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Carbon Price Forecasting and Market Characteristics Analysis in China: An Integrated Approach Using Overall and Market-Specific Models

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  • Weibao Sun

    (College of Tourism, Northwest Normal University, Lanzhou 730070, China)

  • Yafang Gao

    (College of Tourism, Northwest Normal University, Lanzhou 730070, China
    School of Tourism, Lanzhou University of Arts and Science, Lanzhou 730030, China
    Gansu Cultural and Tourism Industry Research Institute, Lanzhou 730030, China)

  • Xuemei Yang

    (School of Tourism, Lanzhou University of Arts and Science, Lanzhou 730030, China
    Gansu Cultural and Tourism Industry Research Institute, Lanzhou 730030, China
    Observation Station of Subalpine Ecology Systems in the Middle Qilian Mountains, Xining 810000, China)

  • Yalong Zhang

    (School of Geographic Sciences, Qinghai Normal University, Xining 810008, China)

  • Haolin Hu

    (College of Tourism, Northwest Normal University, Lanzhou 730070, China)

Abstract

Carbon markets play a pivotal role in achieving carbon peaking targets, with accurate price forecasting being essential for effective policymaking and corporate decision making. This study develops an integrated forecasting framework, combining an overall market model and a market-specific model, to predict carbon price trends in China from 2025 to 2026, while examining inter-market heterogeneity across eight regional markets. The overall market forecast reveals a fluctuating upward trend in the national carbon price over the next two years. Market-specific forecasts highlight significant disparities in price trends, as follows: the Shanghai and Guangzhou markets are projected to experience faster growth and the Beijing market to maintain stable prices, while the Tianjin and Chongqing markets exhibit more moderate increases. These disparities reflect the profound influence of regional economic levels, policy enforcement, and market maturity on carbon market development. By incorporating seasonal fluctuations and stochastic disturbances, we construct a forecasting model aligned with historical data dynamics and achieve differentiated forecasts through the analysis of historical price levels across markets, addressing the limitations of uniform target pricing in prior studies. These findings offer actionable insights for carbon market participants and policymakers, providing a robust foundation for designing differentiated carbon pricing policies to support China’s carbon peaking objectives.

Suggested Citation

  • Weibao Sun & Yafang Gao & Xuemei Yang & Yalong Zhang & Haolin Hu, 2025. "Carbon Price Forecasting and Market Characteristics Analysis in China: An Integrated Approach Using Overall and Market-Specific Models," Sustainability, MDPI, vol. 17(12), pages 1-25, June.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:12:p:5407-:d:1676924
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    References listed on IDEAS

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    1. repec:dau:papers:123456789/6969 is not listed on IDEAS
    2. Hintermann, Beat, 2010. "Allowance price drivers in the first phase of the EU ETS," Journal of Environmental Economics and Management, Elsevier, vol. 59(1), pages 43-56, January.
    3. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect," Applied Energy, Elsevier, vol. 87(6), pages 1804-1814, June.
    4. Huang, Yumeng & Dai, Xingyu & Wang, Qunwei & Zhou, Dequn, 2021. "A hybrid model for carbon price forecastingusing GARCH and long short-term memory network," Applied Energy, Elsevier, vol. 285(C).
    5. Keppler, Jan Horst & Mansanet-Bataller, Maria, 2010. "Causalities between CO2, electricity, and other energy variables during phase I and phase II of the EU ETS," Energy Policy, Elsevier, vol. 38(7), pages 3329-3341, July.
    6. Creti, Anna & Jouvet, Pierre-André & Mignon, Valérie, 2012. "Carbon price drivers: Phase I versus Phase II equilibrium?," Energy Economics, Elsevier, vol. 34(1), pages 327-334.
    7. Emilie Alberola & Benoît Chèze & Julien Chevallier, 2008. "The EU Emissions Trading Scheme : Disentangling the Effects of Industrial Production and CO2 Emissions on Carbon Prices," EconomiX Working Papers 2008-12, University of Paris Nanterre, EconomiX.
    8. Seifert, Jan & Uhrig-Homburg, Marliese & Wagner, Michael, 2008. "Dynamic behavior of CO2 spot prices," Journal of Environmental Economics and Management, Elsevier, vol. 56(2), pages 180-194, September.
    9. Zhu, Bangzhu & Ye, Shunxin & Han, Dong & Wang, Ping & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "A multiscale analysis for carbon price drivers," Energy Economics, Elsevier, vol. 78(C), pages 202-216.
    10. Benz, Eva & Trück, Stefan, 2009. "Modeling the price dynamics of CO2 emission allowances," Energy Economics, Elsevier, vol. 31(1), pages 4-15, January.
    11. Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," Energy, Elsevier, vol. 35(9), pages 3921-3931.
    12. Jianguo Zhou & Shiguo Wang, 2021. "A Carbon Price Prediction Model Based on the Secondary Decomposition Algorithm and Influencing Factors," Energies, MDPI, vol. 14(5), pages 1-20, March.
    13. Chevallier, Julien, 2011. "A model of carbon price interactions with macroeconomic and energy dynamics," Energy Economics, Elsevier, vol. 33(6), pages 1295-1312.
    14. repec:dau:papers:123456789/5269 is not listed on IDEAS
    15. Koch, Nicolas & Fuss, Sabine & Grosjean, Godefroy & Edenhofer, Ottmar, 2014. "Causes of the EU ETS price drop: Recession, CDM, renewable policies or a bit of everything?—New evidence," Energy Policy, Elsevier, vol. 73(C), pages 676-685.
    16. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
    17. Paolella, Marc S. & Taschini, Luca, 2008. "An econometric analysis of emission allowance prices," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2022-2032, October.
    18. Xie, Qiwei & Hao, Jingjing & Li, Jingyu & Zheng, Xiaolong, 2022. "Carbon price prediction considering climate change: A text-based framework," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 382-401.
    19. Dong, Xiyong & Zhang, John F., 2024. "Heterogeneity of regional carbon emission markets in China: Evidence from multidimensional determinants," Energy Economics, Elsevier, vol. 138(C).
    20. repec:dau:papers:123456789/4614 is not listed on IDEAS
    21. Gary Koop & Lise Tole, 2013. "Forecasting the European carbon market," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 723-741, June.
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