IDEAS home Printed from https://ideas.repec.org/a/spr/lsprsc/v16y2023i1d10.1007_s12076-023-00352-w.html
   My bibliography  Save this article

The extreme spillover from climate policy uncertainty to the Chinese sector stock market: wavelet time-varying approach

Author

Listed:
  • Huthaifa Sameeh Alqaralleh

    (Mutah University)

Abstract

This study investigates the extreme return connectedness between five major Chinese stock prices and climate uncertainty between March 2010 and June 2022. A novel wavelet time-varying parameter quantile vector Autoregression is employed. The results show that climate uncertainty depresses investment predominantly in normal periods while altering the lead-lag direction among these sector classes during turmoil periods. The results provide significant implications for investors and policymakers concerned with stock prices.

Suggested Citation

  • Huthaifa Sameeh Alqaralleh, 2023. "The extreme spillover from climate policy uncertainty to the Chinese sector stock market: wavelet time-varying approach," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-17, December.
    • Handle: RePEc:spr:lsprsc:v:16:y:2023:i:1:d:10.1007_s12076-023-00352-w
    DOI: 10.1007/s12076-023-00352-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12076-023-00352-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12076-023-00352-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    2. Xu, Yongan & Li, Ming & Yan, Wen & Bai, Jiancheng, 2022. "Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty," Resources Policy, Elsevier, vol. 79(C).
    3. Bown, Chad, 2019. "The 2018 US-China Trade Conflict After 40 Years of Special Protection," CEPR Discussion Papers 13695, C.E.P.R. Discussion Papers.
    4. Diaz-Rainey, Ivan & Gehricke, Sebastian A. & Roberts, Helen & Zhang, Renzhu, 2021. "Trump vs. Paris: The impact of climate policy on U.S. listed oil and gas firm returns and volatility," International Review of Financial Analysis, Elsevier, vol. 76(C).
    5. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    6. Baek, Seungho & Mohanty, Sunil K. & Glambosky, Mina, 2020. "COVID-19 and stock market volatility: An industry level analysis," Finance Research Letters, Elsevier, vol. 37(C).
    7. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
    8. Chad P. Bown, 2019. "The 2018 US-China trade conflict after forty years of special protection," China Economic Journal, Taylor & Francis Journals, vol. 12(2), pages 109-136, May.
    9. Nordhaus, William D & Yang, Zili, 1996. "A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies," American Economic Review, American Economic Association, vol. 86(4), pages 741-765, September.
    10. Romain Svartzman & Patrick Bolton & Morgan Despres & Luiz Awazu Pereira Da Silva & Frédéric Samama, 2021. "Central banks, financial stability and policy coordination in the age of climate uncertainty: a three-layered analytical and operational framework," Climate Policy, Taylor & Francis Journals, vol. 21(4), pages 563-580, April.
    11. Cao, Guangxi & Xie, Wenhao, 2022. "Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: Evidence from TVP-VAR based connectedness approach," Finance Research Letters, Elsevier, vol. 49(C).
    12. Broadstock, David C. & Chan, Kalok & Cheng, Louis T.W. & Wang, Xiaowei, 2021. "The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China," Finance Research Letters, Elsevier, vol. 38(C).
    13. Janne Kettunen, Derek W. Bunn and William Blyth & Derek W. Bunn & William Blyth, 2011. "Investment Propensities under Carbon Policy Uncertainty," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 77-118.
    14. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    15. Cheng, Feiyang & Wang, Chunfeng & Cui, Xin & Wu, Ji & He, Feng, 2021. "Economic policy uncertainty exposure and stock price bubbles: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 78(C).
    16. Dirk Schoenmaker, 2021. "Greening monetary policy," Climate Policy, Taylor & Francis Journals, vol. 21(4), pages 581-592, April.
    17. Liguang Zhang & Wanyi Chen & Ning Hu, 2021. "Economic policy uncertainty and stock liquidity: evidence from China," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 18(1), pages 22-44, March.
    18. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    19. Dunz, Nepomuk & Naqvi, Asjad & Monasterolo, Irene, 2021. "Climate sentiments, transition risk, and financial stability in a stock-flow consistent model," Journal of Financial Stability, Elsevier, vol. 54(C).
    20. Lv, Wendai & Li, Bin, 2023. "Climate policy uncertainty and stock market volatility: Evidence from different sectors," Finance Research Letters, Elsevier, vol. 51(C).
    21. Su, Xianfang, 2020. "Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    22. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    23. Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
