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The risk spillover of high carbon enterprises in China: Evidence from the stock market

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  • Wu, Baohui
  • Zhu, Pingheng
  • Yin, Hua
  • Wen, Fenghua

Abstract

This paper examines the time-varying risk spillover among high carbon enterprises by constructing Granger-causality networks from 2011 to 2021, and explore the types of high carbon enterprises that have stronger risk spillover capabilities. Additionally, we also expanded our analysis on the risk spillovers from high carbon enterprises to non-high carbon enterprises. We find that the intensity of risk spillover among high carbon stocks strengthened from 2013 to 2016, then weakened, and slightly re-strengthened in 2020. High carbon enterprises from power, steel, aviation, and petrochemical industries occupy central positions in the networks. Moreover, fundamental factors such as asset scale, profitability, capital structure, ownership, and industry category significantly influence the connectivity and centrality of high carbon enterprises in the networks. Meanwhile, the high carbon enterprises with higher connectivity and central location in the networks have greater systemic risk contributions. Finally, we find that the non-high carbon enterprises from agriculture, forestry, animal husbandry and fishery industry, mining industry and transportation, warehousing and postal industry are more susceptible to the risk overflow from high carbon enterprises.

Suggested Citation

  • Wu, Baohui & Zhu, Pingheng & Yin, Hua & Wen, Fenghua, 2023. "The risk spillover of high carbon enterprises in China: Evidence from the stock market," Energy Economics, Elsevier, vol. 126(C).
    • Handle: RePEc:eee:eneeco:v:126:y:2023:i:c:s0140988323004371
    DOI: 10.1016/j.eneco.2023.106939
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    as
    1. Paltalidis, Nikos & Gounopoulos, Dimitrios & Kizys, Renatas & Koutelidakis, Yiannis, 2015. "Transmission channels of systemic risk and contagion in the European financial network," Journal of Banking & Finance, Elsevier, vol. 61(S1), pages 36-52.
    2. Koch, Nicolas & Bassen, Alexander, 2013. "Valuing the carbon exposure of European utilities. The role of fuel mix, permit allocation and replacement investments," Energy Economics, Elsevier, vol. 36(C), pages 431-443.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Corsi, Fulvio & Lillo, Fabrizio & Pirino, Davide & Trapin, Luca, 2018. "Measuring the propagation of financial distress with Granger-causality tail risk networks," Journal of Financial Stability, Elsevier, vol. 38(C), pages 18-36.
    5. Monasterolo, Irene & de Angelis, Luca, 2020. "Blind to carbon risk? An analysis of stock market reaction to the Paris Agreement," Ecological Economics, Elsevier, vol. 170(C).
    6. Oestreich, A. Marcel & Tsiakas, Ilias, 2015. "Carbon emissions and stock returns: Evidence from the EU Emissions Trading Scheme," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 294-308.
    7. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    8. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    9. Wen, Fenghua & Cao, Jiahui & Liu, Zhen & Wang, Xiong, 2021. "Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets," International Review of Financial Analysis, Elsevier, vol. 76(C).
    10. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    11. Chen, Wang & Ho, Kung-Cheng & Yang, Lu, 2020. "Network structures and idiosyncratic contagion in the European sovereign credit default swap market," International Review of Financial Analysis, Elsevier, vol. 72(C).
    12. Sam, Abdoul G. & Zhang, Xiaodong, 2020. "Value relevance of the new environmental enforcement regime in China," Journal of Corporate Finance, Elsevier, vol. 62(C).
    13. Fahmy, Hany, 2022. "The rise in investors’ awareness of climate risks after the Paris Agreement and the clean energy-oil-technology prices nexus," Energy Economics, Elsevier, vol. 106(C).
    14. Kallberg, Jarl & Pasquariello, Paolo, 2008. "Time-series and cross-sectional excess comovement in stock indexes," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 481-502, June.
    15. Nguyen, Justin Hung & Phan, Hieu V., 2020. "Carbon risk and corporate capital structure," Journal of Corporate Finance, Elsevier, vol. 64(C).
