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Index decomposition analysis with multidimensional and multilevel energy data

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  • Ang, B.W.
  • Wang, H.

Abstract

Index decomposition analysis (IDA) is a popular tool for analyzing changes in energy consumption over time. Traditionally, a typical IDA study uses a single dimensional energy dataset, such as industrial energy consumption by industrial sector or transportation energy consumption by transport mode. More recently, there have been a growing number of studies using more sophisticated datasets, e.g. energy consumption by geographical region and by economic sector in a single dataset. For IDA studies using energy data with multiple attributes, intermediate decomposition results can be generated using subsets of the entire dataset, and these results provide further insight into the energy system and problem studied. To ensure that these intermediate results are consistent and meaningful, the IDA method used should ideally satisfy two properties: perfect in decomposition at the subcategory level and consistency in aggregation. It is shown that the logarithmic mean Divisia index method I (LMDI-I) satisfies these two properties in both additive and multiplicative decomposition analysis. It is therefore the recommended IDA method when dealing with energy data with multiple attributes.

Suggested Citation

  • Ang, B.W. & Wang, H., 2015. "Index decomposition analysis with multidimensional and multilevel energy data," Energy Economics, Elsevier, vol. 51(C), pages 67-76.
  • Handle: RePEc:eee:eneeco:v:51:y:2015:i:c:p:67-76
    DOI: 10.1016/j.eneco.2015.06.004
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    References listed on IDEAS

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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.
    2. Das, Aparna & Paul, Saikat Kumar, 2014. "CO2 emissions from household consumption in India between 1993–94 and 2006–07: A decomposition analysis," Energy Economics, Elsevier, vol. 41(C), pages 90-105.
    3. 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.
    4. Xu, X.Y. & Ang, B.W., 2014. "Analysing residential energy consumption using index decomposition analysis," Applied Energy, Elsevier, vol. 113(C), pages 342-351.
    5. Xu, X.Y. & Ang, B.W., 2014. "Multilevel index decomposition analysis: Approaches and application," Energy Economics, Elsevier, vol. 44(C), pages 375-382.
    6. Diewert, W Erwin, 1978. "Superlative Index Numbers and Consistency in Aggregation," Econometrica, Econometric Society, vol. 46(4), pages 883-900, July.
    7. Branger, Frédéric & Quirion, Philippe, 2015. "Reaping the carbon rent: Abatement and overallocation profits in the European cement industry, insights from an LMDI decomposition analysis," Energy Economics, Elsevier, vol. 47(C), pages 189-205.
    8. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    9. 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.
    10. G. Boyd & J. F. McDonald & M. Ross & D. A. Hansont, 1987. "Separating the Changing Composition of U.S. Manufacturing Production from Energy Efficiency Improvements: A Divisia Index Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 77-96.
    11. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Multilevel LMDI decomposition of changes in aggregate energy consumption. A cross country analysis in the EU-27," Energy Policy, Elsevier, vol. 68(C), pages 576-584.
    12. Donglan, Zha & Dequn, Zhou & Peng, Zhou, 2010. "Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis," Energy Policy, Elsevier, vol. 38(7), pages 3377-3383, July.
    13. Liu, Zhu & Geng, Yong & Lindner, Soeren & Guan, Dabo, 2012. "Uncovering China’s greenhouse gas emission from regional and sectoral perspectives," Energy, Elsevier, vol. 45(1), pages 1059-1068.
    14. Xu, Jin-Hua & Fan, Ying & Yu, Song-Min, 2014. "Energy conservation and CO2 emission reduction in China's 11th Five-Year Plan: A performance evaluation," Energy Economics, Elsevier, vol. 46(C), pages 348-359.
    15. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    16. 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.
    17. 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.
    18. Kesicki, Fabian & Anandarajah, Gabrial, 2011. "The role of energy-service demand reduction in global climate change mitigation: Combining energy modelling and decomposition analysis," Energy Policy, Elsevier, vol. 39(11), pages 7224-7233.
    19. 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.
    20. Ma, Chunbo, 2010. "Account for sector heterogeneity in China's energy consumption: Sector price indices vs. GDP deflator," Energy Economics, Elsevier, vol. 32(1), pages 24-29, January.
    21. Ang, BW, 1994. "Decomposition of industrial energy consumption : The energy intensity approach," Energy Economics, Elsevier, vol. 16(3), pages 163-174, July.
    22. 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.
    23. Wang, Wenwen & Liu, Xiao & Zhang, Ming & Song, Xuefeng, 2014. "Using a new generalized LMDI (logarithmic mean Divisia index) method to analyze China's energy consumption," Energy, Elsevier, vol. 67(C), pages 617-622.
    24. 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.
    25. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    26. Ang, B.W. & Huang, H.C. & Mu, A.R., 2009. "Properties and linkages of some index decomposition analysis methods," Energy Policy, Elsevier, vol. 37(11), pages 4624-4632, November.
    27. Petrick, Sebastian, 2013. "Carbon efficiency, technology, and the role of innovation patterns: Evidence from German plant-level microdata," Kiel Working Papers 1833, Kiel Institute for the World Economy (IfW Kiel).
    28. Ang, B. W. & Lee, S. Y., 1994. "Decomposition of industrial energy consumption : Some methodological and application issues," Energy Economics, Elsevier, vol. 16(2), pages 83-92, April.
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    More about this item

    Keywords

    Index decomposition analysis; LMDI; Multidimensional data;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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