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Structural decomposition of energy use in Brazil from 1970 to 1996

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  • Wachsmann, Ulrike
  • Wood, Richard
  • Lenzen, Manfred
  • Schaeffer, Roberto
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    Abstract

    This paper examines the sources of changes in energy use of the Brazilian economy of industries and households from 1970 to 1996, using structural decomposition analysis based on the logarithmic mean divisia index technique. Energy use can be decomposed into eight factors that explain changes in overall energy use over the entire time period, and within five sub-periods. The growth of energy use between 1970 and 1996 was mainly influenced by changes in affluence, population and intersectoral dependencies, while changes in direct energy intensity and per capita residential energy use had a retarding impact on energy use. The novel contributions of the paper are the alignment of a previously disparate data set, the use of supply-use tables for SDA, and the application of such an SDA to a developing country. Both contributions involve solving a range of methodological issues pertaining to handling of large data sets.

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    Bibliographic Info

    Article provided by Elsevier in its journal Applied Energy.

    Volume (Year): 86 (2009)
    Issue (Month): 4 (April)
    Pages: 578-587

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    Handle: RePEc:eee:appene:v:86:y:2009:i:4:p:578-587

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    Keywords: Structural decomposition analysis Energy use Structural change;

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    Cited by:
    1. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
    2. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    3. Achão, Carla & Schaeffer, Roberto, 2009. "Decomposition analysis of the variations in residential electricity consumption in Brazil for the 1980-2007 period: Measuring the activity, intensity and structure effects," Energy Policy, Elsevier, vol. 37(12), pages 5208-5220, December.
    4. Wiedmann, Thomas, 2009. "A review of recent multi-region input-output models used for consumption-based emission and resource accounting," Ecological Economics, Elsevier, vol. 69(2), pages 211-222, December.
    5. Rodrigues, João F.D. & Rueda-Cantuche, José M., 2013. "A two-stage econometric method for the estimation of carbon multipliers with rectangular supply and use tables," Ecological Economics, Elsevier, vol. 95(C), pages 206-212.
    6. Chai, Jian & Guo, Ju-E & Wang, Shou-Yang & Lai, Kin Keung, 2009. "Why does energy intensity fluctuate in China?," Energy Policy, Elsevier, vol. 37(12), pages 5717-5731, December.
    7. Tan, Zhongfu & Li, Li & Wang, Jianjun & Wang, Jianhui, 2011. "Examining the driving forces for improving China’s CO2 emission intensity using the decomposing method," Applied Energy, Elsevier, vol. 88(12), pages 4496-4504.
    8. Zhang, Ming & Li, Huanan & Zhou, Min & Mu, Hailin, 2011. "Decomposition analysis of energy consumption in Chinese transportation sector," Applied Energy, Elsevier, vol. 88(6), pages 2279-2285, June.
    9. Choi, Ki-Hong & Ang, B.W., 2012. "Attribution of changes in Divisia real energy intensity index — An extension to index decomposition analysis," Energy Economics, Elsevier, vol. 34(1), pages 171-176.

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