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Measuring the Energy Saving and CO2 Emissions Reduction Potential Under China’s Belt and Road Initiative


  • Yue-Jun Zhang

    () (Hunan University
    Hunan University)

  • Yan-Lin Jin

    (Hunan University
    Hunan University)

  • Bo Shen

    (Lawrence Berkeley National Laboratory)


Belt and Road Initiative (BRI) countries are major energy producers and consumers in the world, and they have enormous potential for energy cooperation, energy saving, and CO2 emissions reduction due to their various resource endowments. However, little quantitative research has been conducted under the BRI in the same framework. Therefore, by developing a data envelopment analysis optimisation model combined with the window analysis method, this paper investigates the energy performance of BRI countries for the period from 1995 to 2015, and evaluate the potential of energy saving and CO2 emissions reduction for each BRI country. The results show that, first, the average energy performance of 56 BRI countries is about 0.69, with evident difference across regions and countries. Specifically, in Sub-Saharan Africa and Europe and Central Asia, energy performance is relatively lower, and their averages are 0.59 and 0.60, respectively; in particular, Ukraine has the lowest energy performance among the 56 BRI countries (0.24); while the energy performance in Middle East and North Africa and South Asia appears relatively higher (0.80 and 0.89, respectively). Second, these 56 BRI countries have great energy saving potential, about 9.95 billion metric tonnes of oil equivalent from 1995 to 2015. Among them, Europe and Central Asia, East Asia and Pacific, and Middle East and North Africa make relatively larger contribution. Finally, these 56 BRI countries may produce potential CO2 emissions reduction of 50.87 billion metric tonnes during the study period, and Europe and Central Asia and East Asia and Pacific contribute the most (45.18% and 25.53%, respectively).

Suggested Citation

  • Yue-Jun Zhang & Yan-Lin Jin & Bo Shen, 2020. "Measuring the Energy Saving and CO2 Emissions Reduction Potential Under China’s Belt and Road Initiative," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1095-1116, April.
  • Handle: RePEc:kap:compec:v:55:y:2020:i:4:d:10.1007_s10614-018-9839-0
    DOI: 10.1007/s10614-018-9839-0

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    References listed on IDEAS

    1. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    2. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    3. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    4. Jian-Xin Wu & Ling-Yun He, 2017. "The Distribution Dynamics of Carbon Dioxide Emissions Intensity across Chinese Provinces: A Weighted Approach," Sustainability, MDPI, Open Access Journal, vol. 9(1), pages 1-19, January.
    5. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    6. Oropeza-Perez, Ivan & Østergaard, Poul Alberg, 2014. "Energy saving potential of utilizing natural ventilation under warm conditions – A case study of Mexico," Applied Energy, Elsevier, vol. 130(C), pages 20-32.
    7. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    8. Yanni Yu & Yongrok Choi, 2015. "Measuring Environmental Performance Under Regional Heterogeneity in China: A Metafrontier Efficiency Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 375-388, October.
    9. A S Camanho & R G Dyson, 1999. "Efficiency, size, benchmarks and targets for bank branches: an application of data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(9), pages 903-915, September.
    10. Turan Katircioglu, Salih, 2013. "Interactions between energy and imports in Singapore: Empirical evidence from conditional error correction models," Energy Policy, Elsevier, vol. 63(C), pages 514-520.
    11. Sheng, Yu & Shi, Xunpeng, 2013. "Energy market integration and equitable growth across countries," Applied Energy, Elsevier, vol. 104(C), pages 319-325.
    12. Du, Julan & Zhang, Yifei, 2018. "Does One Belt One Road initiative promote Chinese overseas direct investment?," China Economic Review, Elsevier, vol. 47(C), pages 189-205.
    13. 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.
    14. Yang, Tian-Jian & Zhang, Yue-Jun & Huang, Jin & Peng, Ruo-Hong, 2013. "Estimating the energy saving potential of telecom operators in China," Energy Policy, Elsevier, vol. 61(C), pages 448-459.
    15. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    16. Bian, Yiwen & He, Ping & Xu, Hao, 2013. "Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach," Energy Policy, Elsevier, vol. 63(C), pages 962-971.
    17. Zhang, Yue-Jun & Hao, Jun-Fang & Song, Juan, 2016. "The CO2 emission efficiency, reduction potential and spatial clustering in China’s industry: Evidence from the regional level," Applied Energy, Elsevier, vol. 174(C), pages 213-223.
    18. Beirne, John & Beulen, Christian & Liu, Guy & Mirzaei, Ali, 2013. "Global oil prices and the impact of China," China Economic Review, Elsevier, vol. 27(C), pages 37-51.
    19. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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    1. Liu, Haiyue & Wang, Yile & Jiang, Jie & Wu, Peng, 2020. "How green is the “Belt and Road Initiative”? – Evidence from Chinese OFDI in the energy sector," Energy Policy, Elsevier, vol. 145(C).

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