lynx   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v40y2019i4p101-128.html
   My bibliography  Save this article

Can China’s Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector

Author

Listed:
  • Shuai Shao
  • Zhenbing Yang
  • Lili Yang
  • Shuang Ma
Abstract
As part of the country’s efforts to achieve green development, China implemented a mandatory energy intensity reduction target in its 11th “Five-Year Plan (FYP)†in 2006, and then began to roll out a series of relevant measures. However, existing studies have paid little attention to the actual effects of China’s energy intensity constraint policy (EICP). In this paper, using panel data from China’s 36 industrial sub-sectors covering the years from 2001 to 2014, we adopt the difference-in-differences (DID) method to investigate for the first time the EICP’s (marginal) effect on total factor energy efficiency growth (TFEEG). We also estimate the superposition effect caused by the introduction of a carbon intensity constraint policy (CICP) on TFEEG, through the difference-in-difference-in-differences (DDD) strategy. Finally, using counterfactual, re-grouping and quasi-DID analyses, we conduct a series of robustness tests of the empirical results. The results show that the TFEEG in China’s industrial sector experienced an overall declining trend between 2001 and 2014. The implementation of the EICP has had a significantly negative effect on the improvement of the TFEEG of sub-sectors with higher levels of energy intensity. After the implementation of the EICP, the TFEEG rate of these sub-sectors declined by 4.31%, compared to the rate of the other sub-sectors. The results of a series of robustness tests indicate that such a negative effect is credible. The marginal effect in the first two years after the implementation of the EICP was significantly negative, while the superposition effect of the introduction of a CICP on industrial TFEEG remained negative. Thus, the Chinese government should reinforce the implementation of energy-saving policies by introducing additional market-oriented auxiliary policies to propel the green development transformation of China’s industrial sector.

Suggested Citation

  • Shuai Shao & Zhenbing Yang & Lili Yang & Shuang Ma, 2019. "Can China’s Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector," The Energy Journal, , vol. 40(4), pages 101-128, July.
    • Handle: RePEc:sae:enejou:v:40:y:2019:i:4:p:101-128
    DOI: 10.5547/01956574.40.4.ssha
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.40.4.ssha
    Download Restriction: no
    File URL: https://libkey.io/10.5547/01956574.40.4.ssha?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    2. 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.
    3. Ohene-Asare, Kwaku & Turkson, Charles & Afful-Dadzie, Anthony, 2017. "Multinational operation, ownership and efficiency differences in the international oil industry," Energy Economics, Elsevier, vol. 68(C), pages 303-312.
    4. Ma, Chunbo, 2014. "A multi-fuel, multi-sector and multi-region approach to index decomposition: An application to China's energy consumption 1995–2010," Energy Economics, Elsevier, vol. 42(C), pages 9-16.
    5. Shahbaz, Muhammad & Nasreen, Samia & Abbas, Faisal & Anis, Omri, 2015. "Does foreign direct investment impede environmental quality in high-, middle-, and low-income countries?," Energy Economics, Elsevier, vol. 51(C), pages 275-287.
    6. Shao, Shuai & Yang, Lili & Yu, Mingbo & Yu, Mingliang, 2011. "Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994-2009," Energy Policy, Elsevier, vol. 39(10), pages 6476-6494, October.
    7. Wang, H. & Ang, B.W. & Wang, Q.W. & Zhou, P., 2017. "Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach," Energy Economics, Elsevier, vol. 62(C), pages 70-78.
    8. 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.
    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. Yuxin Ning & Jifeng Duan, 2024. "Can the Environmental Protection Tax Promote the Improvement of Energy Efficiency? Evidence from Prefecture-Level City Data in China," Sustainability, MDPI, vol. 16(23), pages 1-24, November.
    2. Zhang, Qianxiang & Lin, Boqiang, 2024. "What does clean energy attract? Evidence from the transfer structure of energy-intensive projects in China," Renewable Energy, Elsevier, vol. 228(C).
    3. Liu, Xinheng & Pan, Sishi & Li, Shuxian & Yang, Xin & Huang, Chuangxia, 2024. "Unraveling the causal impact: Oil price uncertainty on firms’ productivity in China," Resources Policy, Elsevier, vol. 96(C).
    4. Rongbing Huang & Xiaomin Zou, 2025. "Accountability audits of natural resources and industrial green total factor productivity: evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-17, December.
    5. Wan, Yaqi & Li, Zhensheng, 2025. "Environmental governance shock and industrial intelligence upgrading: Insights from machine-labor substitution," International Review of Financial Analysis, Elsevier, vol. 102(C).
    6. Xiongfeng Pan & Sai Yuan & Malin Song & Mengna Li & Yuqing Wang, 2024. "Decomposition of the growth drivers and its spatial distribution characteristics of responsible innovation: A study of Chinese industrial enterprises," Asia Pacific Journal of Management, Springer, vol. 41(3), pages 1061-1084, September.
    7. Yu Zhao & Yunning Ma & Yongrok Choi & Ning Zhang, 2024. "The Effects of The Multi-Target Policy on Green Productivity: Evidence from China’s Fossil Fuel Power Plants," The Energy Journal, , vol. 45(3), pages 177-202, May.

