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The economic impact of a deep decarbonisation pathway for China: a hybrid model analysis through bottom-up and top-down linking

Author

Listed:
  • Xin Su
  • Frédéric Ghersi

    (CIRED - Centre International de Recherche sur l'Environnement et le Développement - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École des Ponts ParisTech - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique, CNRS - Centre National de la Recherche Scientifique)

  • Fei Teng
  • Gaëlle Le Treut
  • Meicong Liang

Abstract

Designing mid-century low-emission development strategies is crucial to guiding long-term mitigation pathways at national levels. The cost of low-carbon transition is one of the key concerns in deep decarbonisation pathways (DDPs). In this study, we estimate the macroeconomic cost of a deep decarbonisation pathway for China, by integrating an energysystems optimization model with an economic model through hard linking. Our results show that deep decarbonisation increases the energy expenses of households in the mid-run through, especially, the higher cost of power and its substitution to coal; but not those of firms, who benefit from lower coal prices caused by the reduction of coal demand and reduce costly oil products consumptions early on. Energy-efficiency improvements therefore lead to a decrease of firms' total energy costs, which allows partially compensating the crowding-out effect of low-carbon investment on general productive capital. Compared to business-as-usual, our DDP 2 scenario consequently comes at a small macroeconomic cost, equal to a lag of less than one year of growth in 2050.

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  • Xin Su & Frédéric Ghersi & Fei Teng & Gaëlle Le Treut & Meicong Liang, 2022. "The economic impact of a deep decarbonisation pathway for China: a hybrid model analysis through bottom-up and top-down linking," Post-Print hal-03897206, HAL.
  • Handle: RePEc:hal:journl:hal-03897206
    DOI: 10.1007/s11027-021-09979-w
    Note: View the original document on HAL open archive server: https://hal.science/hal-03897206
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    as
    1. Kenneth C. Hoffman & Dale W. Jorgenson, 1977. "Economic and Technological Models for Evaluation of Energy Policy," Bell Journal of Economics, The RAND Corporation, vol. 8(2), pages 444-466, Autumn.
    2. Soummane, Salaheddine & Ghersi, Frédéric & Lefèvre, Julien, 2019. "Macroeconomic pathways of the Saudi economy: The challenge of global mitigation action versus the opportunity of national energy reforms," Energy Policy, Elsevier, vol. 130(C), pages 263-282.
    3. Cohen, Stuart M. & Caron, Justin, 2018. "The economic impacts of high wind penetration scenarios in the United States," Energy Economics, Elsevier, vol. 76(C), pages 558-573.
    4. Jacobsson, Staffan & Lauber, Volkmar, 2006. "The politics and policy of energy system transformation--explaining the German diffusion of renewable energy technology," Energy Policy, Elsevier, vol. 34(3), pages 256-276, February.
    5. Soummane, Salaheddine & Ghersi, Frédéric & Lefèvre, Julien, 2019. "Macroeconomic pathways of the Saudi economy: The challenge of global mitigation action versus the opportunity of national energy reforms," Energy Policy, Elsevier, vol. 130(C), pages 263-282.
    6. Patricia Fortes & Sofia Simões & Júlia Seixas & Denise Van Regemorter & Francisco Ferreira, 2013. "Top-down and bottom-up modelling to support low-carbon scenarios: climate policy implications," Climate Policy, Taylor & Francis Journals, vol. 13(3), pages 285-304, May.
    7. Fortes, Patrícia & Pereira, Rui & Pereira, Alfredo & Seixas, Júlia, 2014. "Integrated technological-economic modeling platform for energy and climate policy analysis," Energy, Elsevier, vol. 73(C), pages 716-730.
    8. 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.
    9. Feng, Shenghao & Zhang, Keyu, 2018. "Fuel-factor nesting structures in CGE models of China," Energy Economics, Elsevier, vol. 75(C), pages 274-284.
    10. Abrell, Jan & Rausch, Sebastian, 2016. "Cross-country electricity trade, renewable energy and European transmission infrastructure policy," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 87-113.
    11. Chen, Wenying, 2005. "The costs of mitigating carbon emissions in China: findings from China MARKAL-MACRO modeling," Energy Policy, Elsevier, vol. 33(7), pages 885-896, May.
    12. Bataille, Christopher & Waisman, Henri & Vogt-Schilb, Adrien & Jaramillo, Marcela & Delgado, Ricardo & Arguello, Ricardo & Clarke, Leon & Wild, Thomas & Lallana, Francisco & Bravo, Gonzalo & Le Treut,, 2020. "Net-zero Deep Decarbonization Pathways in Latin America: Challenges and Opportunities," IDB Publications (Working Papers) 10702, Inter-American Development Bank.
    13. Liu, Yu & Lu, Yingying, 2015. "The Economic impact of different carbon tax revenue recycling schemes in China: A model-based scenario analysis," Applied Energy, Elsevier, vol. 141(C), pages 96-105.
    14. Zha, Donglan & Zhou, Dequn, 2014. "The elasticity of substitution and the way of nesting CES production function with emphasis on energy input," Applied Energy, Elsevier, vol. 130(C), pages 793-798.
    15. Martinsen, Thomas, 2011. "Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models," Energy Policy, Elsevier, vol. 39(6), pages 3327-3336, June.
    16. Chen, Wenying & Wu, Zongxin & He, Jiankun & Gao, Pengfei & Xu, Shaofeng, 2007. "Carbon emission control strategies for China: A comparative study with partial and general equilibrium versions of the China MARKAL model," Energy, Elsevier, vol. 32(1), pages 59-72.
    17. Duan, Hong-Bo & Zhu, Lei & Fan, Ying, 2014. "Optimal carbon taxes in carbon-constrained China: A logistic-induced energy economic hybrid model," Energy, Elsevier, vol. 69(C), pages 345-356.
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