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Construction, Stability And Predictability Of An Input-Output Time-Series For Australia

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  • Richard Wood

Abstract

This paper documents the development of a time series of Australian input-output tables. It describes the construction techniques employed in order to overcome the major issues encountered. Environmentally important processes were delineated using a range of detailed commodity data, thus expanding the original tables from roughly 100 industries into a temporally consistent 344 industries. Data confidentiality and inconsistency were overcome using an iterative constrained optimisation method called KRAS - a recent modification of RAS (Lenzen et al. 2006; 2007; 2009). The article concludes by analysing the stability of input-output coefficients over time similar to work in Dietzenbacher and Hoen (2006). The issue of stability of coefficients and multipliers was investigated under the Leontief and Ghosh models of supply/demand. Finally, the predictability of the models was examined under updated final demand or primary inputs and over varying time scales.

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  • Richard Wood, 2011. "Construction, Stability And Predictability Of An Input-Output Time-Series For Australia," Economic Systems Research, Taylor & Francis Journals, vol. 23(2), pages 175-211.
    • Handle: RePEc:taf:ecsysr:v:23:y:2011:i:2:p:175-211
    DOI: 10.1080/09535314.2011.564156
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    1. Marco Percoco & Geoffrey Hewings & Lanfranco Senn, 2006. "Structural change decomposition through a global sensitivity analysis of input-output models," Economic Systems Research, Taylor & Francis Journals, vol. 18(2), pages 115-131.
    2. R C Jensen & G R West, 1980. "The Effect of Relative Coefficient Size on Input—Output Multipliers," Environment and Planning A, , vol. 12(6), pages 659-670, June.
    3. Randall Jackson & Alan Murray, 2004. "Alternative Input-Output Matrix Updating Formulations," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 135-148.
    4. Donald Gilchrist & Larry St. Louis, 2004. "An Algorithm for the Consistent Inclusion of Partial Information in the Revision of Input-Output Tables," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 149-156.
    5. Manfred Lenzen & Richard Wood & Blanca Gallego, 2007. "Some Comments on the GRAS Method," Economic Systems Research, Taylor & Francis Journals, vol. 19(4), pages 461-465.
    6. Donald Gilchrist & Larry V. ST Louis, 1999. "Completing Input-Output Tables using Partial Information, with an Application to Canadian Data," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 185-194.
    7. Utz-Peter Reich, 2008. "Additivity of Deflated Input-Output Tables in National Accounts," Economic Systems Research, Taylor & Francis Journals, vol. 20(4), pages 415-428.
    8. Erik Dietzenbacher & Alex Hoen, 2006. "Coefficient stability and predictability in input-output models: a comparative analysis for the Netherlands," Construction Management and Economics, Taylor & Francis Journals, vol. 24(7), pages 671-680.
    9. Louis de Mesnard, 2004. "Biproportional Methods of Structural Change Analysis: A Typological Survey," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 205-230.
    10. Michael Lahr & Louis de Mesnard, 2004. "Biproportional Techniques in Input-Output Analysis: Table Updating and Structural Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 115-134.
    11. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    12. M Thissen & H Löfgren, 1998. "A New Approach to SAM Updating with an Application to Egypt," Environment and Planning A, , vol. 30(11), pages 1991-2003, November.
    13. Louis de Mesnard, 1997. "A biproportional filter to compare technical and allocation coefficient variations," Post-Print hal-00383934, HAL.
    14. Bon, Ranko, 1986. "Comparative stability analysis of demand-side and supply-side input-output models," International Journal of Forecasting, Elsevier, vol. 2(2), pages 231-235.
    15. 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.
    16. 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.
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    Cited by:

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    2. Rodrigo Mesa-Arango & Badri Narayanan & Satish V. Ukkusuri, 2019. "The Impact of International Crises on Maritime Transportation Based Global Value Chains," Networks and Spatial Economics, Springer, vol. 19(2), pages 381-408, June.
    3. Nicolas Garrido & Jeffrey Morales, 2023. "An analysis of the effect of fiscal expenditure on the income distribution of Chilean households," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-19, December.
    4. Joya, Omar & Rougier, Eric, 2019. "Do (all) sectoral shocks lead to aggregate volatility? Empirics from a production network perspective," European Economic Review, Elsevier, vol. 113(C), pages 77-107.
    5. López, Luis-Antonio & Tobarra, Maria-Angeles & Cadarso, Maria-Ángeles & Gómez, Nuria & Cazcarro, Ignacio, 2022. "Eating local and in-season fruits and vegetables: Carbon-water-employment trade-offs and synergies," Ecological Economics, Elsevier, vol. 192(C).
    6. Rocco, Matteo V. & Golinucci, Nicolò & Ronco, Stefano M. & Colombo, Emanuela, 2020. "Fighting carbon leakage through consumption-based carbon emissions policies: Empirical analysis based on the World Trade Model with Bilateral Trades," Applied Energy, Elsevier, vol. 274(C).
    7. Saari, M. Yusof & Dietzenbacher, Erik & Los, Bart, 2016. "The impacts of petroleum price fluctuations on income distribution across ethnic groups in Malaysia," Ecological Economics, Elsevier, vol. 130(C), pages 25-36.

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