[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v72y2014icp168-179.html
   My bibliography  Save this article

How much CO2 emissions will be reduced through industrial structure change if China focuses on domestic rather than international welfare?

Author

Listed:
  • Zhu, Yongbin
  • Shi, Yajuan
  • Wang, Zheng
Abstract
The current energy-intensive industrial structure is one of the reasons why China has emitted a large amount of CO2. This paper inherited the theory of Keynes and constructed a MIDO (Multi-sector Inter-temporal Dynamic Optimization) model with which we compared two distinct evolution trajectories of industrial structures that are oriented toward the conventional international preference and the domestic genuine preference. Furthermore, we estimated the CO2 emissions that can be reduced by industrial structure changes after the preference transition. Our simulation indicates that sectors such as Transport, Heavy Manufacturing, Oil Production, Light Manufacturing, Chemicals and Metals grow faster, and their share of the total output expands under the international preference pattern, while sectors such as Other Services, Transport, Agriculture, Construction, and Food & Clothes Manufacturing experience enlarged output shares in the domestic preference pattern. Consequently, China will conserve 21.7 Gtoe or 33.2 Gtoe of energy and save 9.89 GtC or 15.6 GtC of CO2 emissions (equivalently reducing them by 15% or 16.5%, respectively) through an industrial structure transition from an international pattern to a domestic pattern, corresponding to the “C15” and “C20” catch-up strategies, where the sectoral energy intensity of China reaches the currently most efficient level in 15 or 20 years.

