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An Econometric Analysis of Emission Trading Allowances

Author

Listed:
  • Marc S. Paoletta

    (University of Zurich and Swiss Finance Institute)

  • Luca Taschini

    (University of Zurich)

Abstract

World power and gas markets have a natural relationship with global tradable carbon permits markets, including the U.S. Clean Air Act Amendments and the EU Emissions Trading Scheme, the latter officially launched in January 2005. Electric utilities operate their power plants based in part on the price of the power and the relative cost of coal and natural gas. As both carbon dioxide and sulphur dioxide are by-products of the coal burning process, the new factors of SO2 and CO2 emissions allowances come into play in a carbon constrained economy. Now that a price has been put on such allowances, the differences in carbon intensity for coal and gas could potentially change the way companies run their power plants. Moreover, knowledge of the statistical distribution of emission trading allowances, and its forecastability, becomes crucial in constructing optimal hedging and purchasing strategies in the carbon market. This paper provides an in-depth analysis of available data addressing the unconditional tail behavior and the inherent heteroskedastic dynamics in the returns on the emissions allowances.

Suggested Citation

  • Marc S. Paoletta & Luca Taschini, 2006. "An Econometric Analysis of Emission Trading Allowances," Swiss Finance Institute Research Paper Series 06-26, Swiss Finance Institute.
  • Handle: RePEc:chf:rpseri:rp0626
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    Citations

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    Cited by:

    1. Dannenberg, Henry & Ehrenfeld, Wilfried, 2008. "Prognose des CO2-Zertifikatepreisrisikos," IWH Discussion Papers 5/2008, Halle Institute for Economic Research (IWH).
    2. repec:wsi:ijtafx:v:12:y:2009:i:07:n:s0219024909005531 is not listed on IDEAS
    3. Rittler, Daniel, 2009. "Price Discovery, Causality and Volatility Spillovers in European Union Allowances Phase II: A High Frequency Analysis," Working Papers 0492, University of Heidelberg, Department of Economics.
    4. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "What explain the short-term dynamics of the prices of CO2 emissions?," Energy Economics, Elsevier, vol. 46(C), pages 122-135.
    5. Richard S. J. Tol & Seán Lyons, 2008. "Incorporating GHG Emission Costs in the Economic Appraisal of Projects Supported by State Development Agencies," Papers WP247, Economic and Social Research Institute (ESRI).
    6. Chevallier, Julien & Le Pen, Yannick & Sévi, Benoît, 2011. "Options introduction and volatility in the EU ETS," Resource and Energy Economics, Elsevier, vol. 33(4), pages 855-880.
    7. Beat Hintermann, 2009. "An Options Pricing Approach for CO2 Allowances in the EU ETS," CEPE Working paper series 09-64, CEPE Center for Energy Policy and Economics, ETH Zurich.
    8. Szymon Borak & Wolfgang Härdle & Stefan Trück & Rafal Weron, 2006. "Convenience Yields for CO2 Emission Allowance Futures Contracts," SFB 649 Discussion Papers SFB649DP2006-076, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Julien Chevallier & Benoît Sévi, 2011. "On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting," Annals of Finance, Springer, vol. 7(1), pages 1-29, February.
    10. Zheng, Zeyu & Xiao, Rui & Shi, Haibo & Li, Guihong & Zhou, Xiaofeng, 2015. "Statistical regularities of Carbon emission trading market: Evidence from European Union allowances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 9-15.
    11. Rotfuß, Waldemar, 2009. "Intraday price formation and volatility in the European Union emissions trading scheme: an introductory analysis," ZEW Discussion Papers 09-018, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    12. Julien Chevallier, 2010. "A Note on Cointegrating and Vector Autoregressive Relationships between CO2 allowances spot and futures prices," Economics Bulletin, AccessEcon, vol. 30(2), pages 1564-1584.
    13. Cong, Ren & Lo, Alex Y., 2017. "Emission trading and carbon market performance in Shenzhen, China," Applied Energy, Elsevier, vol. 193(C), pages 414-425.

    More about this item

    Keywords

    Environmental Finance; GARCH; Greenhouse Gases; Mixture Models; Tail Estimation;

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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