IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v62y2013icp354-362.html
   My bibliography  Save this article

The potential estimation and factor analysis of China′s energy conservation on thermal power industry

Author

Listed:
  • Lin, Boqiang
  • Yang, Lisha

Abstract

At present, researches about energy conservation are focused on prediction. But there are few researches focused on the estimation of effective input and energy conservation potential, and there has been even no research on energy conservation of thermal power industry of China. This paper will try to fill in such a blank. Panel data on Chinese thermal power industry over 2005–2010 are established, and we adopt the stochastic frontier analysis approach to estimate the energy saving potential of thermal power industry. The results are as follows: (1) the average efficiency of energy inputs in China′s thermal power industry over 2005–2010 was about 0.85, and cumulative energy saving potential equals to 551.04 (Mtce); (2) by improving the non-efficiency factors, the relatively backward inland cities could achieve higher energy saving in thermal power industry; (3) the energy input efficiency of Eastern China Grid is shown to be the highest; (4) in order to realize the energy-saving goal of thermal power industry, one important policy method the government should adopt is to conduct a market-oriented reform in power industry and break the state-owned monopoly to provide incentives for private and foreign direct investment in thermal power sector.

Suggested Citation

  • Lin, Boqiang & Yang, Lisha, 2013. "The potential estimation and factor analysis of China′s energy conservation on thermal power industry," Energy Policy, Elsevier, vol. 62(C), pages 354-362.
  • Handle: RePEc:eee:enepol:v:62:y:2013:i:c:p:354-362
    DOI: 10.1016/j.enpol.2013.07.079
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421513007222
    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. Kumbhakar, Subal C., 1991. "Estimation of technical inefficiency in panel data models with firm- and time-specific effects," Economics Letters, Elsevier, vol. 36(1), pages 43-48, May.
    2. Stern, David I., 2012. "Modeling international trends in energy efficiency," Energy Economics, Elsevier, vol. 34(6), pages 2200-2208.
    3. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    4. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    5. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    6. David Popp, 2002. "Induced Innovation and Energy Prices," American Economic Review, American Economic Association, vol. 92(1), pages 160-180, March.
    7. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    8. Wang, Hung-Jen, 2003. "A Stochastic Frontier Analysis of Financing Constraints on Investment: The Case of Financial Liberalization in Taiwan," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 406-419, July.
    9. Lin, Boqiang & Wu, Ya & Zhang, Li, 2012. "Electricity saving potential of the power generation industry in China," Energy, Elsevier, vol. 40(1), pages 307-316.
    10. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    11. Stern, David I., 2010. "Modeling International Trends in Energy Efficiency and Carbon Emissions," Research Reports 94950, Australian National University, Environmental Economics Research Hub.
    12. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    13. Lin, Boqiang & Zhang, Li & Wu, Ya, 2012. "Evaluation of electricity saving potential in China's chemical industry based on cointegration," Energy Policy, Elsevier, vol. 44(C), pages 320-330.
    14. Kneller, Richard & Andrew Stevens, Philip, 2003. "The specification of the aggregate production function in the presence of inefficiency," Economics Letters, Elsevier, vol. 81(2), pages 223-226, November.
    15. Kumbhakar, Subal C. & Wang, Hung-Jen, 2005. "Estimation of growth convergence using a stochastic production frontier approach," Economics Letters, Elsevier, vol. 88(3), pages 300-305, September.
    16. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    17. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. Ma, Xuejiao & Wang, Yong & Wang, Chen, 2017. "Low-carbon development of China's thermal power industry based on an international comparison: Review, analysis and forecast," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 942-970.
    2. Akihiro Otsuka & Mika Goto, 2015. "Estimation and determinants of energy efficiency in Japanese regional economies," Regional Science Policy & Practice, Wiley Blackwell, vol. 7(2), pages 89-101, June.
    3. Boqiang Lin & Zihan Zhang & Fei Ge, 2017. "Energy Conservation in China’s Cement Industry," Sustainability, MDPI, Open Access Journal, vol. 9(4), pages 1-17, April.
    4. Dong, Kangyin & Sun, Renjin & Hochman, Gal & Li, Hui, 2018. "Energy intensity and energy conservation potential in China: A regional comparison perspective," Energy, Elsevier, vol. 155(C), pages 782-795.
    5. Lijun Zeng & Laijun Zhao & Qin Wang & Bingcheng Wang & Yuan Ma & Wei Cui & Yujing Xie, 2018. "Modeling Interprovincial Cooperative Energy Saving in China: An Electricity Utilization Perspective," Energies, MDPI, Open Access Journal, vol. 11(1), pages 1-25, January.
    6. Zhou, Kaile & Yang, Shanlin & Shen, Chao & Ding, Shuai & Sun, Chaoping, 2015. "Energy conservation and emission reduction of China’s electric power industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 10-19.
    7. Yang, Lisha & Lin, Boqiang, 2016. "Carbon dioxide-emission in China׳s power industry: Evidence and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 258-267.
    8. Chen, Hao & Kang, Jia-Ning & Liao, Hua & Tang, Bao-Jun & Wei, Yi-Ming, 2017. "Costs and potentials of energy conservation in China's coal-fired power industry: A bottom-up approach considering price uncertainties," Energy Policy, Elsevier, vol. 104(C), pages 23-32.
    9. Wang, Ke & Zhang, Xian & Yu, Xueying & Wei, Yi-Ming & Wang, Bin, 2016. "Emissions trading and abatement cost savings: An estimation of China's thermal power industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1005-1017.
    10. Zhang, Shanshan & Lundgren, Tommy & Zhou, Wenchao, 2016. "Energy efficiency in Swedish industry," Energy Economics, Elsevier, vol. 55(C), pages 42-51.
    11. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    12. Tang, Baojun & Li, Ru & Yu, Biying & An, Runying & Wei, Yi-Ming, 2018. "How to peak carbon emissions in China's power sector: A regional perspective," Energy Policy, Elsevier, vol. 120(C), pages 365-381.
    13. Wang, Ke & Wang, Shanshan & Liu, Lei & Yue, Hui & Zhang, Ruiqin & Tang, Xiaoyan, 2016. "Environmental co-benefits of energy efficiency improvement in coal-fired power sector: A case study of Henan Province, China," Applied Energy, Elsevier, vol. 184(C), pages 810-819.
    14. Li, Ming-Jia & Tao, Wen-Quan, 2017. "Review of methodologies and polices for evaluation of energy efficiency in high energy-consuming industry," Applied Energy, Elsevier, vol. 187(C), pages 203-215.
    15. Lin, Boqiang & Zhao, Hongli, 2016. "Technological progress and energy rebound effect in China׳s textile industry: Evidence and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 173-181.
    16. Lin, Boqiang & Yang, Lisha, 2014. "Efficiency effect of changing investment structure on China׳s power industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 403-411.

    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:enepol:v:62:y:2013:i:c:p:354-362. 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/locate/enpol .

    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.