• Medientyp: E-Artikel
  • Titel: Spotting Error Patterns in Input–Output Projections Using Location Quotients
  • Beteiligte: Pereira-López, Xesús; Sánchez-Chóez, Napoleón Guillermo; Fernández-Fernández, Melchor
  • Erschienen: MDPI AG, 2022
  • Erschienen in: Mathematics, 10 (2022) 9, Seite 1474
  • Sprache: Englisch
  • DOI: 10.3390/math10091474
  • ISSN: 2227-7390
  • Schlagwörter: General Mathematics ; Engineering (miscellaneous) ; Computer Science (miscellaneous)
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  • Beschreibung: <jats:p>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.</jats:p>
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