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Sector disaggregation, structural effect and industrial energy use: An approach to analyze the interrelationships

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  • Ang, B.W.

Abstract

In the analysis of industrial energy use, the energy impact of structural change has often been estimated at a certain level of sector disaggregation using one of a large number of decomposition methods available. Such an estimate has two limitations. First, it gives the “net” energy impact which is a residual value after cancellation of the positive and negative components of the structural effect. The cancellation conceals information on structural change useful in energy demand analysis and forecasting. Second, such an estimate is highly specific since it is valid only at the level of sector disaggregation considered. We discuss these two limitations and present some possible solutions. We describe the concept of cancellation and propose two indicators to measure it. We then introduce the decomposition tree approach which is a procedure for studying the influence of level of sector disaggregation in a systematic manner. The approach can be easily adopted in many decomposition methods and has several other useful applications.

Suggested Citation

  • Ang, B.W., 1993. "Sector disaggregation, structural effect and industrial energy use: An approach to analyze the interrelationships," Energy, Elsevier, vol. 18(10), pages 1033-1044.
    • Handle: RePEc:eee:energy:v:18:y:1993:i:10:p:1033-1044
    DOI: 10.1016/0360-5442(93)90052-F
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. Ma, Chunbo, 2014. "A multi-fuel, multi-sector and multi-region approach to index decomposition: An application to China's energy consumption 1995–2010," Energy Economics, Elsevier, vol. 42(C), pages 9-16.
    4. Tae Jung & Tae Park, 2000. "Structural Change of the Manufacturing Sector in Korea: Measurement of Real Energy Intensity and CO2 Emissions," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 5(3), pages 221-238, September.
    5. Su, Bin & Huang, H.C. & Ang, B.W. & Zhou, P., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of sector aggregation," Energy Economics, Elsevier, vol. 32(1), pages 166-175, January.
    6. Seck, Gondia Sokhna & Guerassimoff, Gilles & Maïzi, Nadia, 2016. "Analysis of the importance of structural change in non-energy intensive industry for prospective modelling: The French case," Energy Policy, Elsevier, vol. 89(C), pages 114-124.
    7. Greening, Lorna A. & Davis, William B. & Schipper, Lee & Khrushch, Marta, 1997. "Comparison of six decomposition methods: application to aggregate energy intensity for manufacturing in 10 OECD countries," Energy Economics, Elsevier, vol. 19(3), pages 375-390, July.
    8. repec:awi:wpaper:0422 is not listed on IDEAS
    9. Ang, B. W., 1995. "Multilevel decomposition of industrial energy consumption," Energy Economics, Elsevier, vol. 17(1), pages 39-51, January.
    10. Xu, X.Y. & Ang, B.W., 2014. "Multilevel index decomposition analysis: Approaches and application," Energy Economics, Elsevier, vol. 44(C), pages 375-382.
    11. Bruyn, Sander M. de, 1997. "Explaining the environmental Kuznets Curve: the case of sulphur emissions," Serie Research Memoranda 0013, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    12. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.

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