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The impact of oil price on the clean energy metal prices: A multi-scale perspective

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  • Shao, Liuguo
  • Zhang, Hua

Abstract

To examine the spillover effects of crude oil price and clean energy metal prices, we first explore the Granger causality between crude oil and clean energy metals prices. Then, we decompose crude oil price returns into a high frequency sequence (Oil_HF), a low frequency sequence (Oil_LF), and a trend residual (Oil_res) using the ensemble empirical mode decomposition model. Lastly, a VAR model is used to study the spillover effects of crude oil price on seven types of clean energy metal prices. The results show that crude oil price has non-linear Granger causality with lithium, cobalt, manganese, antimony, cadmium, molybdenum, and tellurium. And crude oil price has a significant positive spillover effect on seven types of clean energy metals at different time scales. Specifically, the crude oil original sequence, Oil_HF, Oil_LF, and Oil_res all have fluctuation effects on the cobalt and molybdenum markets. The spillover effects of the crude oil market on the lithium, manganese, antimony, and cadmium markets are caused by the low frequency sequence. The trend in crude oil price returns has a great effect on tellurium price, while the spillover effects of crude oil price, Oil_HF, and Oil_LF on tellurium are weak positive.

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  • Shao, Liuguo & Zhang, Hua, 2020. "The impact of oil price on the clean energy metal prices: A multi-scale perspective," Resources Policy, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:jrpoli:v:68:y:2020:i:c:s0301420719308657
    DOI: 10.1016/j.resourpol.2020.101730
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    as
    1. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The role of outliers and oil price shocks on volatility of metal prices," Resources Policy, Elsevier, vol. 46(P2), pages 139-150.
    2. Jingyu Chen & Faqi Jin & Guangda Ouyang & Jian Ouyang & Fenghua Wen, 2019. "Oil price shocks, economic policy uncertainty and industrial economic growth in China," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-19, May.
    3. Singhal, Shelly & Choudhary, Sangita & Biswal, Pratap Chandra, 2019. "Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico," Resources Policy, Elsevier, vol. 60(C), pages 255-261.
    4. Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
    5. Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur & Jammazi, Rania, 2019. "Spillovers from oil to precious metals: Quantile approaches," Resources Policy, Elsevier, vol. 61(C), pages 508-521.
    6. Wen, Fenghua & Xiao, Yilin & Wu, Haiquan, 2019. "The effects of foreign uncertainty shocks on China’s macro-economy: Empirical evidence from a nonlinear ARDL model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    7. Yin, Libo & Ma, Xiyuan, 2018. "Causality between oil shocks and exchange rate: A Bayesian, graph-based VAR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 434-453.
    8. Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
    9. Yu, Lean & Li, Jingjing & Tang, Ling & Wang, Shuai, 2015. "Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach," Energy Economics, Elsevier, vol. 51(C), pages 300-311.
    10. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    11. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    12. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    13. Korhonen, Iikka & Ledyaeva, Svetlana, 2010. "Trade linkages and macroeconomic effects of the price of oil," Energy Economics, Elsevier, vol. 32(4), pages 848-856, July.
    14. Zhu, Bangzhu & Han, Dong & Wang, Ping & Wu, Zhanchi & Zhang, Tao & Wei, Yi-Ming, 2017. "Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression," Applied Energy, Elsevier, vol. 191(C), pages 521-530.
    15. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
    16. Chen, Yufeng & Qu, Fang, 2019. "Leverage effect and dynamics correlation between international crude oil and China’s precious metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    17. Zhang, Chuanguo & Tu, Xiaohua, 2016. "The effect of global oil price shocks on China's metal markets," Energy Policy, Elsevier, vol. 90(C), pages 131-139.
    18. Kumar, Satish, 2017. "On the nonlinear relation between crude oil and gold," Resources Policy, Elsevier, vol. 51(C), pages 219-224.
    19. Chiu, Yi-Bin, 2017. "Carbon dioxide, income and energy: Evidence from a non-linear model," Energy Economics, Elsevier, vol. 61(C), pages 279-288.
    20. Zhu, Xuehong & Zheng, Weihang & Zhang, Hongwei & Guo, Yaoqi, 2019. "Time-varying international market power for the Chinese iron ore markets," Resources Policy, Elsevier, vol. 64(C).
    21. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
    22. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Wen, Shaobo & Hao, Xiaoqing, 2017. "The multiscale impact of exchange rates on the oil-stock nexus: Evidence from China and Russia," Applied Energy, Elsevier, vol. 194(C), pages 667-678.
    23. Noah Kittner & Felix Lill & Daniel M. Kammen, 2017. "Energy storage deployment and innovation for the clean energy transition," Nature Energy, Nature, vol. 2(9), pages 1-6, September.
    24. Grandell, Leena & Lehtilä, Antti & Kivinen, Mari & Koljonen, Tiina & Kihlman, Susanna & Lauri, Laura S., 2016. "Role of critical metals in the future markets of clean energy technologies," Renewable Energy, Elsevier, vol. 95(C), pages 53-62.
    25. Zou, Gaolu & Chau, K.W., 2006. "Short- and long-run effects between oil consumption and economic growth in China," Energy Policy, Elsevier, vol. 34(18), pages 3644-3655, December.
    26. Norden E. Huang & Man‐Li Wu & Wendong Qu & Steven R. Long & Samuel S. P. Shen, 2003. "Applications of Hilbert–Huang transform to non‐stationary financial time series analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 19(3), pages 245-268, July.
    27. Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Oil prices and global factor macroeconomic variables," Energy Economics, Elsevier, vol. 59(C), pages 198-212.
    28. Ming, Lei & Yang, Shenggang & Cheng, Cheng, 2016. "The double nature of the price of gold—A quantitative analysis based on Ensemble Empirical Mode Decomposition," Resources Policy, Elsevier, vol. 47(C), pages 125-131.
    29. Zhu, Bangzhu & Yuan, Lili & Ye, Shunxin, 2019. "Examining the multi-timescales of European carbon market with grey relational analysis and empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 392-399.
    30. Zhu, Yongguang & Xu, Deyi & Cheng, Jinhua & Ali, Saleem Hassan, 2018. "Estimating the impact of China's export policy on tin prices: a mode decomposition counterfactual analysis method," Resources Policy, Elsevier, vol. 59(C), pages 250-264.
    31. Dutta, Anupam, 2018. "Impacts of oil volatility shocks on metal markets: A research note," Resources Policy, Elsevier, vol. 55(C), pages 9-19.
    32. Ahmed A. A. Khalifa & Hong Miao & Sanjay Ramchander, 2011. "Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(1), pages 55-80, January.
    33. Geng, Jiang-Bo & Ji, Qiang & Fan, Ying, 2017. "The relationship between regional natural gas markets and crude oil markets from a multi-scale nonlinear Granger causality perspective," Energy Economics, Elsevier, vol. 67(C), pages 98-110.
    34. Reboredo, Juan C. & Ugolini, Andrea, 2016. "The impact of downward/upward oil price movements on metal prices," Resources Policy, Elsevier, vol. 49(C), pages 129-141.
    35. Hongwei Zhang & Xuehong Zhu & Yaoqi Guo & Haibo Liu, 2018. "A separate reduced‐form volatility forecasting model for nonferrous metal market: Evidence from copper and aluminum," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 754-766, November.
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