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Aggregation Versus Disaggregation In Input-Output Analysis Of The Environment

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  • Manfred Lenzen
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    Abstract

    Analysts carrying out input-output analyses of environmental issues are often plagued by environmental and input-output data existing in different classifications, with environmentally sensitive sectors sometimes being aggregated in the economic input-output database. In principle there are two alternatives for dealing with such misalignment: either environmental data have to be aggregated into the input-output classification, which entails an undesirable loss of information, or input-output data have to be disaggregated based on fragmentary information. In this article, I show that disaggregation of input-output data, even if based on few real data points, is superior to aggregating environmental data in determining input-output multipliers. This is especially true if the disaggregated sectors are heterogeneous with respect to their economic and environmental characteristics. The results of this work may help analysts in understanding that disaggregation based on even a small amount of proxy information can improve the accuracy of input-output multipliers significantly. Perhaps, these results will also provide encouragement for preferring model disaggregation to aggregation in future work.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/09535314.2010.548793
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Economic Systems Research.

    Volume (Year): 23 (2011)
    Issue (Month): 1 ()
    Pages: 73-89

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    Handle: RePEc:taf:ecsysr:v:23:y:2011:i:1:p:73-89

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    Related research

    Keywords: Aggregation; Disaggregation; Environmentally-extended input-output analysis; Stochastic experiments;

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    Cited by:
    1. Su, Bin & Ang, B.W. & Low, Melissa, 2013. "Input–output analysis of CO2 emissions embodied in trade and the driving forces: Processing and normal exports," Ecological Economics, Elsevier, vol. 88(C), pages 119-125.
    2. Maaike Bouwmeester & Jan Oosterhaven, 2013. "Specification and Aggregation Errors in Environmentally Extended Input–Output Models," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 56(3), pages 307-335, November.
    3. Qi, Tianyu & Winchester, Niven & Karplus, Valerie J. & Zhang, Xiliang, 2014. "Will economic restructuring in China reduce trade-embodied CO2 emissions?," Energy Economics, Elsevier, vol. 42(C), pages 204-212.
    4. Zeng, Lin & Xu, Ming & Liang, Sai & Zeng, Siyu & Zhang, Tianzhu, 2014. "Revisiting drivers of energy intensity in China during 1997–2007: A structural decomposition analysis," Energy Policy, Elsevier, vol. 67(C), pages 640-647.

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