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Analysis of the economic impact of different Chinese climate policy options based on a CGE model incorporating endogenous technological change

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  • Wang, Ke
  • Wang, Can
  • Chen, Jining
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    Abstract

    Abatement cost is the main concern for climate change mitigation and the key factor for mitigation cost is technological change. This study established an integrated economic, energy, environmental, dynamic, computable general equilibrium (CGE) model representing endogenous technological change for China's climate change policy analysis. This study analyzed and compared the economic impact of different approaches to mitigation commitments as well as the potential role of technological change in the formulation of mitigation targets and commitments, taking into account China's climate policy-making needs based on the current international climate negotiation process. The results show that, absolute emission limits similar to the Kyoto Protocol will seriously impede the future economic development of China, while the impact of an 80% reduction in carbon intensity, forecast for 2050 based on the 2005 level, is relatively small. Technological change can promote economic growth, improve energy efficiency and reduce carbon intensity per unit of output through the substitution of production factors. Consequently it can reduce marginal abatement cost and related GDP loss by mitigation. At the same time it can increase mitigation potentials and extend the emission reduction amount, showing that consideration of the impact of technological change when deciding the emission reduction targets is necessary.

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    File URL: http://www.sciencedirect.com/science/article/B6V2W-4W75RW8-2/2/f06646d52692f7220846b32598c8b488
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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 37 (2009)
    Issue (Month): 8 (August)
    Pages: 2930-2940

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    Handle: RePEc:eee:enepol:v:37:y:2009:i:8:p:2930-2940

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    Web page: http://www.elsevier.com/locate/enpol

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    Keywords: Computable general equilibrium Mitigation cost China;

    References

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    Cited by:
    1. Ling Tang & Qin Bao & ZhongXiang Zhang & Shouyang Wang, 2013. "Carbon-based Border Tax Adjustments and China’s International Trade: Analysis based on a Dynamic Computable General Equilibrium Model," Working Papers 2013.17, Fondazione Eni Enrico Mattei.
    2. Wei Jin, 2012. "Can Technological Innovation Help China Take on Its Climate Responsibility? A Computable General Equilibrium Analysis," CAMA Working Papers 2012-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Lucas Bretschger & Lin Zhang, 2014. "Going beyond tradition: Carbon policy in a high-growth economy: The case of China," CER-ETH Economics working paper series 14/201, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    4. Mahmood, Arshad & Marpaung, Charles O.P., 2014. "Carbon pricing and energy efficiency improvement -- why to miss the interaction for developing economies? An illustrative CGE based application to the Pakistan case," Energy Policy, Elsevier, vol. 67(C), pages 87-103.
    5. Bénédicte Meurisse & Maxime Le Roy, 2014. "Towards a clean vehicle fleet: from households’ valuation of fuel efficiency to policy implications," Working Papers 1406, Chaire Economie du Climat.
    6. Zhang, Da & Rausch, Sebastian & Karplus, Valerie J. & Zhang, Xiliang, 2013. "Quantifying regional economic impacts of CO2 intensity targets in China," Energy Economics, Elsevier, vol. 40(C), pages 687-701.
    7. Duscha, Vicki & Schumacher, Katja & Schleich, Joachim & Buisson, Pierre, 2013. "Costs of meeting international climate targets without nuclear power," Working Papers "Sustainability and Innovation" S7/2013, Fraunhofer Institute for Systems and Innovation Research (ISI).
    8. repec:prg:jnlpep:v:2013:y:2013:i:4:id:432:p:412-433 is not listed on IDEAS
    9. Cai, Y.P. & Huang, G.H. & Tan, Q. & Yang, Z.F., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part I: Methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2779-2790, August.
    10. Xu, Shi-Chun & He, Zheng-Xia & Long, Ru-Yin, 2014. "Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI," Applied Energy, Elsevier, vol. 127(C), pages 182-193.
    11. Wang, Can & Zhang, Weishi & Cai, Wenjia & Xie, Xi, 2013. "Employment impacts of CDM projects in China's power sector," Energy Policy, Elsevier, vol. 59(C), pages 481-491.
    12. Zuzana Křístková, 2012. "Impact of R&D Investment on Economic Growth of the Czech Republic - A Recursively Dynamic CGE Approach," Prague Economic Papers, University of Economics, Prague, vol. 2012(4), pages 412-433.
    13. Lin, Boqiang & Moubarak, Mohamed, 2014. "Mitigation potential of carbon dioxide emissions in the Chinese textile industry," Applied Energy, Elsevier, vol. 113(C), pages 781-787.
    14. Cai, Y.P. & Huang, G.H. & Tan, Q. & Liu, L., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part II. Case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3051-3073, August.

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