.html
   My bibliography  Save this article

Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model

Author

Listed:
  • Li, Ke
  • Lin, Boqiang

Abstract

This study introduces an improved Malmquist–Luenberger productivity index to measure the green productivity growth of China’s manufacturing sector during the 11th Five-Year Period (2006–2010). A three-stage data envelopment analysis model is adopted to measure the effects of government measures on green productivity growth. The main results are: (i) the average value of the Malmquist productivity index is 1.045 and the average value of the Malmquist–Luenberger productivity index accounting for CO2 emissions is 1.027. This indicates imply that the relatively higher values of the former are at the expense of substantial energy usage and CO2 emissions; (ii) China’s energy-saving policies and measures, such as mass promotion and adoption of energy-saving technology, closure and elimination of obsolete production capacity, and reduction of over-capacity are important for green development; (iii) after eliminating the effects of environmental influences and statistical noise on output slacks, the adjusted green productivity changes are smaller while the adjusted technical changes are larger than the corresponding initial levels; (iv) the energy conservation policies implemented in China’s manufacturing sector are far from the optimal level, and more stringent enforcement would be conducive for green productivity growth in the manufacturing sector.

Suggested Citation

  • Li, Ke & Lin, Boqiang, 2016. "Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model," Applied Energy, Elsevier, vol. 168(C), pages 351-363.
  • Handle: RePEc:eee:appene:v:168:y:2016:i:c:p:351-363
    DOI: 10.1016/j.apenergy.2016.01.104
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916300927
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nassiri, Seyed Mehdi & Singh, Surendra, 2009. "Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique," Applied Energy, Elsevier, vol. 86(7-8), pages 1320-1325, July.
    2. Chen, Shiyi & Golley, Jane, 2014. "‘Green’ productivity growth in China's industrial economy," Energy Economics, Elsevier, vol. 44(C), pages 89-98.
    3. Wang, Ke & Lu, Bin & Wei, Yi-Ming, 2013. "China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis," Applied Energy, Elsevier, vol. 112(C), pages 1403-1415.
    4. Song, Ma-Lin & Zhang, Lin-Ling & Liu, Wei & Fisher, Ron, 2013. "Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data," Applied Energy, Elsevier, vol. 112(C), pages 1049-1055.
    5. Dale W. Jorgenson & Kevin J. Stiroh, 2000. "Raising the Speed Limit: U.S. Economic Growth in the Information Age," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 31(1), pages 125-236.
    6. Ke, Jing & Price, Lynn & Ohshita, Stephanie & Fridley, David & Khanna, Nina Zheng & Zhou, Nan & Levine, Mark, 2012. "China's industrial energy consumption trends and impacts of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects," Energy Policy, Elsevier, vol. 50(C), pages 562-569.
    7. Zhang, Chunhong & Liu, Haiying & Bressers, Hans Th.A. & Buchanan, Karen S., 2011. "Productivity growth and environmental regulations - accounting for undesirable outputs: Analysis of China's thirty provincial regions using the Malmquist–Luenberger index," Ecological Economics, Elsevier, vol. 70(12), pages 2369-2379.
    8. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    9. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    10. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    11. Cui, Qiang & Li, Ye, 2015. "An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries," Applied Energy, Elsevier, vol. 141(C), pages 209-217.
    12. Fisher-Vanden, Karen & Jefferson, Gary H. & Jingkui, Ma & Jianyi, Xu, 2006. "Technology development and energy productivity in China," Energy Economics, Elsevier, vol. 28(5-6), pages 690-705, November.
    13. Lin, Boqiang & Li, Aijun, 2012. "Impacts of removing fossil fuel subsidies on China: How large and how to mitigate?," Energy, Elsevier, vol. 44(1), pages 741-749.
    14. Wang, Yi-Shu & Xie, Bai-Chen & Shang, Li-Feng & Li, Wen-Hua, 2013. "Measures to improve the performance of China’s thermal power industry in view of cost efficiency," Applied Energy, Elsevier, vol. 112(C), pages 1078-1086.
    15. 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.
    16. Stigson, Peter & Dotzauer, Erik & Yan, Jinyue, 2009. "Improving policy making through government-industry policy learning: The case of a novel Swedish policy framework," Applied Energy, Elsevier, vol. 86(4), pages 399-406, April.
    17. Fang, Chin-Yi & Hu, Jin-Li & Lou, Tze-Kai, 2013. "Environment-adjusted total-factor energy efficiency of Taiwan's service sectors," Energy Policy, Elsevier, vol. 63(C), pages 1160-1168.
