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Appropriate assumption on cross-hauling national input–output table regionalization

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  • Takashi Fujimoto

Abstract

Input–output tables are useful for regional economic analyses. Although scholars often regionalize national input–output tables, cost-related issues make surveying regional trade flow difficult; hence, non-survey approaches are implemented instead. While location quotient (LQ) approaches have been used widely, they ignore cross-hauling in interregional trade. Therefore, alternative non-survey approaches with different assumptions on cross-hauling are used, such as cross-hauling depends on regional size and cross-hauling is proportional to its potential determined by output or demand. This study concludes that the most appropriate assumption, as per the relative performance of non-survey approaches, is that cross-hauling is in proportion to trade volume.

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  • Takashi Fujimoto, 2019. "Appropriate assumption on cross-hauling national input–output table regionalization," Spatial Economic Analysis, Taylor & Francis Journals, vol. 14(1), pages 106-128, January.
    • Handle: RePEc:taf:specan:v:14:y:2019:i:1:p:106-128
    DOI: 10.1080/17421772.2018.1506151
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    Cited by:

    1. A. V. Kotov, 2021. "Options for the Spatial Development of Russia in the Context of Interregional Interactions," Studies on Russian Economic Development, Springer, vol. 32(3), pages 318-324, May.
    2. Shogo Fukui, 2023. "Estimating Input Coefficients for Regional Input-Output Tables Using Deep Learning with Mixup," Papers 2305.01201, arXiv.org, revised May 2023.
    3. Marek Radvanský & Ivan Lichner, 2021. "An alternative approach to the construction of multi-regional input–output tables of the Czech Republic: application of the CHARM method," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(4), pages 1083-1111, November.
    4. Cristian Mardones & Darling Silva, 2023. "Evaluation of Non-survey Methods for the Construction of Regional Input–Output Matrices When There is Partial Historical Information," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1173-1205, March.

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