A 1994 Social Accounting Matrix (SAM) for Peru

cg.authorship.typesCGIAR single centreen
cg.coverage.countryPeru
cg.coverage.iso3166-alpha2PE
cg.coverage.regionAmericas
cg.coverage.regionLatin America and the Caribbean
cg.coverage.regionSouth America
cg.identifier.projectIFPRI - Development Strategy and Governance Division
cg.identifier.publicationRankNot ranked
cg.identifier.urlhttps://hdl.handle.net/1902.1/11191en
cg.placeWashington, DCen
cg.reviewStatusInternal Reviewen
dc.contributor.authorInternational Food Policy Research Instituteen
dc.date.accessioned2024-06-04T09:44:02Zen
dc.date.available2024-06-04T09:44:02Zen
dc.identifier.urihttps://hdl.handle.net/10568/144258
dc.titleA 1994 Social Accounting Matrix (SAM) for Peruen
dcterms.abstractThe 1994 Social Accounting Matrix (SAM) for Peru was assembled as part of a project aimed at analyzing the distributive effects of trade liberalization in a general-equilibrium context. The SAM disaggregates the production activities, labor and households accounts, and opens up the possibility to engage in a detailed analysis of the productive structure of the economy, as well as of the income distribution channels. The accompanying documentation describes both, the macroeconomic and microeconomic SAMs, paying special attention to data sources, assumptions, and balancing procedures.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationInternational Food Policy Research Institute. 2005. A 1994 Social Accounting Matrix (SAM) for Peru. Washington, DC: International Food Policy Research Institute. http://hdl.handle.net/1902.1/11191. Harvard Dataverse. Version 1.en
dcterms.issued2005
dcterms.languageen
dcterms.licenseCC-BY-NC-3.0
dcterms.publisherInternational Food Policy Research Instituteen
dcterms.replaceshttps://ebrary.ifpri.org/digital/collection/p15738coll3/id/58en
dcterms.subjecttrade liberalizationen
dcterms.subjectproductionen
dcterms.subjecthouseholdsen
dcterms.subjectincome distributionen
dcterms.subjectlabouren
dcterms.subjectcomputable general equilibrium modelsen
dcterms.typeDataset

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