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

  • Paul De Boer
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    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
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    1. 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.
    2. 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.
    3. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    4. Kiyoshi Fujikawa & Carlo Milana, 2002. "Input-Output Decomposition Analysis of Sectoral Price Gaps between Japan and China," Economic Systems Research, Taylor & Francis Journals, vol. 14(1), pages 59-79.
    5. Erik Dietzenbacher & Bart Los, 2000. "Structural Decomposition Analyses with Dependent Determinants," Economic Systems Research, Taylor & Francis Journals, vol. 12(4), pages 497-514.
    6. 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.
    7. 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.
    8. Jose Miguel Albala-Bertrand, 1999. "Structural Change in Chile: 1960-90," Economic Systems Research, Taylor & Francis Journals, vol. 11(3), pages 301-320.
    9. Kazumi Hitomi & Yasuhide Okuyama & Geoffrey Hewings & Michael Sonis, 2000. "The Role of Interregional Trade in Generating Change in the Regional Economies of Japan, 1980-1990," Economic Systems Research, Taylor & Francis Journals, vol. 12(4), pages 515-537.
    10. 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.
    11. 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.
    12. 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.
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