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Additive Structural Decomposition Analysis and Index Number Theory: An Empirical Application of the Montgomery Decomposition

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  • Paul De Boer
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    Abstract

    In recent years, a large number of empirical articles on structural decomposition analysis, which aims at disentangling an aggregate change in a variable into its r factors, has been published in this journal. Commonly used methods are the average of the two polar decompositions and the average of all r! elementary decompositions (Dietzenbacher and Los, 1998, D&L). We propose to use instead the 'ideal' Montgomery decomposition, which means that it satisfies the requirement of factor reversal imposed in index number theory. We prefer it to the methods previously mentioned. The average of the two polar decompositions is not 'ideal', so that the outcome depends on the ordering of the factors. The average of all elementary decompositions is 'ideal', but requires the computation of an ever increasing number of decompositions when the number of factors increases. Application to the example of D&L (four factors) shows that the three methods yield results that are close to each other.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/09535310801892066
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    Article provided by Taylor & Francis Journals in its journal Economic Systems Research.

    Volume (Year): 20 (2008)
    Issue (Month): 1 ()
    Pages: 97-109

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    Handle: RePEc:taf:ecsysr:v:20:y:2008:i:1:p:97-109
    DOI: 10.1080/09535310801892066
    Contact details of provider: Web page: http://www.tandfonline.com/CESR20

    Order Information: Web: http://www.tandfonline.com/pricing/journal/CESR20

    Keywords: Additive decomposition; index number theory; structural decomposition analysis;

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    1. Jose Miguel Albala-Bertrand, 1999. "Structural Change in Chile: 1960-90," Economic Systems Research, Taylor & Francis Journals, vol. 11(3), pages 301-320.
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    7. Erik Dietzenbacher & Jesper Stage, 2006. "Mixing oil and water? Using hybrid input-output tables in a Structural decomposition analysis," Economic Systems Research, Taylor & Francis Journals, vol. 18(1), pages 85-95.
    8. Aying Liu & David Saal, 2001. "Structural Change in Apartheid-era South Africa: 1975-93," Economic Systems Research, Taylor & Francis Journals, vol. 13(3), pages 235-257.
    9. Rolando Alcala & Gabrielle Antille & Emilio Fontela, 1999. "Technical Change in the Private Consumption Converter," Economic Systems Research, Taylor & Francis Journals, vol. 11(4), pages 389-400.
    10. Henrik Jacobsen, 2000. "Energy Demand, Structural Change and Trade: A Decomposition Analysis of the Danish Manufacturing Industry," Economic Systems Research, Taylor & Francis Journals, vol. 12(3), pages 319-343.
    11. Hoekstra, Rutger & van den Bergh, Jeroen C. J. M., 2003. "Comparing structural decomposition analysis and index," Energy Economics, Elsevier, vol. 25(1), pages 39-64, January.
    12. Mark De Haan, 2001. "A Structural Decomposition Analysis of Pollution in the Netherlands," Economic Systems Research, Taylor & Francis Journals, vol. 13(2), pages 181-196.
    13. Glen Peters & Edgar Hertwich, 2006. "Structural analysis of international trade: Environmental impacts of Norway," Economic Systems Research, Taylor & Francis Journals, vol. 18(2), pages 155-181.
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    Cited by:

    1. 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.
    2. 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.
    3. Saari, M. Yusof & Dietzenbacher, Erik & Los, Bart, 2015. "Sources of Income Growth and Inequality Across Ethnic Groups in Malaysia, 1970–2000," World Development, Elsevier, vol. 76(C), pages 311-328.
    4. Jialing Zou & Weidong Liu & Zhipeng Tang, 2017. "Analysis of Factors Contributing to Changes in Energy Consumption in Tangshan City between 2007 and 2012," Sustainability, MDPI, Open Access Journal, vol. 9(3), pages 1-14, March.
    5. Mingxiang Deng & Wei Li & Yan Hu, 2016. "Decomposing Industrial Energy-Related CO 2 Emissions in Yunnan Province, China: Switching to Low-Carbon Economic Growth," Energies, MDPI, Open Access Journal, vol. 9(1), pages 1-19, January.
    6. Edward, T. Huw & Lücke, Matthias, 2011. "Decompositions of wage inequality and growth in an advanced economy open to trade," Kiel Working Papers 1749, Kiel Institute for the World Economy (IfW).
    7. 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.
    8. de Boer, P.M.C., 2008. "Energy decomposition analysis: the generalized Fisher index revisited," Econometric Institute Research Papers EI 2008-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. repec:gam:jeners:v:9:y:2016:i:1:p:23:d:61618 is not listed on IDEAS

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