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Updating an Input-Output Matrix with Sign-preservation: Some Improved Objective Functions and their Solutions

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  • Wenfeng Huang
  • Shintaro Kobayashi
  • Hajime Tanji

Abstract

This paper presents an easy-to-use method for updating input-output (IO) matrices with sign-preservation by combining Lagrangian multipliers and penalty functions. Biproportional methods such as the representative RAS are very simple and popular because a target matrix can be obtained simply by iterative computation. However, they cannot reasonably deal with matrices that include negative entries. Although a generalized version, GRAS, can do so, its objective function is questionable. In contrast, some non-biproportional methods such as those that take weighted or unweighted squared differences between the target and original matrix as objective functions can deal with negative entries, but it is difficult to guarantee the signs of entries. In this study, GRAS and some conventional objective functions were improved and their solutions for preserving the signs of entries are presented. Comparisons of applying these objective functions to a simple example show that both the Improved Normalized Squared Differences (INSD) function and the Improved GRAS (IGRAS) function yield a good target matrix and are close to each other; we suggest that INSD or IGRAS be used for updating IO transaction matrices in practice.

Suggested Citation

  • Wenfeng Huang & Shintaro Kobayashi & Hajime Tanji, 2008. "Updating an Input-Output Matrix with Sign-preservation: Some Improved Objective Functions and their Solutions," Economic Systems Research, Taylor & Francis Journals, vol. 20(1), pages 111-123.
  • Handle: RePEc:taf:ecsysr:v:20:y:2008:i:1:p:111-123
    DOI: 10.1080/09535310801892082
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    References listed on IDEAS

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    Cited by:

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    7. Tamas Revesz, 2023. "A not sign-preserving iteration algorithm for the ‘Improved Normalized Squared Differences’ matrix adjustment model," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 49-71, March.
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    10. Jan Oosterhaven & Michiya Nozaki, 2014. "The impact of production and infrastructure shocks to the Japanese inter-regional economy: A non-linear input-output programming approach," ERSA conference papers ersa14p163, European Regional Science Association.
    11. Oosterhaven, J. & Bouwmeester, M.C. & Nozaki, M., 2013. "The impact of production and infrastructure shocks," Research Report 13017-GEM, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    12. Umed Temursho & Manuel Alejandro Cardenete & Krzysztof Wojtowicz & Luis Rey & Matthias Weitzel & Toon Vandyck & Bert Saveyn, 2020. "Projecting input-output tables for model baselines," JRC Research Reports JRC120513, Joint Research Centre.
    13. Manfred Lenzen & Maria Cecilia Pinto de Moura & Arne Geschke & Keiichiro Kanemoto & Daniel Dean Moran, 2012. "A Cycling Method For Constructing Input--Output Table Time Series From Incomplete Data," Economic Systems Research, Taylor & Francis Journals, vol. 24(4), pages 413-432, February.
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