Generating gridded agricultural gross domestic product for Brazil : A comparison of methodologies

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cg.authorship.typesCGIAR single centreen_US
cg.contributor.crpPolicies, Institutions, and Marketsen_US
cg.contributor.donorDepartment for International Development, United Kingdomen_US
cg.contributor.donorWorld Banken_US
cg.coverage.countryBrazilen_US
cg.coverage.iso3166-alpha2BRen_US
cg.coverage.regionSouth Americaen_US
cg.creator.identifierTimothy Thomas: 0000-0002-7951-8157en_US
cg.creator.identifierLiangzhi You: 0000-0001-7930-8814en_US
cg.creator.identifierUlrike Wood-Sichra: 0000-0002-0546-2074en_US
cg.creator.identifierYating Ru: 0000-0001-9071-0687en_US
cg.identifier.doihttps://doi.org/10.1596/1813-9450-8985en_US
cg.identifier.projectIFPRI - Environment and Production Technology Divisionen_US
cg.identifier.publicationRankNot rankeden_US
cg.number8985en_US
cg.reviewStatusInternal Reviewen_US
dc.contributor.authorThomas, Timothy S.en_US
dc.contributor.authorYou, Liangzhien_US
dc.contributor.authorWood-Sichra, Ulrikeen_US
dc.contributor.authorRu, Yatingen_US
dc.contributor.authorBlankespoor, Brianen_US
dc.contributor.authorKalvelagen, Erwinen_US
dc.date.accessioned2024-06-21T09:11:03Zen_US
dc.date.available2024-06-21T09:11:03Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/147075en_US
dc.titleGenerating gridded agricultural gross domestic product for Brazil : A comparison of methodologiesen_US
dcterms.abstractThis paper examines two new methods to generate gridded agricultural Gross Domestic Product (GDP) and compares the results with a traditional method. In the case of Brazil, these two new methods of spatial disaggregation and cross-entropy outperform the prediction of agricultural GDP from the traditional method that distributes agricultural GDP using rural population. The paper finds that the best prediction method is spatial disaggregation using a regression approach for all the key crops and contributors to agricultural GDP. However, the issue of degrees of freedom is an important limiting factor, as the approach requires sufficient subnational data. The cross-entropy method with readily available spatially distributed crop, livestock, forest, and fish allocation far outperforms the traditional method, at least in the case of Brazil, and can operate with nationaland/or subnational-level data.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationThomas, Timothy S.; You, Liangzhi; Wood-Sichra, Ulrike; Ru, Yating; Blankespoor, Brian; and Kalvelagen, Erwin. 2019. Generating gridded agricultural gross domestic product for Brazil : A comparison of methodologies. Policy Research Working Paper 8985. https://doi.org/10.1596/1813-9450-8985en_US
dcterms.isPartOfPolicy Research Working Paperen_US
dcterms.issued2019-12-13en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-3.0-IGOen_US
dcterms.publisherWorld Banken_US
dcterms.replaceshttps://ebrary.ifpri.org/digital/collection/p15738coll5/id/7004en_US
dcterms.subjectgross agricultural producten_US
dcterms.subjectspatial dataen_US
dcterms.subjectregional accountingen_US
dcterms.subjectspatial distributionen_US
dcterms.subjectagricultureen_US
dcterms.subjectgross national producten_US
dcterms.typeWorking Paperen_US

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