Working Paper

Estimating the Impact of Weather on Agriculture

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collection.link.5
https://openknowledge.worldbank.org/handle/10986/9
collection.name.5
Policy Research Working Papers
dc.contributor.author
Michler, Jeffrey D.
dc.contributor.author
Josephson, Anna
dc.contributor.author
Kilic, Talip
dc.contributor.author
Murray, Siobhan
dc.date.accessioned
2021-12-03T14:44:35Z
dc.date.available
2021-12-03T14:44:35Z
dc.date.issued
2021-11
dc.date.lastModified
2021-12-04T05:10:42Z
dc.description.abstract
This 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.identifier
http://documents.worldbank.org/curated/undefined/235241638281693198/Estimating-the-Impact-of-Weather-on-Agriculture
dc.identifier.uri
http://hdl.handle.net/10986/36643
dc.language
English
dc.publisher
World Bank, Washington, DC
dc.relation.ispartofseries
Policy Research Working Paper;No. 9867
dc.rights
CC BY 3.0 IGO
dc.rights.holder
World Bank
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/igo
dc.subject
REMOTE SENSING
dc.subject
AGRICULTURAL PRODUCTIVITY
dc.subject
CROP YIELD
dc.subject
WEATHER IMPACTS
dc.subject
PRECIPITATION
dc.subject
TEMPERATURE
dc.title
Estimating the Impact of Weather on Agriculture
en
dc.type
Working Paper
en
okr.date.disclosure
2021-11-30
okr.date.lastmodified
2021-11-30T00:00:00Z
en
okr.doctype
Publications & Research
okr.doctype
Publications & Research :: Policy Research Working Paper
okr.docurl
http://documents.worldbank.org/curated/undefined/235241638281693198/Estimating-the-Impact-of-Weather-on-Agriculture
okr.googlescholar.linkpresent
yes
okr.guid
235241638281693198
okr.identifier.doi
10.1596/1813-9450-9867
okr.identifier.externaldocumentum
090224b088bd3b6e_1_0
okr.identifier.internaldocumentum
33650496
okr.identifier.report
WPS9867
okr.imported
true
en
okr.language.supported
en
okr.pdfurl
http://documents.worldbank.org/curated/en/235241638281693198/pdf/Estimating-the-Impact-of-Weather-on-Agriculture.pdf
en
okr.region.administrative
Africa
okr.region.geographical
Sub-Saharan Africa
okr.topic
Agriculture :: Climate Change and Agriculture
okr.topic
Agriculture :: Crops & Crop Management Systems
okr.topic
Environment :: Climate Change Impacts
okr.topic
Science and Technology Development :: Climate and Meteorology
okr.topic
Agriculture :: Agricultural Sector Economics
okr.unit
Development Data Group, Development Economics

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