Towards a core approach for cross-sectional farm household survey data collection: a tiered setup for quantifying key farm and livelihood indicators

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cg.authorship.typesCGIAR single centreen
cg.contributor.affiliationInternational Center for Tropical Agricultureen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.contributor.affiliationInternational Crops Research Institute for the Semi-Arid Tropicsen
cg.contributor.affiliationBioversity Internationalen
cg.contributor.affiliationInternational Food Policy Research Instituteen
cg.contributor.affiliationInternational Maize and Wheat Improvement Centeren
cg.contributor.crpBig Data
cg.contributor.donorInternational Crops Research Institute for the Semi-Arid Tropicsen
cg.contributor.donorUniversity of Naplesen
cg.contributor.donorRoyal Institute of the Tropicsen
cg.contributor.donorWageningen University & Researchen
cg.contributor.donorInternational Livestock Research Instituteen
cg.contributor.donorInternational Fund for Agricultural Developmenten
cg.contributor.donorWorldFishen
cg.contributor.donorInternational Rice Research Instituteen
cg.contributor.donorBioversity Internationalen
cg.contributor.donorInternational Center for Tropical Agricultureen
cg.contributor.donorUniversity of Washingtonen
cg.creator.identifierMark van Wijk: 0000-0003-0728-8839
cg.creator.identifierDharani Dhar Burra: 0000-0002-2638-3420
cg.creator.identifierKelvin Mashisia Shikuku: 0000-0003-2290-074X
cg.creator.identifierElizabeth Arnaud: 0000-0002-6020-5919
cg.creator.identifierFrancesco Caracciolo: 0000-0001-9430-7529
cg.creator.identifierCarlo Azzarri: 0000-0002-0345-1304
cg.creator.identifierJessica Heckert: 0000-0002-3022-8298
cg.creator.identifierSoonho Kim: 0000-0002-9417-1040
cg.identifier.projectIFPRI - Markets, Trade, and Institutions Division
cg.identifier.projectIFPRI - Environment and Production Technology Division
cg.identifier.projectIFPRI - Poverty, Health, and Nutrition Division
cg.identifier.publicationRankNot ranked
cg.reviewStatusInternal Reviewen
dc.contributor.authorWijk, Mark T. vanen
dc.contributor.authorÁlvarez, Cristinaen
dc.contributor.authorAnupama, Guvvalaen
dc.contributor.authorArnaud, Elizabethen
dc.contributor.authorAzzarri, Carloen
dc.contributor.authorBurra, Dharani Dharen
dc.contributor.authorCaracciolo, Francescoen
dc.contributor.authorCoomes, David A.en
dc.contributor.authorGarbero, Alessandraen
dc.contributor.authorGotor, Elisabettaen
dc.contributor.authorHeckert, Jessicaen
dc.contributor.authorJohnson, Nancy L.en
dc.contributor.authorKim, Soonhoen
dc.contributor.authorMiro, Bertaen
dc.contributor.authorMuliro, Jacquelineen
dc.contributor.authorShikuku, Kelvin Mashisiaen
dc.contributor.authorTyszler, Marceloen
dc.contributor.authorValdivia, Roberto O.en
dc.contributor.authorViviani, Saraen
dc.contributor.authorVrolijk, Hansen
dc.contributor.authorKruseman, Gideon K.en
dc.date.accessioned2019-11-12T16:35:49Zen
dc.date.available2019-11-12T16:35:49Zen
dc.identifier.urihttps://hdl.handle.net/10568/105714
dc.titleTowards a core approach for cross-sectional farm household survey data collection: a tiered setup for quantifying key farm and livelihood indicatorsen
dcterms.abstractThere is an urgent need to improve the characterisation of agricultural systems at household level to enable a more efficient assessment of the capacity households to adopt a range of agricultural intervention options. Local drivers and factors need to be identified that might constrain or provide opportunities within a specified agricultural system (Carletto et al., 2015), while on the other hand generalisable standardized characteristics need to be identified that would allow robust comparisons between different systems (Frelat et al., 2016; van Wijk et al., 2014). The assessment of opportunities at smallholder farm household level to improve their livelihoods needs integration of validated standardised agricultural, poverty, nutrition and gender indicators in the quantitative characterisation of these households. This will allow us to assess how these welfare indicators vary across a farm household population and across different agro-ecological and socioeconomic conditions. Such data would also allow us to better assess how they may change over time. Furthering such a standardization across all institutes within the CGIAR (who have been estimated to conduct baseline interviews with around 180,000 farmers per year) would allow for much easier application of big data method applications for analyzing the household level data themselves, as well as for linking these data to other larger scale information sources like spatial crop yield data, climate data, market access data, roadmap data, etc. The Big Data platform of the CGIAR has therefore stimulated an effort to define how a common core of a cross-sectional household survey focusing on rural households could look like, the so-called 100Q exercise (with 100Q standing for 100 Questions that that core should contain). The core survey should deliver key information around the agricultural activities and off farm income of the household, as well as key welfare indicators focusing on poverty, food security, dietary diversity and gender equity. Within this effort a workshop was held in Rome, Italy, in December 2018, where a group of scientists from different centers of the CGIAR and partner institutions discussed how such a core approach for cross-sectional surveys could look, and what type of information should be captured. This report is a short reflection of what was discussed during this workshop, and tries to summarize the overall conclusions of this workshop into core modules of key aspects and indicators of rural farm livelihoods. This information can be used as building blocks for survey development, thereby resulting in more harmonized household survey data collection across CGIAR centers.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationvan Wijk, Mark; Alvarez, Cristina; Anupama, Guvvala; Arnaud, Elizabeth; Azzarri, Carlo; Burra, Dharani; Caracciolo, Francesco; Coomes, David; Garbero, Alessandra; Gotor, Elisabetta; Heckert, Jessica; Johnson, Nancy; Kim, Soonho; Miro, Berta; Muliro, Jacqueline; Shikuku, Kelvin; Tyszler, Marcelo; Valdivia, Roberto; Viviani, Sara; Vrolijk, Hans & Kruseman, Gideon (2019). Towards a core approach for cross-sectional farm household survey data collection: a tiered setup for quantifying key farm and livelihood indicators. Community of Practice on Socio-economic Data report COPSED-2019-001. CGIAR Platform for Big Data in Agriculture. 32 p.en
dcterms.extent32 p.en
dcterms.issued2019
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherCGIAR Platform for Big Data in Agricultureen
dcterms.relationhttps://doi.org/10.1016/j.patter.2020.100105en
dcterms.replaceshttps://ebrary.ifpri.org/digital/collection/p15738coll5/id/6992en
dcterms.subjectsocio-economic dataen
dcterms.subjectindicatorsen
dcterms.subjectbig dataen
dcterms.subjectlivelihoodsen
dcterms.subjectsurveysen
dcterms.subjectgenderen
dcterms.subjectfood securityen
dcterms.subjectdietary diversityen
dcterms.subjecthouseholden
dcterms.subjectdataen
dcterms.subjectfarmsen
dcterms.subjectdieten
dcterms.typeReport

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