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Is the CO2 Emissions Reduction from Scale Change, Structural Change or Technology Change? Evidence from Non-metallic Sector of 11 Major Economies in 1995-2009

Author

Listed:
  • Jin-Wei Wang
  • Hua Liao
  • Bao-Jun Tang
  • Ruo-Yu Ke
  • Yi-Ming Wei

    (Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology)

Abstract

The contribution of non-metallic sector to global CO2 emissions is increasing. However, there are very few studies on non-metallic sector CO2 emissions from international comparative perspective. This paper proposes an integrated model employing LMDI (Logarithmic Mean Divisia Index) decomposition technique and TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution) method to contribute to the existing literature by filling the gap that the drivers of aggregate and national level non-metallic sector CO2 emissions and its impacts on CO2 emissions reduction have not been estimated by relevant models. First, we analyze drivers of non-metallic sector CO2 emissions in BRIC countries and G7 countries using LMDI decomposition method. Second, we evaluate the low-carbon development of non-metallic sector in the 11 major economies from a comprehensive viewpoint of main drivers using TOPSIS assessment model. Finally, based on the results of the model, this paper presents some implications for the non-metallic sector CO2 emissions reduction and low-carbon development.

Suggested Citation

  • Jin-Wei Wang & Hua Liao & Bao-Jun Tang & Ruo-Yu Ke & Yi-Ming Wei, 2017. "Is the CO2 Emissions Reduction from Scale Change, Structural Change or Technology Change? Evidence from Non-metallic Sector of 11 Major Economies in 1995-2009," CEEP-BIT Working Papers 101, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    • Handle: RePEc:biw:wpaper:101
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    References listed on IDEAS

    as
    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    3. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.
    4. Oda, Junichiro & Akimoto, Keigo & Tomoda, Toshimasa & Nagashima, Miyuki & Wada, Kenichi & Sano, Fuminori, 2012. "International comparisons of energy efficiency in power, steel, and cement industries," Energy Policy, Elsevier, vol. 44(C), pages 118-129.
    5. Ang, B.W & Zhang, F.Q & Choi, Ki-Hong, 1998. "Factorizing changes in energy and environmental indicators through decomposition," Energy, Elsevier, vol. 23(6), pages 489-495.
    6. 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.
    7. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    8. Wang, Bing & Nistor, Ioan & Murty, Tad & Wei, Yi-Ming, 2014. "Efficiency assessment of hydroelectric power plants in Canada: A multi criteria decision making approach," Energy Economics, Elsevier, vol. 46(C), pages 112-121.
    9. Anusha Chari & Peter Blair Henry, 2014. "Learning from the Doers: Developing Country Lessons for Advanced Economy Growth," American Economic Review, American Economic Association, vol. 104(5), pages 260-265, May.
    10. Zhi-Fu Mi & Yi-Ming Wei & Chen-Qi He & Hua-Nan Li & Xiao-Chen Yuan & Hua Liao, 2017. "Regional efforts to mitigate climate change in China: a multi-criteria assessment approach," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(1), pages 45-66, January.
    11. Marcel Timmer & Abdul A. Erumban & Reitze Gouma & Bart Los & Umed Temurshoev & Gaaitzen J. de Vries & I–aki Arto & Valeria Andreoni AurŽlien Genty & Frederik Neuwahl & JosŽ M. Rueda?Cantuche & Joseph , 2012. "The World Input-Output Database (WIOD): Contents, Sources and Methods," IIDE Discussion Papers 20120401, Institue for International and Development Economics.
    12. Sun, J. W., 1998. "Changes in energy consumption and energy intensity: A complete decomposition model," Energy Economics, Elsevier, vol. 20(1), pages 85-100, February.
    13. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    14. Hoekstra, Rutger & van den Bergh, Jeroen C. J. M., 2003. "Comparing structural decomposition analysis and index," Energy Economics, Elsevier, vol. 25(1), pages 39-64, January.
    15. Wang, W.W. & Zhang, M. & Zhou, M., 2011. "Using LMDI method to analyze transport sector CO2 emissions in China," Energy, Elsevier, vol. 36(10), pages 5909-5915.
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    Cited by:

    1. Yao Qian & Lang Sun & Quanyi Qiu & Lina Tang & Xiaoqi Shang & Chengxiu Lu, 2020. "Analysis of CO 2 Drivers and Emissions Forecast in a Typical Industry-Oriented County: Changxing County, China," Energies, MDPI, vol. 13(5), pages 1-21, March.
    2. Xiao, Hao & Sun, Ke-Juan & Bi, Hui-Min & Xue, Jin-Jun, 2019. "Changes in carbon intensity globally and in countries: Attribution and decomposition analysis," Applied Energy, Elsevier, vol. 235(C), pages 1492-1504.
    3. Nayeah Kim & Yun Seop Hwang & Mun Ho Hwang, 2019. "New projection of GHG reduction potentials for Korea’s cement industry and comparison with Roadmap 2030," Energy & Environment, , vol. 30(3), pages 499-521, May.
    4. Simona-Vasilica Oprea & Irina Alexandra Georgescu & Adela Bâra, 2024. "Charting the BRIC countries’ connection of political stability, economic growth, demographics, renewables and CO2 emissions," Economic Change and Restructuring, Springer, vol. 57(5), pages 1-35, October.
    5. Yi-Ming Wei & Jin-Wei Wang & Tianqi Chen & Bi-Ying Yu & Hua Liao, 2018. "Frontiers of Low-Carbon Technologies: Results from Bibliographic Coupling with Sliding Window," CEEP-BIT Working Papers 116, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    6. Moutinho, Victor & Madaleno, Mara & Inglesi-Lotz, Roula & Dogan, Eyup, 2018. "Factors affecting CO2 emissions in top countries on renewable energies: A LMDI decomposition application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 605-622.
    7. Li-Jing Liu & Qiao-Mei Liang & Felix Creutzig & Nan Cheng & Lan-Cui Liu, 2021. "Electricity end-use and construction activity are key leverage points for co-controlling greenhouse gases and local pollution in China," Climatic Change, Springer, vol. 167(1), pages 1-22, July.
    8. Hongli Zhang & Lei Shen & Shuai Zhong & Ayman Elshkaki, 2020. "Economic Structure Transformation and Low-Carbon Development in Energy-Rich Cities: The Case of the Contiguous Area of Shanxi and Shaanxi Provinces, and Inner Mongolia Autonomous Region of China," Sustainability, MDPI, vol. 12(5), pages 1-14, March.

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    More about this item

    Keywords

    CO2 emissions; Non-metallic sector; Cement; Logarithmic mean divisia index decomposition; WIOD database;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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