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Environment, Energy and Environmental Productivity of Energy: A Decomposition Analysis in China and the US

Listed author(s):
  • Mohamad Taghvaee, Vahid
  • Hajiani, Parviz

The global warming, if not global burning, is a dire warning about environmental pollution dangers to everyone, living on the only one Earth. This study aims to measure relative contributors to the environmental quality changes during 2002-2011 using Logarithmic Mean Divisia Index in China and the US. Since these countries are the biggest polluters in the world, the decomposition technique is used to cut their wide environmental issues into the tiny bits of problems, being easy to cope with. Moreover, we employed Environmental Performance Index (EPI) to evolve the concept of Environmental Productivity of Energy (EPE). The results suggest that economic growth and income equality are environmentally-friendly while energy consumption is environmentally-unfriendly; and the Environmental Productivity of Energy (EPE) and technology progress are environmentally-moody (with various effects on environment). Consequently, the policy makers are advised to develop those economic sectors which are independent of pollutant energies; to replace the black energies by the green ones; and to invest on the research about the products whose demand is price inelastic.

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File URL: https://mpra.ub.uni-muenchen.de/70055/1/MPRA_paper_70055.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 70055.

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Date of creation: 2016
Handle: RePEc:pra:mprapa:70055
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  1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
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  12. Xu, Jin-Hua & Fleiter, Tobias & Eichhammer, Wolfgang & Fan, Ying, 2012. "Energy consumption and CO2 emissions in China's cement industry: A perspective from LMDI decomposition analysis," Energy Policy, Elsevier, vol. 50(C), pages 821-832.
  13. Dahl, Carol A., 2012. "Measuring global gasoline and diesel price and income elasticities," Energy Policy, Elsevier, vol. 41(C), pages 2-13.
  14. Atici, Cemal, 2012. "Carbon emissions, trade liberalization, and the Japan–ASEAN interaction: A group-wise examination," Journal of the Japanese and International Economies, Elsevier, vol. 26(1), pages 167-178.
  15. Mohamad Taghvaee, Vahid & Hajiani, Parviz, 2014. "Price and Income Elasticities of Gasoline Demand in Iran: Using Static, ECM, and Dynamic Models in Short, Intermediate, and Long Run," MPRA Paper 70054, University Library of Munich, Germany.
  16. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
  17. Kasman, Adnan & Duman, Yavuz Selman, 2015. "CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: A panel data analysis," Economic Modelling, Elsevier, vol. 44(C), pages 97-103.
  18. Zhang, Haiyan & Lahr, Michael L., 2014. "China's energy consumption change from 1987 to 2007: A multi-regional structural decomposition analysis," Energy Policy, Elsevier, vol. 67(C), pages 682-693.
  19. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sato, João Ricardo, 2015. "On the relationships between CO2 emissions, energy consumption and income: The importance of time variation," Energy Economics, Elsevier, vol. 49(C), pages 629-638.
  20. Tsurumi, Tetsuya & Managi, Shunsuke, 2010. "Does energy substitution affect carbon dioxide emissions - Income relationship?," Journal of the Japanese and International Economies, Elsevier, vol. 24(4), pages 540-551, December.
  21. Leontief, Wassily, 1970. "Environmental Repercussions and the Economic Structure: An Input-Output Approach," The Review of Economics and Statistics, MIT Press, vol. 52(3), pages 262-271, August.
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