IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03897206.html
   My bibliography  Save this paper

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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://hal.science/hal-03897206/document
    Download Restriction: no
    File URL: https://libkey.io/10.1007/s11027-021-09979-w?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
    ---><---

    References listed on IDEAS

    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. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Feng, Shenghao & Zhang, Keyu, 2018. "Fuel-factor nesting structures in CGE models of China," Energy Economics, Elsevier, vol. 75(C), pages 274-284.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    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. Többen, Johannes & Banning, Maximilian & Hembach-Stunden, Katharina & Stöver, Britta & Ulrich, Philip & Schwab, Thomas, 2023. "Energising EU Cohesion: Powering up lagging regions in the renewable energy transition," MPRA Paper 119374, University Library of Munich, Germany.

    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. Xin Su & Frédéric Ghersi & Fei Teng & Gaëlle 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," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(1), pages 1-37, January.
    2. Durand-Lasserve, Olivier & Almutairi, Hossa & Aljarboua, Abdullah & Pierru, Axel & Pradhan, Shreekar & Murphy, Frederic, 2023. "Hard-linking a top-down economic model with a bottom-up energy system for an oil-exporting country with price controls," Energy, Elsevier, vol. 266(C).
    3. Lee, Hwarang & Kang, Sung Won & Koo, Yoonmo, 2020. "A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects," Energy, Elsevier, vol. 212(C).
    4. Pisciella, Paolo & van Beesten, E. Ruben & Tomasgard, Asgeir, 2023. "Efficient coordination of top-down and bottom-up models for energy system design: An algorithmic approach," Energy, Elsevier, vol. 284(C).
    5. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    6. Andersen, Kristoffer S. & Termansen, Lars B. & Gargiulo, Maurizio & Ó Gallachóirc, Brian P., 2019. "Bridging the gap using energy services: Demonstrating a novel framework for soft linking top-down and bottom-up models," Energy, Elsevier, vol. 169(C), pages 277-293.
    7. Shenghao Feng & Xiujian Peng & Philip Adams, 2021. "Energy and Economic Implications of Carbon Neutrality in China -- A Dynamic General Equilibrium Analysis," Centre of Policy Studies/IMPACT Centre Working Papers g-318, Victoria University, Centre of Policy Studies/IMPACT Centre.
    8. 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.
    9. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
    10. Le Treut, Gaëlle & Lefèvre, Julien & Lallana, Francisco & Bravo, Gonzalo, 2021. "The multi-level economic impacts of deep decarbonization strategies for the energy system," Energy Policy, Elsevier, vol. 156(C).
    11. Chen, Han & Yang, Lei & Chen, Wenying, 2020. "Modelling national, provincial and city-level low-carbon energy transformation pathways," Energy Policy, Elsevier, vol. 137(C).
    12. Dong, Huijuan & Dai, Hancheng & Geng, Yong & Fujita, Tsuyoshi & Liu, Zhe & Xie, Yang & Wu, Rui & Fujii, Minoru & Masui, Toshihiko & Tang, Liang, 2017. "Exploring impact of carbon tax on China’s CO2 reductions and provincial disparities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 596-603.
    13. Krook-Riekkola, Anna & Berg, Charlotte & Ahlgren, Erik O. & Söderholm, Patrik, 2017. "Challenges in top-down and bottom-up soft-linking: Lessons from linking a Swedish energy system model with a CGE model," Energy, Elsevier, vol. 141(C), pages 803-817.
    14. Yang, Xi & Pang, Jun & Teng, Fei & Gong, Ruixin & Springer, Cecilia, 2021. "The environmental co-benefit and economic impact of China's low-carbon pathways: Evidence from linking bottom-up and top-down models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    15. Feng, Shenghao & Zhang, Keyu, 2018. "Fuel-factor nesting structures in CGE models of China," Energy Economics, Elsevier, vol. 75(C), pages 274-284.
    16. Sophie Maire & Philippe Thalmann & Frank Vöhringer, 2019. "Welfare effects of technology-based climate policies in liberalized electricity markets: seeing beyond total system cost," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-12, December.
    17. Olegs Krasnopjorovs & Daniels Jukna & Konstantins Kovalovs, 2022. "On the Use of General Equilibrium Model to Assess the Impact of Climate Policy in Latvia," Post-Print hal-03861139, HAL.
    18. Helgesen, Per Ivar & Tomasgard, Asgeir, 2018. "From linking to integration of energy system models and computational general equilibrium models – Effects on equilibria and convergence," Energy, Elsevier, vol. 159(C), pages 1218-1233.
    19. Igos, Elorri & Rugani, Benedetto & Rege, Sameer & Benetto, Enrico & Drouet, Laurent & Zachary, Daniel S., 2015. "Combination of equilibrium models and hybrid life cycle-input–output analysis to predict the environmental impacts of energy policy scenarios," Applied Energy, Elsevier, vol. 145(C), pages 234-245.
    20. Wesseh, Presley K. & Lin, Boqiang, 2018. "Optimal carbon taxes for China and implications for power generation, welfare, and the environment," Energy Policy, Elsevier, vol. 118(C), pages 1-8.

    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:hal:journl:hal-03897206. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.