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Carbon intensity as a proxy for environmental performance and the informational content of the EPI

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  • Thomakos, Dimitrios D.
  • Alexopoulos, Thomas A.

Abstract

We analyze the relationship between carbon intensity and EPI and find that the informational content of EPI is in large part explainable by the state of economic growth and level of carbon intensity, with the second variable being already an increasing function of emissions and a decreasing function of economic well being. Carbon intensity has the largest explanatory power for EPI rankings and consistently produces the correct, anticipated, negative sign in its relationship to EPI. Second in importance are the renewable energy sources, which also produce consistent results with respect to their impact on the EPI but with much lower explanatory power. Our results suggest that advanced countries should, as they are doing already, implement measures of high quality environmental content while measures for increasing economic growth, while controlling emissions, are appropriate for developing countries. A number of other energy policy implications and the use of new technologies are also discussed in the context of our analysis.

Suggested Citation

  • Thomakos, Dimitrios D. & Alexopoulos, Thomas A., 2016. "Carbon intensity as a proxy for environmental performance and the informational content of the EPI," Energy Policy, Elsevier, vol. 94(C), pages 179-190.
    • Handle: RePEc:eee:enepol:v:94:y:2016:i:c:p:179-190
    DOI: 10.1016/j.enpol.2016.03.030
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    as
    1. Hao, Yu & Liao, Hua & Wei, Yi-Ming, 2015. "Is China’s carbon reduction target allocation reasonable? An analysis based on carbon intensity convergence," Applied Energy, Elsevier, vol. 142(C), pages 229-239.
    2. Ahking, Francis W., 2002. "Model mis-specification and Johansen's co-integration analysis: an application to the US money demand," Journal of Macroeconomics, Elsevier, vol. 24(1), pages 51-66, March.
    3. Cowan, Wendy N. & Chang, Tsangyao & Inglesi-Lotz, Roula & Gupta, Rangan, 2014. "The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries," Energy Policy, Elsevier, vol. 66(C), pages 359-368.
    4. Itkonen, Juha V.A., 2012. "Problems estimating the carbon Kuznets curve," Energy, Elsevier, vol. 39(1), pages 274-280.
    5. Stern, David I., 2002. "Explaining changes in global sulfur emissions: an econometric decomposition approach," Ecological Economics, Elsevier, vol. 42(1-2), pages 201-220, August.
    6. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    7. Li, Huanan & Wei, Yi-Ming, 2015. "Is it possible for China to reduce its total CO2 emissions?," Energy, Elsevier, vol. 83(C), pages 438-446.
    8. Su, Bin & Ang, B.W., 2015. "Multiplicative decomposition of aggregate carbon intensity change using input–output analysis," Applied Energy, Elsevier, vol. 154(C), pages 13-20.
    9. Liaskas, K. & Mavrotas, G. & Mandaraka, M. & Diakoulaki, D., 2000. "Decomposition of industrial CO2 emissions:: The case of European Union," Energy Economics, Elsevier, vol. 22(4), pages 383-394, August.
    10. Yuan, Jiahai & Hou, Yong & Xu, Ming, 2012. "China's 2020 carbon intensity target: Consistency, implementations, and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4970-4981.
    11. Elettra Agliardi & Mehmet Pinar & Thanasis Stengos, 2015. "An environmental degradation index based on stochastic dominance," Empirical Economics, Springer, vol. 48(1), pages 439-459, February.
    12. Greening, Lorna A. & Davis, William B. & Schipper, Lee, 1998. "Decomposition of aggregate carbon intensity for the manufacturing sector: comparison of declining trends from 10 OECD countries for the period 1971-1991," Energy Economics, Elsevier, vol. 20(1), pages 43-65, February.
    13. Singh, Omendra Kumar & Kaushik, Subhash C., 2013. "Reducing CO2 emission and improving exergy based performance of natural gas fired combined cycle power plants by coupling Kalina cycle," Energy, Elsevier, vol. 55(C), pages 1002-1013.
    14. Burnett, J. Wesley & Bergstrom, John C. & Wetzstein, Michael E., 2013. "Carbon dioxide emissions and economic growth in the U.S," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 1014-1028.
    15. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    16. Lise, Wietze, 2006. "Decomposition of CO2 emissions over 1980-2003 in Turkey," Energy Policy, Elsevier, vol. 34(14), pages 1841-1852, September.
    17. Hamilton, Clive & Turton, Hal, 2002. "Determinants of emissions growth in OECD countries," Energy Policy, Elsevier, vol. 30(1), pages 63-71, January.
    18. Roca, Jordi & Alcantara, Vicent, 2001. "Energy intensity, CO2 emissions and the environmental Kuznets curve. The Spanish case," Energy Policy, Elsevier, vol. 29(7), pages 553-556, June.
    19. Yanine, Franco Fernando & Caballero, Federico I. & Sauma, Enzo E. & Córdova, Felisa M., 2014. "Building sustainable energy systems: Homeostatic control of grid-connected microgrids, as a means to reconcile power supply and energy demand response management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 1168-1191.
    20. Schipper, Lee & Ting, Michael & Khrushch, Marta & Golove, William, 1997. "The evolution of carbon dioxide emissions from energy use in industrialized countries: an end-use analysis," Energy Policy, Elsevier, vol. 25(7-9), pages 651-672.
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    More about this item

    Keywords

    Environmental performance index; Carbon intensity; Policy implications; Panel regression; Economic growth;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • 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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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