    24. Alshater, Muneer M. & Alqaralleh, Huthaifa & El Khoury, Rim, 2023. "Dynamic asymmetric connectedness in technological sectors," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    25. Fang, Yi & Jing, Zhongbo & Shi, Yukun & Zhao, Yang, 2021. "Financial spillovers and spillbacks: New evidence from China and G7 countries," Economic Modelling, Elsevier, vol. 94(C), pages 184-200.
    26. Stolbova, Veronika & Monasterolo, Irene & Battiston, Stefano, 2018. "A Financial Macro-Network Approach to Climate Policy Evaluation," Ecological Economics, Elsevier, vol. 149(C), pages 239-253.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Yongan & Li, Ming & Yan, Wen & Bai, Jiancheng, 2022. "Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty," Resources Policy, Elsevier, vol. 79(C).
    2. Zhang, Hongwei & Hong, Huojun & Ding, Shijie, 2023. "The role of climate policy uncertainty on the long-term correlation between crude oil and clean energy," Energy, Elsevier, vol. 284(C).
    3. Chada, Swechha, 2023. "Economic policy uncertainties and institutional ownership in India," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    4. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    5. Nyakurukwa, Kingstone & Seetharam, Yudhvir, 2023. "Quantile and asymmetric return connectedness among BRICS stock markets," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    6. Xie, Qiwei & Cheng, Lu & Liu, Ranran & Zheng, Xiaolong & Li, Jingyu, 2023. "COVID-19 and risk spillovers of China's major financial markets: Evidence from time-varying variance decomposition and wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 52(C).
    7. Wang, Xiong & Li, Jingyao & Ren, Xiaohang, 2022. "Asymmetric causality of economic policy uncertainty and oil volatility index on time-varying nexus of the clean energy, carbon and green bond," International Review of Financial Analysis, Elsevier, vol. 83(C).
    8. Lu, Xunfa & Huang, Nan & Mo, Jianlei & Ye, Zhitao, 2023. "Dynamics of the return and volatility connectedness among green finance markets during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 125(C).
    9. Umar, Zaghum & Bossman, Ahmed, 2023. "Quantile connectedness between oil price shocks and exchange rates," Resources Policy, Elsevier, vol. 83(C).
    10. Yannis Dafermos, 2022. "Climate change, central banking and financial supervision: beyond the risk exposure approach," Chapters, in: Sylvio Kappes & Louis-Philippe Rochon & Guillaume Vallet (ed.), The Future of Central Banking, chapter 8, pages 175-194, Edward Elgar Publishing.
    11. Zhou, Yuqin & Liu, Zhenhua & Wu, Shan, 2022. "The global economic policy uncertainty spillover analysis: In the background of COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 61(C).
    12. Nguyen, Duc Nguyen & Nguyen, Canh Phuc & Dang, Le Phuong Xuan, 2022. "Uncertainty and corporate default risk: Novel evidence from emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    13. Ridley, William & Devadoss, Stephen, 2024. "Determinants of Policy Responses in the US–China Tit-for-Tat Trade War," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Preprint), January.
    14. William Oman & Romain Svartzman, 2021. "What Justifies Sustainable Finance Measures? Financial-Economic Interactions and Possible Implications for Policymakers," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 22(03), pages 03-11, May.
    15. Huang, Ying Sophie & Wu, Jiajia & Guo, Feng, 2022. "Venture capital staging under economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 572-596.
    16. Abuzayed, Bana & Bouri, Elie & Al-Fayoumi, Nedal & Jalkh, Naji, 2021. "Systemic risk spillover across global and country stock markets during the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 180-197.
    17. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan & Vo, Xuan Vinh, 2023. "Portfolio diversification during the COVID-19 pandemic: Do vaccinations matter?," Journal of Financial Stability, Elsevier, vol. 65(C).
    18. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2022. "The impact and role of COVID-19 uncertainty: A global industry analysis," International Review of Financial Analysis, Elsevier, vol. 80(C).
    19. Agbloyor, Elikplimi Kolma & Dwumfour, Richard Adjei & Pan, Lei & Yawson, Alfred, 2021. "Carbon emissions and banking stability: Global evidence," MPRA Paper 111092, University Library of Munich, Germany.
    20. Qiao, Xingzhi & Zhu, Huiming & Zhang, Zhongqingyang & Mao, Weifang, 2022. "Time-frequency transmission mechanism of EPU, investor sentiment and financial assets: A multiscale TVP-VAR connectedness analysis," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).

    More about this item

    Keywords

    Climate uncertainty; Quantile connectedness; W-Q-TVP-VAR;
    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
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:lsprsc:v:16:y:2023:i:1:d:10.1007_s12076-023-00352-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.