IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v346y2026ics0360544226002471.html

Who is leading the methanol price? The roles of international transmission and energy price based on the PLBX model

Author

Listed:
  • Li, Qian
  • Chen, Hong
  • Long, Ruyin
  • Huang, Zhiping

Abstract

Driven by decarbonization and energy security strategies, China has emerged as the world's largest methanol market. However, its regional structure and underlying price influence mechanism remain unclear. This study constructs the spatial correlation network of methanol price (MP) in China. Then, a three-stage feature identification model (PCC-LASSO-BO-XGBoost, PLBX) is proposed to elucidate the effects of international market and energy price, with causal relationships further examined using convergent cross mapping. The results show that: (1) MP exhibits a clear core-marginal structure. North, East, and Central China occupy core positions, while Southwest, Northwest, South, and Northeast China remain at the margin. (2) MP in the United States and Rotterdam serve as the key external drivers of China core/marginal markets, with correlations of 42.76%/39.92%. (3) The aggregate impact of energy prices on core/marginal MP reaches 39.88%/37%, where coal and crude oil exert a more pronounced influence than natural gas. (4) Causal analysis further indicates that coal price acts as a dominant shock transmitter, whereas international methanol and crude oil markets function as price-signal resonators through stable bidirectional linkages with China's methanol market. These findings provide an international perspective and multi-method framework for advancing the understanding of MP formation mechanism.