    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. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    2. Yang, Zhenbing & Shao, Shuai & Yang, Lili & Liu, Jianghua, 2017. "Differentiated effects of diversified technological sources on energy-saving technological progress: Empirical evidence from China's industrial sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1379-1388.
    3. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
    4. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    5. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    6. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    7. Tabak, Benjamin M. & Miranda, Rogério Boueri & Fazio, Dimas M., 2013. "A geographically weighted approach to measuring efficiency in panel data: The case of US saving banks," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3747-3756.
    8. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    9. Martini, Gianmaria & Scotti, Davide & Viola, Domenico & Vittadini, Giorgio, 2020. "Persistent and temporary inefficiency in airport cost function: An application to Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 999-1019.
    10. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    11. Iva Tomić, 2014. "Regional matching (in)efficiency on the Croatian labour market," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 64(3), pages 287-312, September.
    12. Yang, Yuan & Cai, Wenjia & Wang, Can, 2014. "Industrial CO2 intensity, indigenous innovation and R&D spillovers in China’s provinces," Applied Energy, Elsevier, vol. 131(C), pages 117-127.
    13. Zheng, Xuemei & Wu, Chengkuan & He, Shijun, 2021. "Impacts of China's differential electricity pricing on the productivity of energy-intensive industries," Energy Economics, Elsevier, vol. 94(C).
    14. Kai Sun & Ruhul Salim, 2020. "A semiparametric stochastic input distance frontier model with application to the Indonesian banking industry," Journal of Productivity Analysis, Springer, vol. 54(2), pages 139-156, December.
    15. Thomas Graaff, 2020. "On the estimation of spatial stochastic frontier models: an alternative skew-normal approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 267-285, April.
    16. Agasisti, Tommaso & Barra, Cristian & Zotti, Roberto, 2016. "Evaluating the efficiency of Italian public universities (2008–2011) in presence of (unobserved) heterogeneity," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 47-58.
    17. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2017. "Determinants of transient and persistent hospital efficiency: The case of Italy," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 5-22, September.
    18. Tian, Xu & Sun, Feifei & Zhou, Yingheng, 2015. "Technical Efficiency and Its Determinants in China's Hog Production," 2015 Conference, August 9-14, 2015, Milan, Italy 212718, International Association of Agricultural Economists.
    19. Emilie Caldeira & Alou Adessé Dama & Ali Compaoré & Mario Mansour & Grégoire Rota-Graziosi, 2020. "Tax effort in Sub-Saharan African countries : evidence from a new dataset," CERDI Working papers hal-02543162, HAL.
    20. Martinez-Cillero, Maria & Lawless, Martina & O'Toole, Conor, 2023. "Analysing SME investment, financing constraints and its determinants. A stochastic frontier approach," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 578-588.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:sae:enejou:v:40:y:2019:i:4:p:101-128. 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: SAGE Publications (email available below). General contact details of provider: .

    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.
    Лучший частный хостинг