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Spotting Error Patterns in Input–Output Projections Using Location Quotients

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  • Xesús Pereira-López

    (Department of Quantitative Economics, University of Santiago de Compostela, 27002 Santiago de Compostela, Spain
    Institute of Development Studies of Galicia (IDEGA), University of Santiago de Compostela, 15706 Santiago de Compostela, Spain)

  • Napoleón Guillermo Sánchez-Chóez

    (Institute of Development Studies of Galicia (IDEGA), University of Santiago de Compostela, 15706 Santiago de Compostela, Spain
    Department of Organizational Studies and Human Development, National Polytechnic School, Quito 170525, Ecuador)

  • Melchor Fernández-Fernández

    (Institute of Development Studies of Galicia (IDEGA), University of Santiago de Compostela, 15706 Santiago de Compostela, Spain
    Department of Fundamentals of Economic Analysis, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain)

Abstract

The Sustainable Development Goals (SDGs) stated by the United Nations (UN) constitute a universal agenda committed to human rights. In this context, mathematics can perform a fundamental role. Exploring possible contributions to these goals could be considered an interesting approach. Input–output (IO) tables provide detailed information for socio-economic quantifications. Thus, they allow for more precise policy decision-making and application in the SDG strategy. However, the smaller the subnational unit to be considered, the less statistical information that is available. Survey-based IO tables with large product/industry disaggregation are seldom published. Therefore, non-survey methods to estimate subnational IO tables based on the national are needed. These methodologies should yield optimal results. In the present investigation, different formulations for these non-survey regionalization methods are analyzed. The work focuses on the methodologies based on location quotients ( LQ ). As a result, some error patterns associated with current formulations present in literature are described. A slight refinement of these methodologies is proposed in order to improve the estimation’s accuracy.

Suggested Citation

  • Xesús Pereira-López & Napoleón Guillermo Sánchez-Chóez & Melchor Fernández-Fernández, 2022. "Spotting Error Patterns in Input–Output Projections Using Location Quotients," Mathematics, MDPI, vol. 10(9), pages 1-19, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:9:p:1474-:d:803940
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    References listed on IDEAS

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    1. A. T. Flegg & C. D. Webber, 1997. "On the Appropriate Use of Location Quotients in Generating Regional Input-Output Tables: Reply," Regional Studies, Taylor & Francis Journals, vol. 31(8), pages 795-805.
    2. A. T. Flegg & C. D. Webber, 2000. "Regional Size, Regional Specialization and the FLQ Formula," Regional Studies, Taylor & Francis Journals, vol. 34(6), pages 563-569.
    3. Andrea Bonfiglio & Francesco Chelli, 2008. "Assessing the Behaviour of Non-Survey Methods for Constructing Regional Input-Output Tables through a Monte Carlo Simulation," Economic Systems Research, Taylor & Francis Journals, vol. 20(3), pages 243-258.
    4. William A. Schaffer & Kong Chu, 1969. "Nonsurvey Techniques For Constructing Regional Interindustry Models," Papers in Regional Science, Wiley Blackwell, vol. 23(1), pages 83-104, January.
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