Publication:
Estimating the Impact of Weather on Agriculture

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dc.contributor.authorMichler, Jeffrey D.
dc.contributor.authorJosephson, Anna
dc.contributor.authorKilic, Talip
dc.contributor.authorMurray, Siobhan
dc.date.accessioned2021-12-03T14:44:35Z
dc.date.available2021-12-03T14:44:35Z
dc.date.issued2021-11
dc.description.abstractThis paper quantifies the significance and magnitude of the effect of measurement error in remote sensing weather data in the analysis of smallholder agricultural productivity. The analysis leverages 17 rounds of nationally-representative, panel household survey data from six countries in Sub-Saharan Africa. These data are spatially linked with a range of geospatial weather data sources and related metrics. The paper provides systematic evidence on measurement error introduced by (1) different methods used to obfuscate the exact GPS coordinates of households, (2) different metrics used to quantify precipitation and temperature, and (3) different remote sensing measurement technologies. First, the analysis finds no discernible effect of measurement error introduced by different obfuscation methods. Second, it finds that simple weather metrics, such as total seasonal rainfall and mean daily temperature, outperform more complex metrics, such as deviations in rainfall from the long-run average or growing degree days, in a broad range of settings. Finally, the analysis finds substantial amounts of measurement error based on remote sensing products. In extreme cases, the data drawn from different remote sensing products result in opposite signs for coefficients on weather metrics, meaning that precipitation or temperature drawn from one product purportedly increases crop output while the same metrics drawn from a different product purportedly reduces crop output. The paper concludes with a set of six best practices for researchers looking to combine remote sensing weather data with socioeconomic survey data.en
dc.identifierhttp://documents.worldbank.org/curated/undefined/235241638281693198/Estimating-the-Impact-of-Weather-on-Agriculture
dc.identifier.doi10.1596/1813-9450-9867
dc.identifier.urihttps://hdl.handle.net/10986/36643
dc.languageEnglish
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 9867
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectREMOTE SENSING
dc.subjectAGRICULTURAL PRODUCTIVITY
dc.subjectCROP YIELD
dc.subjectWEATHER IMPACTS
dc.subjectPRECIPITATION
dc.subjectTEMPERATURE
dc.titleEstimating the Impact of Weather on Agricultureen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleEstimating the Impact of Weather on Agriculture
okr.date.disclosure2021-11-30
okr.date.doiregistration2025-04-10T11:15:39.286950Z
okr.date.lastmodified2021-11-30T00:00:00Zen
okr.doctypePublications & Research
okr.doctypePublications & Research::Policy Research Working Paper
okr.docurlhttp://documents.worldbank.org/curated/undefined/235241638281693198/Estimating-the-Impact-of-Weather-on-Agriculture
okr.guid235241638281693198
okr.identifier.doi10.1596/1813-9450-9867
okr.identifier.externaldocumentum090224b088bd3b6e_1_0
okr.identifier.internaldocumentum33650496
okr.identifier.reportWPS9867
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/235241638281693198/pdf/Estimating-the-Impact-of-Weather-on-Agriculture.pdfen
okr.region.administrativeAfrica
okr.region.geographicalSub-Saharan Africa
okr.topicAgriculture::Climate Change and Agriculture
okr.topicAgriculture::Crops & Crop Management Systems
okr.topicEnvironment::Climate Change Impacts
okr.topicScience and Technology Development::Climate and Meteorology
okr.topicAgriculture::Agricultural Sector Economics
okr.unitDevelopment Data Group, Development Economics
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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