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

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  • 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
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    1. 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.
    2. 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.
    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    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.
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    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).

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