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Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach

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  • Yu, Lean
  • Li, Jingjing
  • Tang, Ling
  • Wang, Shuai

Abstract

This paper investigates the causality between carbon market and crude oil market using a multi-scale analysis approach, in which two main steps are involved: multi-scale analysis and causality testing. In multi-scale analysis, bivariate empirical mode decomposition (BEMD) is employed to decompose the two series of market returns at different time-scales. In causality testing, a linear and nonlinear integrated Granger test is formulated to investigate the relationship among each pair of matched components on a similar time-scale. With the European Union emission allowance (EUA) futures and Brent futures as study samples, some interesting findings can be obtained. (1) At the original data level (without multi-scale decomposition), this study finds evidence supporting a neutrality hypothesis, i.e., no Granger causality between the carbon and crude oil markets. (2) On small time-scale (within one week excluding non-work days), the two markets might be uncorrelated and driven by their own respective supply–demand disequilibriums. (3) For medium time-scale (above one week but below one year), there is a strong bi-directional linear and nonlinear spillover effect between the two markets, due to certain extra factors with medium-term effects, e.g., significant events and policy changes. (4) For long time-scale, the long-term trends of the two markets appear an obvious linear relationship.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:eneeco:v:51:y:2015:i:c:p:300-311
    DOI: 10.1016/j.eneco.2015.07.005
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    as
    1. Cifter, Atilla & Ozun, Alper, 2007. "Multi-scale Causality between Energy Consumption and GNP in Emerging Markets: Evidence from Turkey," MPRA Paper 2483, University Library of Munich, Germany.
    2. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    3. Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong & Sousa, Ricardo M., 2015. "An empirical analysis of energy cost pass-through to CO2 emission prices," Energy Economics, Elsevier, vol. 49(C), pages 149-156.
    4. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
    5. Aatola, Piia & Ollikainen, Markku & Toppinen, Anne, 2013. "Price determination in the EU ETS market: Theory and econometric analysis with market fundamentals," Energy Economics, Elsevier, vol. 36(C), pages 380-395.
    6. Zhuang, Xiaoyang & Wei, Yu & Zhang, Bangzheng, 2014. "Multifractal detrended cross-correlation analysis of carbon and crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 113-125.
    7. Chevallier, Julien, 2009. "Carbon futures and macroeconomic risk factors: A view from the EU ETS," Energy Economics, Elsevier, vol. 31(4), pages 614-625, July.
    8. Creti, Anna & Jouvet, Pierre-André & Mignon, Valérie, 2012. "Carbon price drivers: Phase I versus Phase II equilibrium?," Energy Economics, Elsevier, vol. 34(1), pages 327-334.
    9. Mansanet-Bataller, Maria & Chevallier, Julien & Hervé-Mignucci, Morgan & Alberola, Emilie, 2011. "EUA and sCER phase II price drivers: Unveiling the reasons for the existence of the EUA-sCER spread," Energy Policy, Elsevier, vol. 39(3), pages 1056-1069, March.
    10. Yuying Yang & Chang Liu & Xiaolei Sun & Jianping Li, 2015. "Spillover effect of international crude oil market on tanker market," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(4/5/6), pages 257-277.
    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. Bangzhu Zhu & Ping Wang & Julien Chevallier & Yiming Wei, 2015. "Carbon Price Analysis Using Empirical Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 195-206, February.
    13. Massimo Peri & Lucia Baldi, 2011. "Nonlinear price dynamics between CO2 futures and Brent," Applied Economics Letters, Taylor & Francis Journals, vol. 18(13), pages 1207-1211.
    14. Bredin, Don & Muckley, Cal, 2011. "An emerging equilibrium in the EU emissions trading scheme," Energy Economics, Elsevier, vol. 33(2), pages 353-362, March.
    15. Reboredo, Juan C., 2013. "Modeling EU allowances and oil market interdependence. Implications for portfolio management," Energy Economics, Elsevier, vol. 36(C), pages 471-480.
    16. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    17. Bangzhu Zhu, 2012. "A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network," Energies, MDPI, vol. 5(2), pages 1-16, February.
    18. Zhang, Dayong, 2008. "Oil shock and economic growth in Japan: A nonlinear approach," Energy Economics, Elsevier, vol. 30(5), pages 2374-2390, September.
    19. repec:dau:papers:123456789/4222 is not listed on IDEAS
    20. Yu, Lean & Zhao, Yang & Tang, Ling, 2014. "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, vol. 46(C), pages 236-245.
    21. Reboredo, Juan C., 2014. "Volatility spillovers between the oil market and the European Union carbon emission market," Economic Modelling, Elsevier, vol. 36(C), pages 229-234.
    22. Chiou-Wei, Song Zan & Chen, Ching-Fu & Zhu, Zhen, 2008. "Economic growth and energy consumption revisited -- Evidence from linear and nonlinear Granger causality," Energy Economics, Elsevier, vol. 30(6), pages 3063-3076, November.
    23. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
    24. repec:dau:papers:123456789/4210 is not listed on IDEAS
    25. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    26. 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.
    27. Alberola, Emilie & Chevallier, Julien & Cheze, Benoi^t, 2008. "Price drivers and structural breaks in European carbon prices 2005-2007," Energy Policy, Elsevier, vol. 36(2), pages 787-797, February.
    28. Liu, Hsiang-Hsi & Chen, Yi-Chun, 2013. "A study on the volatility spillovers, long memory effects and interactions between carbon and energy markets: The impacts of extreme weather," Economic Modelling, Elsevier, vol. 35(C), pages 840-855.
    29. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    30. Maria Mansanet-Bataller & Angel Pardo & Enric Valor, 2007. "CO2 Prices, Energy and Weather," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 73-92.
    31. repec:dau:papers:123456789/5109 is not listed on IDEAS
    32. François Benhmad, 2012. "Modeling Nonlinear Granger Causality between the Oil price and U.S Dollar," Post-Print hal-03062497, HAL.
    33. Reboredo, Juan C. & Ugando, Mikel, 2015. "Downside risks in EU carbon and fossil fuel markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 111(C), pages 17-35.
    34. Lean Yu & Jingjing Li & Ling Tang, 2015. "Dynamic volatility spillover effect analysis between carbon market and crude oil market: a DCC-ICSS approach," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(4/5/6), pages 242-256.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Bivariate empirical mode decomposition; Nonlinear Granger causality test; Multi-scale analysis; Carbon market; Crude oil market;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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