IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v42y2014icp9-16.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988313002715
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2013.11.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ang, B.W., 1995. "Decomposition methodology in industrial energy demand analysis," Energy, Elsevier, vol. 20(11), pages 1081-1095.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. Heltberg, Rasmus, 2004. "Fuel switching: evidence from eight developing countries," Energy Economics, Elsevier, vol. 26(5), pages 869-887, September.
    14. 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.
    15. 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.
    16. 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).
    17. Zhang, Ming & Guo, Fangyan, 2013. "Analysis of rural residential commercial energy consumption in China," Energy, Elsevier, vol. 52(C), pages 222-229.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Duran, Elisa & Aravena, Claudia & Aguilar, Renato, 2015. "Analysis and decomposition of energy consumption in the Chilean industry," Energy Policy, Elsevier, vol. 86(C), pages 552-561.
    2. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.
    3. Fernández González, P. & Landajo, M. & Presno, M.J., 2013. "The Divisia real energy intensity indices: Evolution and attribution of percent changes in 20 European countries from 1995 to 2010," Energy, Elsevier, vol. 58(C), pages 340-349.
    4. Fernández González, P., 2015. "Exploring energy efficiency in several European countries. An attribution analysis of the Divisia structural change index," Applied Energy, Elsevier, vol. 137(C), pages 364-374.
    5. Wang, Miao & Feng, Chao, 2018. "Decomposing the change in energy consumption in China's nonferrous metal industry: An empirical analysis based on the LMDI method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2652-2663.
    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. 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.
    8. Banie Naser Outchiri, 2020. "Contributing to better energy and environmental analyses: how accurate are decomposition analysis results?," Cahiers de recherche 20-11, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    9. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    10. Román-Collado, Rocío & Cansino, José M. & Botia, Camilo, 2018. "How far is Colombia from decoupling? Two-level decomposition analysis of energy consumption changes," Energy, Elsevier, vol. 148(C), pages 687-700.
    11. Patiño, Lourdes Isabel & Alcántara, Vicent & Padilla, Emilio, 2021. "Driving forces of CO2 emissions and energy intensity in Colombia," Energy Policy, Elsevier, vol. 151(C).
    12. 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.
    13. 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.
    14. Du, Kerui & Xie, Chunping & Ouyang, Xiaoling, 2017. "A comparison of carbon dioxide (CO2) emission trends among provinces in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 19-25.
    15. Lin, Boqiang & Du, Kerui, 2014. "Decomposing energy intensity change: A combination of index decomposition analysis and production-theoretical decomposition analysis," Applied Energy, Elsevier, vol. 129(C), pages 158-165.
    16. Löschel, Andreas & Pothen, Frank & Schymura, Michael, 2015. "Peeling the onion: Analyzing aggregate, national and sectoral energy intensity in the European Union," Energy Economics, Elsevier, vol. 52(S1), pages 63-75.
    17. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    18. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    19. Lan, Jun & Malik, Arunima & Lenzen, Manfred & McBain, Darian & Kanemoto, Keiichiro, 2016. "A structural decomposition analysis of global energy footprints," Applied Energy, Elsevier, vol. 163(C), pages 436-451.
    20. Xuankai Deng & Yanhua Yu & Yanfang Liu, 2015. "Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011," Energies, MDPI, vol. 8(6), pages 1-22, June.

    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)

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:42:y:2014:i:c:p:9-16. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.