    16. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    17. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    18. Wang, Wei & Zhang, Yue-Jun, 2022. "Does China's carbon emissions trading scheme affect the market power of high-carbon enterprises?," Energy Economics, Elsevier, vol. 108(C).
    19. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    20. Shiyu Sun & Xixi Chu & Xiangbo Liu, 2022. "Urban wage inequality: The reform of state-owned enterprises in China’s great transition," Economic and Political Studies, Taylor & Francis Journals, vol. 10(4), pages 442-461, October.
    21. Maarten R C van Oordt & Chen Zhou, 2019. "Estimating Systematic Risk under Extremely Adverse Market Conditions," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 432-461.
    22. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    23. Ramiah, Vikash & Martin, Belinda & Moosa, Imad, 2013. "How does the stock market react to the announcement of green policies?," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1747-1758.
    24. Hanaka, Tesshu & Kagawa, Shigemi & Ono, Hirotaka & Kanemoto, Keiichiro, 2017. "Finding environmentally critical transmission sectors, transactions, and paths in global supply chain networks," Energy Economics, Elsevier, vol. 68(C), pages 44-52.
    25. Oberndorfer, Ulrich, 2009. "EU Emission Allowances and the stock market: Evidence from the electricity industry," Ecological Economics, Elsevier, vol. 68(4), pages 1116-1126, February.
    26. Wen, Fenghua & Zhao, Lili & He, Shaoyi & Yang, Guozheng, 2020. "Asymmetric relationship between carbon emission trading market and stock market: Evidences from China," Energy Economics, Elsevier, vol. 91(C).
    27. Skintzi, Vasiliki D., 2019. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 20-28.
    28. Ying Fan & Zhuang Liang & Xing Yao, 2022. "Regional power system transitions towards carbon neutrality: The case of North China," Economic and Political Studies, Taylor & Francis Journals, vol. 10(4), pages 416-441, October.
    29. Tatiana Didier & Inessa Love & María Soledad Martínez Pería, 2012. "What explains comovement in stock market returns during the 2007–2008 crisis?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 17(2), pages 182-202, April.
    30. Rahul Kaushik & Stefano Battiston, 2013. "Credit Default Swaps Drawup Networks: Too Interconnected to Be Stable?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-8, July.
    31. Maarten van Oordt & Chen Zhou, 2019. "Systemic risk and bank business models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 365-384, April.
    32. Lu, Shuai & Li, Shouwei & Zhou, Wei & Yang, Wenke, 2022. "Network herding of energy funds in the post-Carbon-Peak Policy era: Does it benefit profitability and stability?," Energy Economics, Elsevier, vol. 109(C).
    33. Zhifang Zhou & Tao Zhang & Kang Wen & Huixiang Zeng & Xiaohong Chen, 2018. "Carbon risk, cost of debt financing and the moderation effect of media attention: Evidence from Chinese companies operating in high‐carbon industries," Business Strategy and the Environment, Wiley Blackwell, vol. 27(8), pages 1131-1144, December.
    34. Zhang, Yue-Jun & Wang, Wei, 2021. "How does China's carbon emissions trading (CET) policy affect the investment of CET-covered enterprises?," Energy Economics, Elsevier, vol. 98(C).
    35. Yang, Zhenbing & Shao, Shuai & Yang, Lili, 2021. "Unintended consequences of carbon regulation on the performance of SOEs in China: The role of technical efficiency," Energy Economics, Elsevier, vol. 94(C).
    36. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
    37. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    38. Bu, Hui & Tang, Wenjin & Wu, Junjie, 2019. "Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method," Economic Modelling, Elsevier, vol. 81(C), pages 181-204.
    39. Veith, Stefan & Werner, Jörg R. & Zimmermann, Jochen, 2009. "Capital market response to emission rights returns: Evidence from the European power sector," Energy Economics, Elsevier, vol. 31(4), pages 605-613, July.
    40. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
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    More about this item

    Keywords

    High carbon enterprises; Complex network; Risk spillover; Driving factors;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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