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Decomposing the variation of aggregate electricity intensity in Spanish industry

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  • González, P.Fernández
  • Suárez, R.Pérez

Abstract

Several papers have dealt with methodological and application issues related to techniques for decomposing changes in environmental indicators. This paper aims to decompose changes in electricity intensity in Spanish industry and to explain the factors that contribute to these changes. Focusing on an energy intensity approach based on Divisia indices, we began by reviewing the two general parametric Divisia methods and six specific cases. In order to avoid obtaining significantly different results by using differing methods, all of them have been applied to Spanish data. Also two different disaggregation levels have been taken into consideration. Combined with electricity price analysis, the results of this paper indicate the poor contribution of structural change to substantial reductions in aggregate electricity intensity, and underline the role of innovation, development, diffusion and access to more efficient technologies as main contributors to the reduction of the energy/production ratio.

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  • González, P.Fernández & Suárez, R.Pérez, 2003. "Decomposing the variation of aggregate electricity intensity in Spanish industry," Energy, Elsevier, vol. 28(2), pages 171-184.
    • Handle: RePEc:eee:energy:v:28:y:2003:i:2:p:171-184
    DOI: 10.1016/S0360-5442(02)00086-5
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    References listed on IDEAS

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    Cited by:

    1. Lu, I.J. & Lin, Sue J. & Lewis, Charles, 2007. "Decomposition and decoupling effects of carbon dioxide emission from highway transportation in Taiwan, Germany, Japan and South Korea," Energy Policy, Elsevier, vol. 35(6), pages 3226-3235, June.
    2. Olanrewaju, O.A. & Jimoh, A.A. & Kholopane, P.A., 2012. "Integrated IDA–ANN–DEA for assessment and optimization of energy consumption in industrial sectors," Energy, Elsevier, vol. 46(1), pages 629-635.
    3. Olanrewaju, O.A. & Jimoh, A.A. & Kholopane, P.A., 2013. "Assessing the energy potential in the South African industry: A combined IDA-ANN-DEA (Index Decomposition Analysis-Artificial Neural Network-Data Envelopment Analysis) model," Energy, Elsevier, vol. 63(C), pages 225-232.
    4. Lin, Sue J. & Lu, I.J. & Lewis, Charles, 2006. "Identifying key factors and strategies for reducing industrial CO2 emissions from a non-Kyoto protocol member's (Taiwan) perspective," Energy Policy, Elsevier, vol. 34(13), pages 1499-1507, September.

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