Suggested Citation

  • Li, Qian & Chen, Hong & Long, Ruyin & Huang, Zhiping, 2026. "Who is leading the methanol price? The roles of international transmission and energy price based on the PLBX model," Energy, Elsevier, vol. 346(C).
  • Handle: RePEc:eee:energy:v:346:y:2026:i:c:s0360544226002471
    DOI: 10.1016/j.energy.2026.140145
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544226002471
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2026.140145?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. Xu, Chao & Zhao, Xiaojun & Wang, Yanwen, 2022. "Causal decomposition on multiple time scales: Evidence from stock price-volume time series," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    3. Liu, Zhenhua & Chen, Shumin & Zhong, Hongyu & Ding, Zhihua, 2024. "Coal price shocks, investor sentiment, and stock market returns," Energy Economics, Elsevier, vol. 135(C).
    4. Sun, Chuanwang & Min, Jialin & Sun, Jiacheng & Gong, Xu, 2023. "The role of China's crude oil futures in world oil futures market and China's financial market," Energy Economics, Elsevier, vol. 120(C).
    5. Demirer, Riza & Polat, Onur & Sokhanvar, Amin, 2025. "Do oil price shocks drive systematic risk premia in stock markets? A novel investment application," Research in International Business and Finance, Elsevier, vol. 73(PA).
    6. Minlend, Jacques, 2025. "Does the European low-carbon policy impact price uncertainty in fossil energy markets?," Energy Economics, Elsevier, vol. 148(C).
    7. Hasanov, Fakhri J. & Javid, Muhammad & Mikayilov, Jeyhun I. & Shabaneh, Rami & Darandary, Abdulelah & Alyamani, Ryan, 2025. "Macroeconomic and sectoral effects of natural gas price: Policy insights from a macroeconometric model," Energy Economics, Elsevier, vol. 143(C).
    8. Broadstock, David C. & Fouquet, Roger & Kim, Jeong Won, 2025. "Carbon pricing and stock performance: Are carbon prices already more influential than energy prices?," Energy Policy, Elsevier, vol. 206(C).
    9. Zhao, Yongning & Zhao, Yuan & Liao, Haohan & Pan, Shiji & Zheng, Yingying, 2025. "Interpreting LASSO regression model by feature space matching analysis for spatio-temporal correlation based wind power forecasting," Applied Energy, Elsevier, vol. 380(C).
    10. Galimova, Tansu & Fasihi, Mahdi & Bogdanov, Dmitrii & Lopez, Gabriel & Breyer, Christian, 2025. "Analysis of green e-methanol supply costs: Domestic production in Europe versus imports via pipeline and sea shipping," Renewable Energy, Elsevier, vol. 241(C).
    11. Zhou, Xinxing & Wang, Ping & Zhu, Bangzhu, 2025. "Exploring the drivers of China's carbon price spatial correlation network structure," Applied Energy, Elsevier, vol. 396(C).
    12. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
    13. Wang, Kangsheng & Wen, Fenghua & Gong, Xu, 2024. "Oil prices and systemic financial risk: A complex network analysis," Energy, Elsevier, vol. 293(C).
    14. Kröger, Mats & Longmuir, Maximilian & Neuhoff, Karsten & Schütze, Franziska, 2023. "The price of natural gas dependency: Price shocks, inequality, and public policy," Energy Policy, Elsevier, vol. 175(C).
    15. Rodriguez-Pastor, D.A. & Soltero, V.M. & Chacartegui, R., 2025. "Green methanol production from photovoltaics in Europe," Renewable Energy, Elsevier, vol. 254(C).
    16. Asmamaw Mulusew & Mingyong Hong, 2024. "A dynamic linkage between greenhouse gas (GHG) emissions and agricultural productivity: evidence from Ethiopia," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    17. Sun, Qingqing & Chen, Hong & Long, Ruyin & Chen, Jiawei, 2024. "Integrated prediction of carbon price in China based on heterogeneous structural information and wall-value constraints," Energy, Elsevier, vol. 306(C).
    18. Guliyev, Hasraddin & Mustafayev, Eldayag, 2022. "Predicting the changes in the WTI crude oil price dynamics using machine learning models," Resources Policy, Elsevier, vol. 77(C).
    19. Xiao, Jihong & Xu, Wen & Liu, Hong & Zhao, Yunning, 2025. "Spillovers from oil price uncertainty to Chinese sectoral stock returns: New insights from effective transfer entropy," International Review of Financial Analysis, Elsevier, vol. 106(C).
    20. Jacques Minlend, 2025. "Does the European low-carbon policy impact price uncertainty in fossil energy markets?," Post-Print hal-05167910, HAL.
    21. Alola, Andrew Adewale & Özkan, Oktay & Usman, Ojonugwa, 2023. "Examining crude oil price outlook amidst substitute energy price and household energy expenditure in the USA: A novel nonparametric multivariate QQR approach," Energy Economics, Elsevier, vol. 120(C).
    22. Gong, Xu & Jin, Yujing & Liu, Tangyong, 2023. "Analyzing pure contagion between crude oil and agricultural futures markets," Energy, Elsevier, vol. 269(C).
