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Energy decomposition analysis: the generalized Fisher index revisited

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  • de Boer, P.M.C.

Abstract

It is generally believed that index decomposition analysis (IDA) and input-output structural decomposition analysis (SDA) (Rose and Casler, 1996; Dietzenbacher and Los, 1998) are different approaches in energy studies; see for instance Ang, Liu and Chung (2004). In this paper it is shown that the generalized Fisher approach, introduced in IDA by Ang, c.s. (2004) for the decomposition of an aggregate change in a variable in factors is equivalent to SDA. They base their formulae on the very complicated generic formula that Shapley (1953) derived for his value of n-person games, and mention that Siegel (1945) gave their formulae using a different route. In this paper tables are given from which the formulae of the generalized Fisher approach can easily be derived for the cases of factors. It is shown that these tables can easily be extended to cover the cases of r=5 and r=6 factors.

Suggested Citation

  • de Boer, P.M.C., 2008. "Energy decomposition analysis: the generalized Fisher index revisited," Econometric Institute Research Papers EI 2008-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:13049
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    References listed on IDEAS

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    1. Paul De Boer, 2008. "Additive Structural Decomposition Analysis and Index Number Theory: An Empirical Application of the Montgomery Decomposition," Economic Systems Research, Taylor & Francis Journals, vol. 20(1), pages 97-109.
    2. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    3. Paul De Boer, 2009. "Multiplicative Decomposition And Index Number Theory: An Empirical Application Of The Sato-Vartia Decomposition," Economic Systems Research, Taylor & Francis Journals, vol. 21(2), pages 163-174.
    4. Albrecht, Johan & Francois, Delphine & Schoors, Koen, 2002. "A Shapley decomposition of carbon emissions without residuals," Energy Policy, Elsevier, vol. 30(9), pages 727-736, July.
    5. Ang, B. W. & Liu, F. L. & Chew, E. P., 2003. "Perfect decomposition techniques in energy and environmental analysis," Energy Policy, Elsevier, vol. 31(14), pages 1561-1566, November.
    6. Sun, J. W., 1998. "Changes in energy consumption and energy intensity: A complete decomposition model," Energy Economics, Elsevier, vol. 20(1), pages 85-100, February.
    7. Chung, Hyun-Sik & Rhee, Hae-Chun, 2001. "A residual-free decomposition of the sources of carbon dioxide emissions: a case of the Korean industries," Energy, Elsevier, vol. 26(1), pages 15-30.
    8. de Boer, P.M.C., 2006. "Structural decomposition analysis and index number theory: an empirical application of the Montgomery decomposition," Econometric Institute Research Papers EI 2006-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Mark De Haan, 2001. "A Structural Decomposition Analysis of Pollution in the Netherlands," Economic Systems Research, Taylor & Francis Journals, vol. 13(2), pages 181-196.
    10. Ang, B.W. & Liu, F.L. & Chung, Hyun-Sik, 2004. "A generalized Fisher index approach to energy decomposition analysis," Energy Economics, Elsevier, vol. 26(5), pages 757-763, September.
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    Cited by:

    1. Jimenez, Raul & Mercado, Jorge, 2014. "Energy intensity: A decomposition and counterfactual exercise for Latin American countries," Energy Economics, Elsevier, vol. 42(C), pages 161-171.

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