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The dynamic spillover effects of climate policy uncertainty and coal price on carbon price: Evidence from China

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  • Yan, Wan-Lin
  • Cheung, Adrian (Wai Kong)

Abstract

This paper applies the time-varying parameters vector autoregression (TVP-VAR) model to investigate the dynamic effects of climate policy uncertainty and coal price on carbon price in China. Based on news from China's mainstream newspapers and websites, a tailor-made climate policy uncertainty index is constructed. The VAR-BEKK-GARCH model is utilized as robustness check. The results indicate that both the climate policy uncertainty and coal price have significant time-varying effects on the carbon price. Additional dynamic connectedness analysis reveals that coal price is the main shock transmitter while climate policy uncertainty and carbon price are mostly net shock receivers.

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  • 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).
    • Handle: RePEc:eee:finlet:v:53:y:2023:i:c:s1544612322005773
    DOI: 10.1016/j.frl.2022.103400
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    as
    1. Huang, Yun & Luk, Paul, 2020. "Measuring economic policy uncertainty in China," China Economic Review, Elsevier, vol. 59(C).
    2. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    3. Robert F Engle & Stefano Giglio & Bryan Kelly & Heebum Lee & Johannes Stroebel, 2020. "Hedging Climate Change News," Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1184-1216.
    4. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression," International Review of Financial Analysis, Elsevier, vol. 65(C).
    5. Lin, Boqiang & Chen, Yufang, 2019. "Dynamic linkages and spillover effects between CET market, coal market and stock market of new energy companies: A case of Beijing CET market in China," Energy, Elsevier, vol. 172(C), pages 1198-1210.
    6. Lardic, Sandrine & Mignon, Valérie, 2008. "Oil prices and economic activity: An asymmetric cointegration approach," Energy Economics, Elsevier, vol. 30(3), pages 847-855, May.
    7. Fischer, Carolyn, 2008. "Emissions pricing, spillovers, and public investment in environmentally friendly technologies," Energy Economics, Elsevier, vol. 30(2), pages 487-502, March.
    8. 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.
    9. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    10. Ye, Liping, 2022. "The effect of climate news risk on uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    11. Wu, Ruirui & Qin, Zhongfeng & Liu, Bing-Yue, 2022. "A systemic analysis of dynamic frequency spillovers among carbon emissions trading (CET), fossil energy and sectoral stock markets: Evidence from China," Energy, Elsevier, vol. 254(PA).
    12. Chen, Yingqi & Ba, Shusong & Yang, Qing & Yuan, Tian & Zhao, Haibo & Zhou, Ming & Bartocci, Pietro & Fantozzi, Francesco, 2021. "Efficiency of China’s carbon market: A case study of Hubei pilot market," Energy, Elsevier, vol. 222(C).
    13. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    14. Stephie Fried & Kevin Novan & William B. Peterman, 2021. "The Macro Effects of Climate Policy Uncertainty," Finance and Economics Discussion Series 2021-018, Board of Governors of the Federal Reserve System (U.S.).
    15. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    16. Wen, Danyan & Wang, Yudong & Ma, Chaoqun & Zhang, Yaojie, 2020. "Information transmission between gold and financial assets: Mean, volatility, or risk spillovers?," Resources Policy, Elsevier, vol. 69(C).
    17. Chang, Kai & Ge, Fangping & Zhang, Chao & Wang, Weihong, 2018. "The dynamic linkage effect between energy and emissions allowances price for regional emissions trading scheme pilots in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 415-425.
    18. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2020. "The effects of geopolitical risks on the stock dynamics of China's rare metals: A TVP-VAR analysis," Resources Policy, Elsevier, vol. 68(C).
    19. Li, Xin & Li, Zheng & Su, Chi-Wei & Umar, Muhammad & Shao, Xuefeng, 2022. "Exploring the asymmetric impact of economic policy uncertainty on China's carbon emissions trading market price: Do different types of uncertainty matter?," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    20. Yin, Jiuli & Zhu, Yan & Fan, Xinghua, 2021. "Correlation analysis of China’s carbon market and coal market based on multi-scale entropy," Resources Policy, Elsevier, vol. 72(C).
    21. Chang, Kai & Ye, Zhifang & Wang, Weihong, 2019. "Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China’s emissions trading scheme pilots," Energy, Elsevier, vol. 185(C), pages 1314-1324.
    22. Zeng, Qing & Ma, Feng & Lu, Xinjie & Xu, Weiju, 2022. "Policy uncertainty and carbon neutrality: Evidence from China," Finance Research Letters, Elsevier, vol. 47(PB).
    23. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    24. Chen, Yufeng & Xu, Jing & Hu, May, 2022. "Asymmetric volatility spillovers and dynamic correlations between crude oil price, exchange rate and gold price in BRICS," Resources Policy, Elsevier, vol. 78(C).
    25. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    26. Veugelers, Reinhilde, 2012. "Which policy instruments to induce clean innovating?," Research Policy, Elsevier, vol. 41(10), pages 1770-1778.
    27. E. A. G. Schuur & A. D. McGuire & C. Schädel & G. Grosse & J. W. Harden & D. J. Hayes & G. Hugelius & C. D. Koven & P. Kuhry & D. M. Lawrence & S. M. Natali & D. Olefeldt & V. E. Romanovsky & K. Schae, 2015. "Climate change and the permafrost carbon feedback," Nature, Nature, vol. 520(7546), pages 171-179, April.
    28. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    29. Blyth, William & Bradley, Richard & Bunn, Derek & Clarke, Charlie & Wilson, Tom & Yang, Ming, 2007. "Investment risks under uncertain climate change policy," Energy Policy, Elsevier, vol. 35(11), pages 5766-5773, November.
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    More about this item

    Keywords

    Dynamic spillover effect; The time-varying parameters vector autoregression model; Carbon price; Climate policy uncertainty; Coal price;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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