Regional input-output analysis is a widely used tool for regional scientists to study economic, social and environmental phenomena. Ever since its first steps, regional input-output analysis has suffered from the lack of adequate and detailed data at different subnational levels. The problem becomes particularly acute in less developed regions, where resources to gather information are seldom available. Scholars agree in that hybrid approaches to construct regional input-output models are the most cost-effective alternative. The aim of this thesis is to expand the toolbox that regional input-output modellers have in hand with new hybrid techniques. In this vein, I introduce three methodological alternatives that relax information requirements to solve certain modelling challenges.
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