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An Algorithm for Balancing Commodity-flow Systems

Author

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  • Esben Dalgaard
  • Christian Gysting

Abstract

In many cases there is a need to balance commodity-flow system data quickly and with limited resources. In order to compile new supply and use tables and investment matrices consistent with revised national accounts data, it can be necessary to apply some sort of automatic balancing technique. The paper proposes an algorithm that, contrary to RAS, can balance a commodity-flow system with unequal net row and column sums. The algorithm is applied to a recent revision of Danish capital stock estimates.

Suggested Citation

  • Esben Dalgaard & Christian Gysting, 2004. "An Algorithm for Balancing Commodity-flow Systems," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 169-190.
    • Handle: RePEc:taf:ecsysr:v:16:y:2004:i:2:p:169-190
    DOI: 10.1080/0953531042000219295
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    Cited by:

    1. Sargento, Ana Lúcia Marto & Lahr, Michael L. & Ferreira, João Pedro & de la Torre Cuevas, Fernando, 2024. "Revisiting methods for estimating interregional input-output accounts: It's not just about trade flows," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 664-677.
    2. Cobb, Marcus P A, 2017. "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper 76556, University Library of Munich, Germany.
    3. M. Alejandro Cardenete & M. Carmen Delgado & Patricia D. Fuentes & M. Carmen Lima & Alfredo J. Mainar & Jose M. Rueda-Cantuche & Sébastien Mary & Fabien Santini & Sergio Gomez y Paloma, 2015. "Rural-urban social accounting matrixes for modelling the impact of rural development policies in the EU," JRC Research Reports JRC94394, Joint Research Centre.
    4. Juan Manuel Valderas‐Jaramillo & José Manuel Rueda‐Cantuche, 2021. "The multidimensional nD‐GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1599-1624, December.
    5. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.

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