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Influencing factors and fluctuation characteristics of China’s carbon emission trading price

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  • Zhou, Kaile
  • Li, Yiwen

Abstract

The environmental deterioration and resulting climate change have become one of the major challenges that human has faced in recent years. Carbon emission trading, as an effective economic tool to deal with climate change issues, has attracted widespread attention. As a major carbon emitter, China plays an important role in combating global climate change. Based on the carbon emission trading price data of China’s Hubei Emission Exchange, a Vector Auto-Regressive (VAR)-Vector Error Correction (VEC) model is first used to investigate the dynamic relationship between energy price, macroeconomic indicators, air quality, and carbon emission trading price. The results show that there is a long-term equilibrium relationship between carbon emission trading price and these indicators. When the carbon emission price is too high and deviates from the long-term equilibrium value, it will slowly decline to reach the long-term equilibrium value. The price of carbon emission trading is largely affected by macroeconomic indicators among all these influencing factors. In addition, a Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model is used to explore the fluctuation characteristics of China’s carbon emission trading price. It is found that the return series of carbon emission price are consistent with the characteristics of financial time series, such as fluctuation aggregates, spikes and thick tails, and non-normal distribution. There is a positive leverage effect for the fluctuation of China’s carbon emission price. It is further found that external bad news has a greater impact on the fluctuation of China’s carbon emission trading price than good news.

Suggested Citation

  • Zhou, Kaile & Li, Yiwen, 2019. "Influencing factors and fluctuation characteristics of China’s carbon emission trading price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 459-474.
    • Handle: RePEc:eee:phsmap:v:524:y:2019:i:c:p:459-474
    DOI: 10.1016/j.physa.2019.04.249
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    as
    1. Jiang, Jing Jing & Ye, Bin & Ma, Xiao Ming, 2014. "The construction of Shenzhen׳s carbon emission trading scheme," Energy Policy, Elsevier, vol. 75(C), pages 17-21.
    2. Zheng, Zeyu & Xiao, Rui & Shi, Haibo & Li, Guihong & Zhou, Xiaofeng, 2015. "Statistical regularities of Carbon emission trading market: Evidence from European Union allowances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 9-15.
    3. Munnings, Clayton & Morgenstern, Richard D. & Wang, Zhongmin & Liu, Xu, 2016. "Assessing the design of three carbon trading pilot programs in China," Energy Policy, Elsevier, vol. 96(C), pages 688-699.
    4. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    5. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Zhao, Xin-gang & Wu, Lei & Li, Ang, 2017. "Research on the efficiency of carbon trading market in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1-8.
    8. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    9. Guo, Huaying & Liang, Jin, 2016. "An optimal control model for reducing and trading of carbon emissions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 11-21.
    10. Chevallier, Julien, 2009. "Carbon futures and macroeconomic risk factors: A view from the EU ETS," Energy Economics, Elsevier, vol. 31(4), pages 614-625, July.
    11. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    12. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    13. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    14. repec:dau:papers:123456789/4210 is not listed on IDEAS
    15. Deviren, Seyma Akkaya & Deviren, Bayram, 2016. "The relationship between carbon dioxide emission and economic growth: Hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 429-439.
    16. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    17. Yang, Lin & Li, Fengyu & Zhang, Xian, 2016. "Chinese companies’ awareness and perceptions of the Emissions Trading Scheme (ETS): Evidence from a national survey in China," Energy Policy, Elsevier, vol. 98(C), pages 254-265.
    18. Fan, Ying & Wu, Jie & Xia, Yan & Liu, Jing-Yu, 2016. "How will a nationwide carbon market affect regional economies and efficiency of CO2 emission reduction in China?," China Economic Review, Elsevier, vol. 38(C), pages 151-166.
    19. Cong, Ren & Lo, Alex Y., 2017. "Emission trading and carbon market performance in Shenzhen, China," Applied Energy, Elsevier, vol. 193(C), pages 414-425.
    20. Zhang, Chi & Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2017. "Exploring the transformation and upgrading of China’s economy using electricity consumption data: A VAR–VEC based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 144-155.
    21. Maria Mansanet-Bataller & Angel Pardo & Enric Valor, 2007. "CO2 Prices, Energy and Weather," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 73-92.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Yuanfeng Hu & Yixiang Tian & Luping Zhang, 2023. "Green Bond Pricing and Optimization Based on Carbon Emission Trading and Subsidies: From the Perspective of Externalities," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    2. Hu, Yuanfeng & Tian, Yixiang, 2024. "The role of green reputation, carbon trading and government intervention in determining the green bond pricing: An externality perspective," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 46-62.
    3. 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.
    4. Liang Shen & Xiaodi Wang & Qinqin Liu & Yuyan Wang & Lingxue Lv & Rongyun Tang, 2021. "Carbon Trading Mechanism, Low-Carbon E-Commerce Supply Chain and Sustainable Development," Mathematics, MDPI, vol. 9(15), pages 1-26, July.
    5. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    6. Xiaohua Song & Wen Zhang & Zeqi Ge & Siqi Huang & Yamin Huang & Sijia Xiong, 2022. "A Study of the Influencing Factors on the Carbon Emission Trading Price in China Based on the Improved Gray Relational Analysis Model," Sustainability, MDPI, vol. 14(13), pages 1-27, June.
    7. Jianguo Zhou & Dongfeng Chen, 2021. "Carbon Price Forecasting Based on Improved CEEMDAN and Extreme Learning Machine Optimized by Sparrow Search Algorithm," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
    8. Chun Jiang & Yi-Fan Wu & Xiao-Lin Li & Xin Li, 2020. "Time-frequency Connectedness between Coal Market Prices, New Energy Stock Prices and CO 2 Emissions Trading Prices in China," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    9. Wen, Fenghua & Zhao, Haocen & Zhao, Lili & Yin, Hua, 2022. "What drive carbon price dynamics in China?," International Review of Financial Analysis, Elsevier, vol. 79(C).
    10. Guoli Qu & Chengwei Guo & Jindong Cui, 2024. "Influencing Factors and Formation Mechanism of Carbon Emission Rights Prices in Shanghai, China," Sustainability, MDPI, vol. 16(20), pages 1-15, October.
    11. Liu, Zhibin & Huang, Shan, 2021. "Carbon option price forecasting based on modified fractional Brownian motion optimized by GARCH model in carbon emission trading," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    12. Yan, Wan-Lin & Cheung, Adrian (Wai Kong), 2023. "The dynamic spillover effects of climate policy uncertainty and coal price on carbon price: Evidence from China," Finance Research Letters, Elsevier, vol. 53(C).
    13. Liu, Qingchen & Li, Hongchang & Shang, Wen-long & Wang, Kun, 2022. "Spatio-temporal distribution of Chinese cities’ air quality and the impact of high-speed rail," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    14. Jiaojiao Sun & Feng Dong, 2023. "Optimal reduction and equilibrium carbon allowance price for the thermal power industry under China’s peak carbon emissions target," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    15. Zhang, Wen & Wu, Zhibin & Zeng, Xiaojun & Zhu, Changhui, 2023. "An ensemble dynamic self-learning model for multiscale carbon price forecasting," Energy, Elsevier, vol. 263(PC).

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