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A multi-fuel, multi-sector and multi-region approach to index decomposition: An application to China's energy consumption 1995–2010

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  • Ma, Chunbo

Abstract

Index Decomposition Analysis (IDA) has been extensively applied in studies of energy consumption and energy-related emissions. Most have focused on the impacts of industrial structural change and technology progress and a few have also looked at inter-fuel substitution. There has been no study examining spatial aspects within an IDA setting. This paper first describes an analytical framework analyzing driving forces behind a country's changing energy consumption with special highlights on the spatial dimension and then develops an IDA model to operationalize the analytical framework. The model is applied to a panel of 29 Chinese provinces over the period of 1995–2010. It is shown that the model not only captures the impact of changes of economic and human geography but also provides valuable insights and richer information on spatial variations of other contributing factors than conventional country-level analysis.

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  • 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.
  • Handle: RePEc:eee:eneeco:v:42:y:2014:i:c:p:9-16
    DOI: 10.1016/j.eneco.2013.11.009
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    as
    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. Jennifer Hunt, 2011. "Which Immigrants Are Most Innovative and Entrepreneurial? Distinctions by Entry Visa," Journal of Labor Economics, University of Chicago Press, vol. 29(3), pages 417-457.
    3. Ang, B.W & Zhang, F.Q & Choi, Ki-Hong, 1998. "Factorizing changes in energy and environmental indicators through decomposition," Energy, Elsevier, vol. 23(6), pages 489-495.
    4. Ang, B.W., 1995. "Decomposition methodology in industrial energy demand analysis," Energy, Elsevier, vol. 20(11), pages 1081-1095.
    5. Ang, B.W. & Mu, A.R. & Zhou, P., 2010. "Accounting frameworks for tracking energy efficiency trends," Energy Economics, Elsevier, vol. 32(5), pages 1209-1219, September.
    6. Cleveland, Cutler J. & Kaufmann, Robert K. & Stern, David I., 2000. "Aggregation and the role of energy in the economy," Ecological Economics, Elsevier, vol. 32(2), pages 301-317, February.
    7. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    8. Ma, Chunbo & Stern, David I., 2008. "China's changing energy intensity trend: A decomposition analysis," Energy Economics, Elsevier, vol. 30(3), pages 1037-1053, May.
    9. Ekholm, Tommi & Krey, Volker & Pachauri, Shonali & Riahi, Keywan, 2010. "Determinants of household energy consumption in India," Energy Policy, Elsevier, vol. 38(10), pages 5696-5707, October.
    10. 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.
    11. Zhao, Xiaoli & Li, Na & Ma, Chunbo, 2012. "Residential energy consumption in urban China: A decomposition analysis," Energy Policy, Elsevier, vol. 41(C), pages 644-653.
    12. Ma, Hengyun & Oxley, Les & Gibson, John, 2010. "China's energy economy: A survey of the literature," Economic Systems, Elsevier, vol. 34(2), pages 105-132, June.
    13. 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.
    14. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    15. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    16. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    17. Ma, Chunbo & Stern, David I., 2008. "Biomass and China's carbon emissions: A missing piece of carbon decomposition," Energy Policy, Elsevier, vol. 36(7), pages 2517-2526, July.
    18. 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.
    19. Liu, Na & Ang, B.W., 2007. "Factors shaping aggregate energy intensity trend for industry: Energy intensity versus product mix," Energy Economics, Elsevier, vol. 29(4), pages 609-635, July.
    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. 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.
    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. X. Q. Liu & B. W. Ang & H.L. Ong, 1992. "The Application of the Divisia Index to the Decomposition of Changes in Industrial Energy Consumption," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 161-178.
    24. Satoru Komatsu & Hieu Dinh Ha & Shinji Kaneko, 2012. "Effects of Internal Migration on Residential Energy Consumption and CO2 Emissions in Hanoi," IDEC DP2 Series 2-17, Hiroshima University, Graduate School for International Development and Cooperation (IDEC).
    25. Heltberg, Rasmus, 2004. "Fuel switching: evidence from eight developing countries," Energy Economics, Elsevier, vol. 26(5), pages 869-887, September.
    26. Sorrell, Steve & Lehtonen, Markku & Stapleton, Lee & Pujol, Javier & Champion, Toby, 2009. "Decomposing road freight energy use in the United Kingdom," Energy Policy, Elsevier, vol. 37(8), pages 3115-3129, August.
    27. 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.
    28. Wang, Chunhua, 2011. "Sources of energy productivity growth and its distribution dynamics in China," Resource and Energy Economics, Elsevier, vol. 33(1), pages 279-292, January.
    29. 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.
    30. 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).
    31. Ang, B.W. & Liu, Na, 2007. "Handling zero values in the logarithmic mean Divisia index decomposition approach," Energy Policy, Elsevier, vol. 35(1), pages 238-246, January.
    32. Miah, Md.Danesh & Foysal, Muhammad Abul & Koike, Masao & Kobayashi, Hajime, 2011. "Domestic energy-use pattern by the households: A comparison between rural and semi-urban areas of Noakhali in Bangladesh," Energy Policy, Elsevier, vol. 39(6), pages 3757-3765, June.
    33. Zhang, Ming & Guo, Fangyan, 2013. "Analysis of rural residential commercial energy consumption in China," Energy, Elsevier, vol. 52(C), pages 222-229.
    34. Wood, Richard & Lenzen, Manfred, 2006. "Zero-value problems of the logarithmic mean divisia index decomposition method," Energy Policy, Elsevier, vol. 34(12), pages 1326-1331, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Index decomposition analysis; Inter-fuel substitution; Spatial variation; Energy consumption; China;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • 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
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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