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Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China

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  • Qi, Haozhi
  • Wu, Tiantian
  • Chen, Hao
  • Lu, Xiuling

Abstract

This paper aims to investigate the dynamic connectedness and the cross-quantile dependence structure between carbon emission trading and commodity markets in China. We employ both the Baruník and Křehlík (2018) connectedness method and the Baruník and Kley (2019) cross-quantile dependence method to provide time-frequency-quantile evidence. In addition, we use a daily dataset from September 2, 2013, to September 30, 2022, to gauge the macroeconomic effects of the COVID-19 pandemic. We find that Petrochemical is the biggest contributor and recipient in the carbon-commodities system, and the results show that carbon markets are more influenced by other commodity markets than the reverse. Furthermore, the total connectedness is stronger in the short term but can increase over the long term, especially during the onset of COVID-19. The dynamic pair-wise results show that the carbon market can impact other commodity markets, but the effects are diverse and varied. The quantile-varying dependence between the carbon market and commodities is detected, and the cross-quantile dependence gradually strengthens as the trading days increase. This paper concludes with fruitful policy implications for resource decision-makers.

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  • Qi, Haozhi & Wu, Tiantian & Chen, Hao & Lu, Xiuling, 2023. "Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:jrpoli:v:82:y:2023:i:c:s0301420723001265
    DOI: 10.1016/j.resourpol.2023.103418
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    as
    1. Jiang, Yonghong & Lao, Jiashun & Mo, Bin & Nie, He, 2018. "Dynamic linkages among global oil market, agricultural raw material markets and metal markets: An application of wavelet and copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 265-279.
    2. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    3. Li, Zijian & Meng, Qiaoyu, 2022. "Time and frequency connectedness and portfolio diversification between cryptocurrencies and renewable energy stock markets during COVID-19," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    4. Cai, Guixin & Zhang, Hao & Chen, Ziyue, 2019. "Comovement between commodity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1247-1258.
    5. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2016. "Risk spillovers across the energy and carbon markets and hedging strategies for carbon risk," Energy Economics, Elsevier, vol. 54(C), pages 159-172.
    6. Lao, Jiashun & Nie, He & Jiang, Yonghong, 2018. "Revisiting the investor sentiment–stock returns relationship: A multi-scale perspective using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 420-427.
    7. Onur Polat, 2019. "Systemic risk contagion in FX market: A frequency connectedness and network analysis," Bulletin of Economic Research, Wiley Blackwell, vol. 71(4), pages 585-598, October.
    8. 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).
    9. Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    10. He Nie & Yonghong Jiang & Baoqing Yang, 2018. "Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?," Applied Economics Letters, Taylor & Francis Journals, vol. 25(11), pages 747-751, June.
    11. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    12. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    13. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    14. Chevallier, Julien, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Economic Modelling, Elsevier, vol. 28(1-2), pages 557-567, January.
    15. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    16. Jiang, Yonghong & Feng, Qidi & Mo, Bin & Nie, He, 2020. "Visiting the effects of oil price shocks on exchange rates: Quantile-on-quantile and causality-in-quantiles approaches," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    17. Mo, Bin & Meng, Juan & Zheng, Liping, 2022. "Time and frequency dynamics of connectedness between cryptocurrencies and commodity markets," Resources Policy, Elsevier, vol. 77(C).
    18. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    19. Huang, Jikun & Rozelle, Scott, 2006. "The emergence of agricultural commodity markets in China," China Economic Review, Elsevier, vol. 17(3), pages 266-280.
    20. Maghyereh, Aktham & Abdoh, Hussein, 2021. "Tail dependence between gold and Islamic securities," Finance Research Letters, Elsevier, vol. 38(C).
    21. Song, Xiang & Wang, Dingyu & Zhang, Xuantao & He, Yuan & Wang, Yong, 2022. "A comparison of the operation of China's carbon trading market and energy market and their spillover effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    22. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods," Energy, Elsevier, vol. 246(C).
