Closing the gaps in experimental and observational crop response estimates: a Bayesian approach

cg.contributor.affiliationInternational Maize and Wheat Improvement Centeren
cg.contributor.affiliationUniversity of Minnesotaen
cg.contributor.donorBill & Melinda Gates Foundationen
cg.contributor.donorMcKnight Foundationen
cg.contributor.donorCGIAR Trust Funden
cg.contributor.initiativeExcellence in Agronomy
cg.coverage.countryMalawi
cg.coverage.iso3166-alpha2MW
cg.coverage.regionEastern Africa
cg.creator.identifierMaxwell Mkondiwa: 0000-0003-0008-9095
cg.creator.identifierTerrance Hurley: 0000-0003-2135-7570
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.1093/qopen/qoae017en
cg.issn2633-9048en
cg.issue2en
cg.journalQ Openen
cg.reviewStatusPeer Reviewen
cg.subject.actionAreaResilient Agrifood Systems
cg.subject.impactAreaClimate adaptation and mitigation
cg.subject.impactAreaNutrition, health and food security
cg.volume4en
dc.contributor.authorMkondiwa, Maxwellen
dc.contributor.authorHurley, Terrance M.en
dc.contributor.authorPardey, Philip G.en
dc.date.accessioned2024-08-21T19:08:50Zen
dc.date.available2024-08-21T19:08:50Zen
dc.identifier.urihttps://hdl.handle.net/10568/151784
dc.titleClosing the gaps in experimental and observational crop response estimates: a Bayesian approachen
dcterms.abstractA stylized fact of African agriculture is that crop responses to inorganic fertilizer application derived from experimental studies are often substantially greater than those from observational studies (e.g., surveys and administrative data). Recent debates on relative costs and benefits of expensive farm input subsidy programs in Africa, have raised the importance of reconciling these estimates. Beyond mean response differences, this paper argues for including parameter uncertainty and heterogeneity arising from variations in soil types, environmental conditions, and management practices. We use a Bayesian approach that combines information from experimental and observational data to model uncertainty and heterogeneity in crop yield responses. Using nationally representative experimental, survey, and administrative datasets from Malawi, we find that: (1) crop responses are low in observational data, (2) there are large spatial heterogeneities, and (3) based on sensitivity analysis, ignoring parameter uncertainty and spatial heterogeneity in crop responses can lead to questionable policy prescriptions.en
dcterms.accessRightsOpen Access
dcterms.available2024-07-23
dcterms.bibliographicCitationMkondiwa, M., Hurley, T.M., & Pardey, P.G. (2024). Closing the gaps in experimental and observational crop response estimates: a Bayesian approach. Q Open, 4(2), qoae017. https://doi.org/10.1093/qopen/qoae017en
dcterms.hasVersionhttps://hdl.handle.net/10883/34657en
dcterms.issued2024-07
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherOxford University Pressen
dcterms.subjectbayesian theoryen
dcterms.subjectcropsen
dcterms.subjectyield gapen
dcterms.typeJournal Article

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