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European Union emissions trading scheme impact on the Spanish electricity price during phase II and phase III implementation

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  • Freitas, Carlos J. Pereira
  • Silva, Patrícia Pereira da

Abstract

The European Union Emissions Trading Scheme (EU ETS) is a cornerstone of the European Union's policy to combat climate change and its key tool for reducing industrial greenhouse gas emissions cost-effectively. The purpose of the present work is to evaluate the influence of CO2 opportunity cost on the Spanish wholesale electricity price. Our sample includes all Phase II of the EU ETS and the first year of Phase III implementation, from January 2008 to December 2013. A vector error correction model (VECM) is applied to estimate not only long-run equilibrium relations, but also short-run interactions between the electricity price and the fuel (natural gas and coal) and carbon prices. The four commodities prices are modeled as joint endogenous variables with air temperature and renewable energy as exogenous variables. We found a long-run relationship (cointegration) between electricity price, carbon price, and fuel prices. By estimating the dynamic pass-through of carbon price into electricity price for different periods of our sample, it is possible to observe the weakening of the link between carbon and electricity prices as a result from the collapse on CO2 prices, therefore compromising the efficacy of the system to reach proposed environmental goals. This conclusion is in line with the need to shape new policies within the framework of the EU ETS that prevent excessive low prices for carbon over extended periods of time.

Suggested Citation

  • Freitas, Carlos J. Pereira & Silva, Patrícia Pereira da, 2015. "European Union emissions trading scheme impact on the Spanish electricity price during phase II and phase III implementation," Utilities Policy, Elsevier, vol. 33(C), pages 54-62.
    • Handle: RePEc:eee:juipol:v:33:y:2015:i:c:p:54-62
    DOI: 10.1016/j.jup.2015.01.004
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    Cited by:

    1. Fabio Zagonari, 2018. "Coherence, Causality, and Effectiveness of the EU Environmental Policy System: Results of Complementary Statistical and Econometric Analyses," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(1), pages 1-29, May.
    2. Chang, Kai & Ye, Zhifang & Wang, Weihong, 2019. "Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China’s emissions trading scheme pilots," Energy, Elsevier, vol. 185(C), pages 1314-1324.
    3. Georg Wolff & Stefan Feuerriegel, 2019. "Emissions Trading System of the European Union: Emission Allowances and EPEX Electricity Prices in Phase III," Energies, MDPI, Open Access Journal, vol. 12(15), pages 1-1, July.
    4. da Silva, Patricia Pereira & Moreno, Blanca & Figueiredo, Nuno Carvalho, 2016. "Firm-specific impacts of CO2 prices on the stock market value of the Spanish power industry," Energy Policy, Elsevier, vol. 94(C), pages 492-501.
    5. Jiménez-Rodríguez, Rebeca, 2019. "What happens to the relationship between EU allowances prices and stock market indices in Europe?," Energy Economics, Elsevier, vol. 81(C), pages 13-24.
    6. Schusser, Sandra & Jaraitė, Jūratė, 2018. "Explaining the interplay of three markets: Green certificates, carbon emissions and electricity," Energy Economics, Elsevier, vol. 71(C), pages 1-13.
    7. Tadahiro Nakajima, 2019. "Expectations for Statistical Arbitrage in Energy Futures Markets," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(1), pages 1-1, January.
    8. 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.
    9. Feria-Domínguez, José Manuel & Rodriguez-Carrillero, David & Guerra-Martinez, José Carlos, 2018. "Measuring the risk-adjusted performance of CO2 emission markets: Evidence from SENDECO2," Utilities Policy, Elsevier, vol. 50(C), pages 124-132.
    10. da Silva, Patrícia Pereira & Cerqueira, Pedro A., 2017. "Assessing the determinants of household electricity prices in the EU: a system-GMM panel data approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1131-1137.
    11. Zhu, Bangzhu & Han, Dong & Chevallier, Julien & Wei, Yi-Ming, 2017. "Dynamic multiscale interactions between European carbon and electricity markets during 2005–2016," Energy Policy, Elsevier, vol. 107(C), pages 309-322.
    12. Chang, Kai & Ge, Fangping & Zhang, Chao & Wang, Weihong, 2018. "The dynamic linkage effect between energy and emissions allowances price for regional emissions trading scheme pilots in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 415-425.
    13. Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
    14. Liu, Xiuli & Moreno, Blanca & García, Ana Salomé, 2016. "A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors," Energy, Elsevier, vol. 115(P1), pages 1042-1054.

    More about this item

    Keywords

    Q58; H23; Q48; C32; L94; Environmental policy; Carbon emissions; Electricity prices; Cointegration; Vector error correction model;

    JEL classification:

    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • 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
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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