IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v211y2020ics036054422031834x.html
   My bibliography  Save this article

Policy inducement effect in energy efficiency: An empirical analysis of China

Author

Listed:
  • Xin-gang, Zhao
  • Xin, Meng
  • Ying, Zhou
  • Pei-ling, Li

Abstract

Energy efficiency improvement is one of the most effective means to achieve energy conservation. The success of energy conservation depends on scientific policy design. So what is the impact of existing policies on energy efficiency? What types of policy tools have the most significant impact on energy efficiency? In response to these problems, this paper took the energy conservation policies promulgated by the Chinese government over the years as samples. This paper used the ridge regression model to analyze policy inducement effect in energy efficiency based on the data envelopment analysis (DEA) model and the policy text evaluation model. The results show that: (1) Energy conservation policies have a positive influence on improving energy efficiency. (2) Among the policy tools, economic incentive tools have the most significant influence on the increase in energy efficiency. Therefore, the government should emphasize the use of economic incentive policy tools and coordinate the relationship between various policy tools to achieve China’s stated energy conservation goals.

Suggested Citation

  • Xin-gang, Zhao & Xin, Meng & Ying, Zhou & Pei-ling, Li, 2020. "Policy inducement effect in energy efficiency: An empirical analysis of China," Energy, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:energy:v:211:y:2020:i:c:s036054422031834x
    DOI: 10.1016/j.energy.2020.118726
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422031834X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.118726?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
    ---><---

    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. Charlier, Dorothée & Risch, Anna, 2012. "Evaluation of the impact of environmental public policy measures on energy consumption and greenhouse gas emissions in the French residential sector," Energy Policy, Elsevier, vol. 46(C), pages 170-184.
    2. Galloway, Emily & Johnson, Erik Paul, 2016. "Teaching an old dog new tricks: Firm learning from environmental regulation," Energy Economics, Elsevier, vol. 59(C), pages 1-10.
    3. 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.
    4. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    5. Bukarica, Vesna & Robić, Slavica, 2013. "Implementing energy efficiency policy in Croatia: Stakeholder interactions for closing the gap," Energy Policy, Elsevier, vol. 61(C), pages 414-422.
    6. 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.
    7. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    8. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    9. He, K. & Lei, Y. & Pan, X. & Zhang, Y. & Zhang, Q. & Chen, D., 2010. "Co-benefits from energy policies in China," Energy, Elsevier, vol. 35(11), pages 4265-4272.
    10. Li, Li & Tan, Zhongfu & Wang, Jianhui & Xu, Jun & Cai, Chengkai & Hou, Yong, 2011. "Energy conservation and emission reduction policies for the electric power industry in China," Energy Policy, Elsevier, vol. 39(6), pages 3669-3679, June.
    11. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    12. Zhang, Jian & Zhang, Wei & Song, Qi & Li, Xin & Ye, Xuanting & Liu, Yu & Xue, Yawei, 2020. "Can energy saving policies drive firm innovation behaviors? - Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    13. Liao, Zhongju, 2016. "The evolution of wind energy policies in China (1995–2014): An analysis based on policy instruments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 464-472.
    14. DeCanio, Stephen J., 1993. "Barriers within firms to energy-efficient investments," Energy Policy, Elsevier, vol. 21(9), pages 906-914, September.
    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. Madurai Elavarasan, Rajvikram & Nadarajah, Mithulananthan & Pugazhendhi, Rishi & Sinha, Avik & Gangatharan, Sivasankar & Chiaramonti, David & Abou Houran, Mohamad, 2023. "The untold subtlety of energy consumption and its influence on policy drive towards Sustainable Development Goal 7," Applied Energy, Elsevier, vol. 334(C).
    2. Sheng, Pengfei & Liu, Weiliang, 2024. "Does the government's green commitment matter for energy conservation in China? The role of public spending," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1061-1073.
    3. Xiong, Yongqing & Cheng, Qian, 2023. "Effects of new energy vehicle adoption on provincial energy efficiency in China: From the perspective of regional imbalances," Energy, Elsevier, vol. 281(C).

    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. 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.
    2. Su, Hongwei & Liang, Biming, 2021. "The impact of regional market integration and economic opening up on environmental total factor energy productivity in Chinese provinces," Energy Policy, Elsevier, vol. 148(PA).
    3. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    4. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    5. Kounetas, Konstantinos & Stergiou, Eirini, 2019. "Technology heterogeneity in European industries' energy efficiency performance. The role of climate, greenhouse gases, path dependence and energy mix," MPRA Paper 92314, University Library of Munich, Germany.
    6. Fan, Di & Peng, Bo & Wu, Jianxin & Zhang, ZhongXiang, 2024. "The convergence of total-factor energy efficiency across Chinese cities: A distribution dynamics approach," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 406-416.
    7. Wang, Zhaohua & Zhang, Bin & Liu, Tongfan, 2016. "Empirical analysis on the factors influencing national and regional carbon intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 34-42.
    8. Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.
    9. Hu, Jin-Li & Chang, Ming-Chung & Tsay, Hui-Wen, 2017. "The congestion total-factor energy efficiency of regions in Taiwan," Energy Policy, Elsevier, vol. 110(C), pages 710-718.
    10. Shujing Yue & Yang Yang & Jun Shao & Yuting Zhu, 2016. "International Comparison of Total Factor Ecology Efficiency: Focused on G20 from 1999–2013," Sustainability, MDPI, vol. 8(11), pages 1-13, November.
    11. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    12. Mian Yang & Zheng Hu & Jiahai Yuan, 2016. "The recent history and successes of China's energy efficiency policy," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(6), pages 715-730, November.
    13. 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.
    14. Zhou, Xiaoyan & Zhang, Jie & Li, Junpeng, 2013. "Industrial structural transformation and carbon dioxide emissions in China," Energy Policy, Elsevier, vol. 57(C), pages 43-51.
    15. 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.
    16. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    17. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    18. Shuangjie Li & Li Li & Liming Wang, 2020. "2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry," Energies, MDPI, vol. 14(1), pages 1-17, December.
    19. Pillai N., Vijayamohanan, 2019. "Measuring Energy Efficiency: An Application of Data Envelopment Analysis to Power Sector in Kerala," MPRA Paper 101945, University Library of Munich, Germany.
    20. Antunes, Jorge Junio Moreira & Neves, Juliana Campos & Elmor, Larissa Rosa Carneiro & Araujo, Michel Fontaine Reis De & Wanke, Peter Fernandes & Tan, Yong, 2023. "A new perspective on the U.S. energy efficiency: The political context," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).

    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:energy:v:211:y:2020:i:c:s036054422031834x. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.