Publication:
A new perspective for the calculation of Ghosh-like forward multipliers

dc.contributor.authorLima Díaz, M. Carmen
dc.contributor.authorSancho, Ferran
dc.date.accessioned2026-06-22T09:14:56Z
dc.date.available2026-06-22T09:14:56Z
dc.date.issued2026-05-19
dc.descriptionProyectos de investigación PAIDI SEJ 511 Climamodel
dc.description.abstractThe tools currently used to identify and measure forward effects in disaggregated multi-sector models are widely considered inadequate. While the multi-sector approach is broadly accepted, the Ghosh classical model (1958), commonly employed in these analyses, has faced substantial criticism for two primary reasons. First, the model fails to accurately represent the technological characteristics of a market economy. Second, it gives rise to conceptual inconsistencies in the relationship between value-added and output levels. To overcome these limitations, we propose a new and straightforward replication method, grounded in standard theory, for identifying and measuring forward effects. Although this approach departs from the Ghosh model, it retains the core principle of examining the dependence of output on value-added.
dc.description.sponsorshipDepartamento Economía, Métodos Ciamtitativos e Historia Económica
dc.format.mimetypeapplication/pdf
dc.identifier.citationStructural Change and Economic Dynamics, Vol 79, August 2026, p. 262-268
dc.identifier.doi10.1016/j.strueco.2026.05.006
dc.identifier.urihttps://hdl.handle.net/10433/27032
dc.language.isoen
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectForward linkages
dc.subjectMultiplier matrices
dc.subjectValue added drivers
dc.titleA new perspective for the calculation of Ghosh-like forward multipliers
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication6ec36481-35c5-4407-bb47-5eeefdb4665a
relation.isAuthorOfPublication.latestForDiscovery6ec36481-35c5-4407-bb47-5eeefdb4665a

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