    23. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    24. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
    25. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    26. Jiawen Luo & Qun Zhang, 2021. "Risk contagions between global oil markets and China’s agricultural commodity markets under structural breaks," Applied Economics, Taylor & Francis Journals, vol. 53(5), pages 628-649, January.
    27. Cui, Jinxin & Goh, Mark & Zou, Huiwen, 2021. "Coherence, extreme risk spillovers, and dynamic linkages between oil and China’s commodity futures markets," Energy, Elsevier, vol. 225(C).
    28. Chen, Hao & Xu, Chao, 2022. "The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    29. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Wanas Al-Jarrah, Idries Mohammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Does volatility connectedness across major cryptocurrencies behave the same at different frequencies? A portfolio risk analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 96-113.
    30. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
    31. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    32. repec:dau:papers:123456789/5111 is not listed on IDEAS
    33. Himadri Rajput & Rahil Changotra & Prachi Rajput & Sneha Gautam & Anjani R. K. Gollakota & Amarpreet Singh Arora, 2021. "A shock like no other: coronavirus rattles commodity markets," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 6564-6575, May.
    34. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Hedström, Axel, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Energy Economics, Elsevier, vol. 71(C), pages 35-46.
    35. Liu, Yunqiang & Liu, Sha & Shao, Xiaoyu & He, Yanqiu, 2022. "Policy spillover effect and action mechanism for environmental rights trading on green innovation: Evidence from China's carbon emissions trading policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    36. Xia, Tongshui & Yao, Chen-Xi & Geng, Jiang-Bo, 2020. "Dynamic and frequency-domain spillover among economic policy uncertainty, stock and housing markets in China," International Review of Financial Analysis, Elsevier, vol. 67(C).
    37. Bai, Lan & Zhang, Xuhui & Liu, Yuntong & Wang, Qian, 2019. "Economic risk contagion among major economies: New evidence from EPU spillover analysis in time and frequency domains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    38. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    39. Chen, Hao & Xu, Chao & Peng, Yun, 2022. "Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China," Resources Policy, Elsevier, vol. 78(C).
    40. Jia, Zhijie & Lin, Boqiang, 2020. "Rethinking the choice of carbon tax and carbon trading in China," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    41. Li, Zhenghui & Mo, Bin & Nie, He, 2023. "Time and frequency dynamic connectedness between cryptocurrencies and financial assets in China," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 46-57.
    42. Balli, Faruk & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2019. "Spillover network of commodity uncertainties," Energy Economics, Elsevier, vol. 81(C), pages 914-927.
    43. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    44. Le, Trung Hai & Do, Hung Xuan & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Covid-19 pandemic and tail-dependency networks of financial assets," Finance Research Letters, Elsevier, vol. 38(C).
    45. Zhao, Lili & Liu, Wenhua & Zhou, Min & Wen, Fenghua, 2022. "Extreme event shocks and dynamic volatility interactions: The stock, commodity, and carbon markets in China," Finance Research Letters, Elsevier, vol. 47(PA).
    46. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    47. Kang, Sang Hoon & Yoon, Seong-Min, 2019. "Financial crises and dynamic spillovers among Chinese stock and commodity futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    48. Christoph Böhringer & Thomas Rutherford, 2002. "Carbon Abatement and International Spillovers," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(3), pages 391-417, July.
    49. Dai, Xingyu & Li, Matthew C. & Xiao, Ling & Wang, Qunwei, 2022. "COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis," Resources Policy, Elsevier, vol. 79(C).
    50. Yun Liu, 2022. "Housing and monetary policy: Fresh evidence from China," Financial Economics Letters, Anser Press, vol. 1(1), pages 1-12, December.
    51. Zhang, Hao & Cai, Guixin & Yang, Dongxiao, 2020. "The impact of oil price shocks on clean energy stocks: Fresh evidence from multi-scale perspective," Energy, Elsevier, vol. 196(C).
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