    23. Masih, A. Mansur M. & Albinali, Khaled & DeMello, Lurion, 2010. "Price dynamics of natural gas and the regional methanol markets," Energy Policy, Elsevier, vol. 38(3), pages 1372-1378, March.
    24. Wang, Wenyang & Luo, Yuping & Ma, Mingrui & Wang, Jinglin & Sui, Cong, 2025. "A novel forecasting framework leveraging large language model and machine learning for methanol price," Energy, Elsevier, vol. 320(C).
    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. Lin, Boqiang & Lan, Tianxu, 2025. "Energy price uncertainty and sectoral tail risk: Evidence from quantile-on-quantile connectedness," Journal of Commodity Markets, Elsevier, vol. 40(C).
    2. Liu, Hong & Zhu, Yulin & Cui, Na & Zheng, Yan, 2024. "The impact of global uncertainties on the spillover among the European carbon market, the Chinese oil futures market, and the international oil futures market," Finance Research Letters, Elsevier, vol. 67(PB).
    3. Vo, Duc Hong & Tran, Minh Phuoc-Bao, 2024. "Volatility spillovers between energy and agriculture markets during the ongoing food & energy crisis: Does uncertainty from the Russo-Ukrainian conflict matter?," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    4. Bin, Meng & Shuiyang, Chen & Jingjing, Dong, 2025. "Nonlinear risk dynamics and strategic Management: Insights for LNG shipping policy and practice," Transport Policy, Elsevier, vol. 173(C).
    5. Zhang, Dongyang & Wang, Cao & Wang, Yizhi, 2024. "Unveiling the critical nexus: Volatility of crude oil future prices and trade partner’s cash holding behavior in the face of the Russia–Ukraine conflict," Energy Economics, Elsevier, vol. 132(C).
    6. Ye, Shiqi & Zhang, Hongyin & Zhou, Mo & Zheng, Tingguo, 2025. "Assessing energy sector resilience to adverse shocks: A scenario-based QVAR approach," Energy Economics, Elsevier, vol. 149(C).
    7. Xu, Zhiwei & Gou, Xinyi & Zhang, Teng, 2025. "Have the Chinese crude oil futures prices made a progress towards becoming the regional oil pricing benchmark? Empirical analysis from the asset pricing perspective," Energy Economics, Elsevier, vol. 145(C).
    8. Zheng, J.H. & Su, Y.Y. & Guo, Y.W. & Li, Yuanzheng & Wu, Q.H., 2025. "Preference-based interactive multi-attribute decision-making support for stochastic scheduling of virtual power plants," Energy Economics, Elsevier, vol. 152(C).
    9. Yu, Yue & Wang, Jianzhou & Jiang, He & Lu, Haiyan, 2025. "How to manage a multifactor-driven crude oil market more effectively? A revisit based on the multiple criteria perspective," Resources Policy, Elsevier, vol. 100(C).
    10. Lin, Boqiang & Chen, Yiyang & Gong, Xu, 2024. "Stress from attention: The relationship between climate change attention and crude oil markets," Journal of Commodity Markets, Elsevier, vol. 34(C).
    11. Hua, Xia & Dong, Dairui & Xu, Zhiwei & Huang, Wentao, 2025. "Official media sentiments toward energy and equity returns: Evidence from China," Energy, Elsevier, vol. 340(C).
    12. Liu, Zhenhua & Wang, Yushu & Yuan, Xinting & Ding, Zhihua & Ji, Qiang, 2025. "Geopolitical risk and vulnerability of energy markets," Energy Economics, Elsevier, vol. 141(C).
    13. Gkillas, Konstantinos & Manickavasagam, Jeevananthan & Visalakshmi, S., 2022. "Effects of fundamentals, geopolitical risk and expectations factors on crude oil prices," Resources Policy, Elsevier, vol. 78(C).
    14. Zhang, Jiahao & Chen, Xiaodan & Wei, Yu & Bai, Lan, 2023. "Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis," International Review of Financial Analysis, Elsevier, vol. 88(C).
    15. Yin, Libo & Cao, Hong & Guo, Yumei, 2024. "The information content of Shanghai crude oil futures vs WTI benchmark: Evidence from temporal and spatial dimensions," Energy Economics, Elsevier, vol. 132(C).
    16. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    17. Wang, Kangsheng & Wen, Fenghua & Gong, Xu, 2024. "Oil prices and systemic financial risk: A complex network analysis," Energy, Elsevier, vol. 293(C).
    18. Zhuo, Xingxuan & Ye, Jianjiang & Liu, Han & Lin, Feng, 2025. "Analyzing dynamics of crude oil price amid sudden events and intervention measures: Insights from a Prophet-QR model," Applied Energy, Elsevier, vol. 401(PB).
    19. Wang, Xiao-Qing & Wu, Tong & Zhong, Huaming & Su, Chi-Wei, 2023. "Bubble behaviors in nickel price: What roles do geopolitical risk and speculation play?," Resources Policy, Elsevier, vol. 83(C).
    20. Ha, Le Thanh, 2025. "From wars to dynamic waves: Scrutinizing connectedness between geopolitical risk index, green and non-green crypto volatility by quantile spillovers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 679(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:eee:energy:v:346:y:2026:i:c:s0360544226002471. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.