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Disaggregating input–output tables in time: the temporal input–output framework

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  • Andre Fernandes Tomon Avelino

Abstract

The input–output framework has evolved dramatically since its initial formulation. New analytical techniques and extensions have allowed a more comprehensive assessment of the economy and expanded its applicability. Nonetheless, the core of the framework has remained unchanged: an annually compiled input–output table, which conveys monetary flows between sectors in a region in a particular year. Hence, the technical coefficients derived from it are ‘average’ input compositions, neglecting fluctuations in production capacity, seasonality and temporal shocks within that period. This paper develops a consistent methodology to disaggregate the annual input–output table in its time dimension in order to estimate intra-year input–output matrices with distinct technical structures for a particular year. The main advantages in relation to the annual model are to allow seasonal effects to be studied within the input–output framework, to better understand the process of coefficient change and to offer a more comprehensive dynamic view of production.

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  • Andre Fernandes Tomon Avelino, 2017. "Disaggregating input–output tables in time: the temporal input–output framework," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 313-334, July.
    • Handle: RePEc:taf:ecsysr:v:29:y:2017:i:3:p:313-334
    DOI: 10.1080/09535314.2017.1290587
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    2. Andre F. T. Avelino & Sandy Dall'erba, 2019. "Comparing the Economic Impact of Natural Disasters Generated by Different Input–Output Models: An Application to the 2007 Chehalis River Flood (WA)," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 85-104, January.
    3. Christopher Cotton & Bahman Kashi & Huw Lloyd‐Ellis & Frederic Tremblay & Brett Crowley, 2022. "Quantifying the economic impacts of COVID‐19 policy responses on Canada's provinces in (almost) real time," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 406-445, February.
    4. Baoline Chen & Tommaso Di Fonzo & Thomas Howells & Marco Marini, 2018. "The statistical reconciliation of time series of accounts between two benchmark revisions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 533-552, November.
    5. Su, Bin & Ang, B.W., 2022. "Improved granularity in input-output analysis of embodied energy and emissions: The use of monthly data," Energy Economics, Elsevier, vol. 113(C).
    6. Stanislav Shmelev & Harrison Roger Brook, 2021. "Macro Sustainability across Countries: Key Sector Environmentally Extended Input-Output Analysis," Sustainability, MDPI, vol. 13(21), pages 1-46, October.
    7. He, Kehan & Mi, Zhifu & Coffman, D'Maris & Guan, Dabo, 2022. "Using a linear regression approach to sequential interindustry model for time-lagged economic impact analysis," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 399-406.

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