Suggested Citation

  • Zhu, Yongbin & Shi, Yajuan & Wang, Zheng, 2014. "How much CO2 emissions will be reduced through industrial structure change if China focuses on domestic rather than international welfare?," Energy, Elsevier, vol. 72(C), pages 168-179.
  • Handle: RePEc:eee:energy:v:72:y:2014:i:c:p:168-179
    DOI: 10.1016/j.energy.2014.05.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214005714
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2014.05.022?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. André Lorentz & Maria Savona, 2009. "Evolutionary micro-dynamics and changes in the economic structure," Springer Books, in: Uwe Cantner & Jean-Luc Gaffard & Lionel Nesta (ed.), Schumpeterian Perspectives on Innovation, Competition and Growth, pages 137-160, Springer.
    2. Liao, Hua & Fan, Ying & Wei, Yi-Ming, 2007. "What induced China's energy intensity to fluctuate: 1997-2006?," Energy Policy, Elsevier, vol. 35(9), pages 4640-4649, September.
    3. A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
    4. Wei, Taoyuan, 2010. "A general equilibrium view of global rebound effects," Energy Economics, Elsevier, vol. 32(3), pages 661-672, May.
    5. Canyurt, Olcay Ersel & Ozturk, Harun Kemal, 2008. "Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey," Energy Policy, Elsevier, vol. 36(7), pages 2562-2569, July.
    6. Zha, Donglan & Zhou, Dequn & Ding, Ning, 2009. "The contribution degree of sub-sectors to structure effect and intensity effects on industry energy intensity in China from 1993 to 2003," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 895-902, May.
    7. Liu, Na & Ang, B.W., 2007. "Factors shaping aggregate energy intensity trend for industry: Energy intensity versus product mix," Energy Economics, Elsevier, vol. 29(4), pages 609-635, July.
    8. Lin, Boqiang & Yang, Fang & Liu, Xia, 2013. "A study of the rebound effect on China's current energy conservation and emissions reduction: Measures and policy choices," Energy, Elsevier, vol. 58(C), pages 330-339.
    9. Nordhaus, William D & Yang, Zili, 1996. "A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies," American Economic Review, American Economic Association, vol. 86(4), pages 741-765, September.
    10. Wang, H. & Zhou, P. & Zhou, D.Q., 2012. "An empirical study of direct rebound effect for passenger transport in urban China," Energy Economics, Elsevier, vol. 34(2), pages 452-460.
    11. X. Q. Liu & B. W. Ang & H.L. Ong, 1992. "The Application of the Divisia Index to the Decomposition of Changes in Industrial Energy Consumption," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 161-178.
    12. Kahrl, Fredrich & Roland-Holst, David, 2008. "Energy and exports in China," China Economic Review, Elsevier, vol. 19(4), pages 649-658, December.
    13. Valentina Bosetti & Emanuele Massetti & Massimo Tavoni, 2007. "The WITCH Model. Structure, Baseline, Solutions," Working Papers 2007.10, Fondazione Eni Enrico Mattei.
    14. Ang, B. W., 1995. "Multilevel decomposition of industrial energy consumption," Energy Economics, Elsevier, vol. 17(1), pages 39-51, January.
    15. Fisher-Vanden, Karen & Jefferson, Gary H. & Liu, Hongmei & Tao, Quan, 2004. "What is driving China's decline in energy intensity?," Resource and Energy Economics, Elsevier, vol. 26(1), pages 77-97, March.
    16. André Lorentz & Maria Savona, 2008. "Evolutionary Micro-dynamics and Changes in the Economic Structure," Working Papers hal-00279238, HAL.
    17. Manne, Alan & Mendelsohn, Robert & Richels, Richard, 1995. "MERGE : A model for evaluating regional and global effects of GHG reduction policies," Energy Policy, Elsevier, vol. 23(1), pages 17-34, January.
    18. Geem, Zong Woo & Roper, William E., 2009. "Energy demand estimation of South Korea using artificial neural network," Energy Policy, Elsevier, vol. 37(10), pages 4049-4054, October.
    19. Weber, Christopher L. & Peters, Glen P. & Guan, Dabo & Hubacek, Klaus, 2008. "The contribution of Chinese exports to climate change," Energy Policy, Elsevier, vol. 36(9), pages 3572-3577, September.
    20. Assareh, E. & Behrang, M.A. & Assari, M.R. & Ghanbarzadeh, A., 2010. "Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran," Energy, Elsevier, vol. 35(12), pages 5223-5229.
    21. Zhang, ZhongXiang, 2003. "Why did the energy intensity fall in China's industrial sector in the 1990s? The relative importance of structural change and intensity change," Energy Economics, Elsevier, vol. 25(6), pages 625-638, November.
    22. Lin, Boqiang & Liu, Xia, 2012. "Dilemma between economic development and energy conservation: Energy rebound effect in China," Energy, Elsevier, vol. 45(1), pages 867-873.
    23. Yu, Shi-wei & Zhu, Ke-jun, 2012. "A hybrid procedure for energy demand forecasting in China," Energy, Elsevier, vol. 37(1), pages 396-404.
    24. Manfred Lenzen & Daniel Moran & Keiichiro Kanemoto & Arne Geschke, 2013. "Building Eora: A Global Multi-Region Input-Output Database At High Country And Sector Resolution," Economic Systems Research, Taylor & Francis Journals, vol. 25(1), pages 20-49, March.
    25. André Lorentz & Maria Savona, 2009. "Evolutionary micro-dynamics and changes in the economic structure," Springer Books, in: Uwe Cantner & Jean-Luc Gaffard & Lionel Nesta (ed.), Schumpeterian Perspectives on Innovation, Competition and Growth, pages 137-160, Springer.