    18. 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.
    19. Zhao, Xiaofan & Li, Huimin & Wu, Liang & Qi, Ye, 2014. "Implementation of energy-saving policies in China: How local governments assisted industrial enterprises in achieving energy-saving targets," Energy Policy, Elsevier, vol. 66(C), pages 170-184.
    20. Du, Limin & Yanan, He & Wei, Chu, 2010. "The relationship between oil price shocks and China's macro-economy: An empirical analysis," Energy Policy, Elsevier, vol. 38(8), pages 4142-4151, August.
    21. Li, Ke & Lin, Boqiang, 2015. "How does administrative pricing affect energy consumption and CO2 emissions in China?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 952-962.
    22. Ramanathan, Ramakrishnan, 2005. "An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa," Energy, Elsevier, vol. 30(15), pages 2831-2842.
    23. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    24. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Mohammadi, Ali, 2011. "Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis," Energy, Elsevier, vol. 36(2), pages 909-916.
    25. Hu, Jin-Li & Lio, Mon-Chi & Yeh, Fang-Yu & Lin, Cheng-Hsun, 2011. "Environment-adjusted regional energy efficiency in Taiwan," Applied Energy, Elsevier, vol. 88(8), pages 2893-2899, August.
    26. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    27. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    28. Bai-Chen, Xie & Ying, Fan & Qian-Qian, Qu, 2012. "Does generation form influence environmental efficiency performance? An analysis of China’s power system," Applied Energy, Elsevier, vol. 96(C), pages 261-271.
    29. Li, Ke & Lin, Boqiang, 2015. "Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China," Energy Economics, Elsevier, vol. 48(C), pages 230-241.
    30. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    31. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    32. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    33. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    34. Oh, Dong-hyun & Heshmati, Almas, 2010. "A sequential Malmquist-Luenberger productivity index: Environmentally sensitive productivity growth considering the progressive nature of technology," Energy Economics, Elsevier, vol. 32(6), pages 1345-1355, November.
    35. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    36. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    37. He, Feng & Zhang, Qingzhi & Lei, Jiasu & Fu, Weihui & Xu, Xiaoning, 2013. "Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs," Energy Policy, Elsevier, vol. 54(C), pages 204-213.
    38. Chen, Xia & Wang, Li & Tong, Lige & Sun, Shufeng & Yue, Xianfang & Yin, Shaowu & Zheng, Lifang, 2013. "Energy saving and emission reduction of China's urban district heating," Energy Policy, Elsevier, vol. 55(C), pages 677-682.
    39. Hailu, Atakelty & Veeman, Terrence S., 2000. "Environmentally Sensitive Productivity Analysis of the Canadian Pulp and Paper Industry, 1959-1994: An Input Distance Function Approach," Journal of Environmental Economics and Management, Elsevier, vol. 40(3), pages 251-274, November.
    40. Wei, Yi-Ming & Liao, Hua & Fan, Ying, 2007. "An empirical analysis of energy efficiency in China's iron and steel sector," Energy, Elsevier, vol. 32(12), pages 2262-2270.
    41. Ke Li & Boqiang Lin & Xiying Liu, 2015. "Special: Theme of Clean Coal How Policy Strategies Affect Clean Coal Technology Innovation in China? A Patent-Based Approach," Energy & Environment, , vol. 26(6-7), pages 1015-1033, November.
    42. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    43. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    44. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
    45. Zhou, Nan & Levine, Mark D. & Price, Lynn, 2010. "Overview of current energy-efficiency policies in China," Energy Policy, Elsevier, vol. 38(11), pages 6439-6452, November.
    46. Huang, Chin-wei & Chiu, Yung-ho & Fang, Wei-ta & Shen, Neng, 2014. "Assessing the performance of Taiwan’s environmental protection system with a non-radial network DEA approach," Energy Policy, Elsevier, vol. 74(C), pages 547-556.
    47. Shiyi Chen, 2009. "Engine or drag: Can high energy consumption and CO 2 emission drive the sustainable development of Chinese industry?," Frontiers of Economics in China, Springer;Higher Education Press, vol. 4(4), pages 548-571, December.
    48. Yu-Ying Lin, Eugene & Chen, Ping-Yu & Chen, Chi-Chung, 2013. "Measuring green productivity of country: A generlized metafrontier Malmquist productivity index approach," Energy, Elsevier, vol. 55(C), pages 340-353.
    Full references (including those not matched with items on IDEAS)

    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:eee:appene:v:168:y:2016:i:c:p:351-363. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.