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When does the turning point in China's CO2 emissions occur? Results based on the Green Solow model

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  • Hao, Yu
  • Wei, Yi-Ming

Abstract

In recent years, the surge in China's CO2 emissions has caused increasing international concern. In this paper, we investigate whether and when the turning point in China's CO2 emissions would occur. A simple yet powerful neoclassical Green Solow model (GSM) is utilized herein as the main forecasting tool. To verify the capability of this framework to address China's economy, a key prediction of the GSM – the convergence in per capita CO2 emissions across Chinese provinces – is empirically verified. By assigning reasonable values to the GSM's key parameters, the trajectories of total CO2 emissions are projected for the three regions of China and the whole country. The forecast results show that, under the benchmark scenario, China's total CO2 emissions would peak around the year 2047. According to the sensitivity analysis, carbon efficiency is the most important determining factor for whether a turning point in total CO2 emissions may occur.

Suggested Citation

  • Hao, Yu & Wei, Yi-Ming, 2015. "When does the turning point in China's CO2 emissions occur? Results based on the Green Solow model," Environment and Development Economics, Cambridge University Press, vol. 20(6), pages 723-745, December.
    • Handle: RePEc:cup:endeec:v:20:y:2015:i:06:p:723-745_00
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    Cited by:

    1. Yu, Shiwei & Zheng, Shuhong & Li, Xia, 2018. "The achievement of the carbon emissions peak in China: The role of energy consumption structure optimization," Energy Economics, Elsevier, vol. 74(C), pages 693-707.
    2. Chang, Chun-Ping & Wen, Jun & Dong, Minyi & Hao, Yu, 2018. "Does government ideology affect environmental pollutions? New evidence from instrumental variable quantile regression estimations," Energy Policy, Elsevier, vol. 113(C), pages 386-400.
    3. Yong Bian & Zhi Yu & Xuelan Zeng & Jingchun Feng & Chao He, 2018. "Achieving China’s Long-Term Carbon Emission Abatement Targets: A Perspective from Regional Disparity," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    4. Hao, Yu & Wang, Ling-Ou & Lee, Chien-Chiang, 2020. "Financial development, energy consumption and China's economic growth: New evidence from provincial panel data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1132-1151.
    5. Hao, Yu & Zhang, Zong-Yong & Yang, Chuxiao & Wu, Haitao, 2021. "Does structural labor change affect CO2 emissions? Theoretical and empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    6. Zhiyuan Gao & Lianqing Li & Yu Hao, 2024. "Financial risk under the shock of global warming: Evidence from China," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 335-351, February.
    7. Wu, Ya & Zhang, Wanying, 2016. "The driving factors behind coal demand in China from 1997 to 2012: An empirical study of input-output structural decomposition analysis," Energy Policy, Elsevier, vol. 95(C), pages 126-134.
    8. Hao, Yu & Peng, Hui, 2017. "On the convergence in China's provincial per capita energy consumption: New evidence from a spatial econometric analysis," Energy Economics, Elsevier, vol. 68(C), pages 31-43.
    9. Xiao-Ying Dong & Qiying Ran & Yu Hao, 2019. "On the nonlinear relationship between energy consumption and economic development in China: new evidence from panel data threshold estimations," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1837-1857, July.
    10. Yunwei Li & Qiuping Ji & Zijie Wang & Zishan Xiong & Simeng Zhan & Yiping Yang & Yu Hao, 2022. "Green energy mismatch, industrial intelligence and economics growth: theory and empirical evidence from China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(10), pages 11785-11816, October.
    11. Firouz Fallahi, 2020. "Persistence and unit root in $$\text {CO}_{2}$$CO2 emissions: evidence from disaggregated global and regional data," Empirical Economics, Springer, vol. 58(5), pages 2155-2179, May.
    12. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
    13. Lu, Zhijian & Shao, Shuai, 2016. "Impacts of government subsidies on pricing and performance level choice in Energy Performance Contracting: A two-step optimal decision model," Applied Energy, Elsevier, vol. 184(C), pages 1176-1183.
    14. Wang, Ling-Ou & Wu, Haitao & Hao, Yu, 2020. "How does China's land finance affect its carbon emissions?," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 267-281.
    15. Liu, Yiming & Hao, Yu & Gao, Yixuan, 2017. "The environmental consequences of domestic and foreign investment: Evidence from China," Energy Policy, Elsevier, vol. 108(C), pages 271-280.
    16. Yu Hao & Zirui Huang & Haitao Wu, 2019. "Do Carbon Emissions and Economic Growth Decouple in China? An Empirical Analysis Based on Provincial Panel Data," Energies, MDPI, vol. 12(12), pages 1-15, June.
    17. Zhi-Fu Mi & Yi-Ming Wei & Bing Wang & Jing Meng & Zhu Liu & Yuli Shan & Jingru Liu & Dabo Guan, 2017. "Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030," CEEP-BIT Working Papers 103, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    18. Shobande, Olatunji A. & Ogbeifun, Lawrence, 2023. "Pooling cross-sectional and time series data for estimating causality between technological innovation, affluence and carbon dynamics: A comparative evidence from developed and developing countries," Technological Forecasting and Social Change, Elsevier, vol. 187(C).

    More about this item

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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