    26. Zheng, Yuhua & Luo, Dongkun, 2013. "Industrial structure and oil consumption growth path of China: Empirical evidence," Energy, Elsevier, vol. 57(C), pages 336-343.
    27. Ma, Hengyun & Oxley, Les & Gibson, John, 2009. "China's energy situation in the new millennium," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1781-1799, October.
    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. Zhao, Jun & Shahbaz, Muhammad & Dong, Xiucheng & Dong, Kangyin, 2021. "How does financial risk affect global CO2 emissions? The role of technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    2. Jiang, Jingjing & Ye, Bin & Liu, Junguo, 2019. "Research on the peak of CO2 emissions in the developing world: Current progress and future prospect," Applied Energy, Elsevier, vol. 235(C), pages 186-203.
    3. Gu, Gaoxiang & Wang, Zheng, 2018. "China’s carbon emissions abatement under industrial restructuring by investment restriction," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 133-144.
    4. Balogh, Jeremiás Máté, 2022. "Az egy főre jutó szén-dioxid-kibocsátás meghatározó tényezői a világgazdaságban [Determinants of per capita carbon dioxide emissions at the global level]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(4), pages 480-501.
    5. Zhang, Zhonghua & Zhao, Yuhuan & Su, Bin & Zhang, Yongfeng & Wang, Song & Liu, Ya & Li, Hao, 2017. "Embodied carbon in China’s foreign trade: An online SCI-E and SSCI based literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 492-510.
    6. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin & Jiang, Hongdian, 2022. "How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China," Energy Economics, Elsevier, vol. 105(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. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    2. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    3. Yang, Lisha & Li, Zhi, 2017. "Technology advance and the carbon dioxide emission in China – Empirical research based on the rebound effect," Energy Policy, Elsevier, vol. 101(C), pages 150-161.
    4. Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2015. "A comparative study on prediction methods for China's medium- and long-term coal demand," Energy, Elsevier, vol. 93(P2), pages 1671-1683.
    5. Lin, Boqiang & Du, Kerui, 2015. "Measuring energy rebound effect in the Chinese economy: An economic accounting approach," Energy Economics, Elsevier, vol. 50(C), pages 96-104.
    6. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.
    7. Li, Ke & Lin, Boqiang, 2015. "Heterogeneity in rebound effects: Estimated results and impact of China’s fossil-fuel subsidies," Applied Energy, Elsevier, vol. 149(C), pages 148-160.
    8. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    9. Wang, Wenchao & Mu, Hailin & Kang, Xudong & Song, Rongchen & Ning, Yadong, 2010. "Changes in industrial electricity consumption in china from 1998 to 2007," Energy Policy, Elsevier, vol. 38(7), pages 3684-3690, July.
    10. Ma, Hengyun & Oxley, Les & Gibson, John, 2010. "China's energy economy: A survey of the literature," Economic Systems, Elsevier, vol. 34(2), pages 105-132, June.
    11. Yan, Zheming & Ouyang, Xiaoling & Du, Kerui, 2019. "Economy-wide estimates of energy rebound effect: Evidence from China's provinces," Energy Economics, Elsevier, vol. 83(C), pages 389-401.
    12. Kahrl, Fredrich & Roland-Holst, David, 2009. "Growth and structural change in China's energy economy," Energy, Elsevier, vol. 34(7), pages 894-903.
    13. Gu, Gaoxiang & Wang, Zheng, 2018. "China’s carbon emissions abatement under industrial restructuring by investment restriction," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 133-144.
    14. Li, Yi & Sun, Linyan & Feng, Taiwen & Zhu, Chunyan, 2013. "How to reduce energy intensity in China: A regional comparison perspective," Energy Policy, Elsevier, vol. 61(C), pages 513-522.
    15. Li, Ke & Zhang, Ning & Liu, Yanchu, 2016. "The energy rebound effects across China’s industrial sectors: An output distance function approach," Applied Energy, Elsevier, vol. 184(C), pages 1165-1175.
    16. Ma, Hengyun & Oxley, Les & Gibson, John, 2009. "Substitution possibilities and determinants of energy intensity for China," Energy Policy, Elsevier, vol. 37(5), pages 1793-1804, May.
    17. Gu, Gaoxiang & Wang, Zheng & Wu, Leying, 2021. "Carbon emission reductions under global low-carbon technology transfer and its policy mix with R&D improvement," Energy, Elsevier, vol. 216(C).
    18. Gu, Gaoxiang & Wang, Zheng, 2018. "Research on global carbon abatement driven by R&D investment in the context of INDCs," Energy, Elsevier, vol. 148(C), pages 662-675.
    19. Zhang, Jing & Deng, Shihuai & Shen, Fei & Yang, Xinyao & Liu, Guodong & Guo, Hang & Li, Yuanwei & Hong, Xiao & Zhang, Yanzong & Peng, Hong & Zhang, Xiaohong & Li, Li & Wang, Yingjun, 2011. "Modeling the relationship between energy consumption and economy development in China," Energy, Elsevier, vol. 36(7), pages 4227-4234.
    20. Wang, Xiaolei & Wen, Xiaohui & Xie, Chunping, 2018. "An evaluation of technical progress and energy rebound effects in China's iron & steel industry," Energy Policy, Elsevier, vol. 123(C), pages 259-265.

    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:72:y:2014:i:c:p:168-179. 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.