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Incorporating data quality improvement into supply–use table balancing

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  • Martin C. Serpell

Abstract

This paper investigates the benefits of using a boundary tightening algorithm to improve the quality of the data used in supply and use table (SUT) balancing, building on similarities with certain approaches to statistical disclosure control. Boundary tightening was shown to significantly improve the quality of the finally balanced SUTs well beyond that of existing techniques. Most notably, improvements occurred when boundary tightening was applied prior to the balancing process – showing that it can be used as a valuable preliminary to other approaches. It also multiplied the improvement in SUTs quality when more accurate updated information was added to the SUTs. The findings of this paper strongly suggest that this boundary tightening algorithm will improve the quality of the output of the balancing process and it is equally likely to be useful when applied to other processes that handle uncertain data.

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  • Martin C. Serpell, 2018. "Incorporating data quality improvement into supply–use table balancing," Economic Systems Research, Taylor & Francis Journals, vol. 30(2), pages 271-288, April.
    • Handle: RePEc:taf:ecsysr:v:30:y:2018:i:2:p:271-288
    DOI: 10.1080/09535314.2017.1396962
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    Cited by:

    1. Venkata Sai Gargeya Vunnava & Jaewoo Shin & Lan Zhao & Shweta Singh, 2022. "PIOT‐Hub ‐ A collaborative cloud tool for generation of physical input–output tables using mechanistic engineering models," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 107-120, February.

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