Studying inclusive innovation with the right data: An empirical illustration from Ethiopia

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cg.authorship.typesCGIAR and advanced research instituteen_US
cg.contributor.affiliationCGIAR Standing Panel on Impact Assessmenten_US
cg.contributor.affiliationInternational Food Policy Research Instituteen_US
cg.contributor.affiliationParis School of Economicsen_US
cg.contributor.affiliationInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Franceen_US
cg.contributor.affiliationInternational Livestock Research Instituteen_US
cg.contributor.donorCGIAR Trust Funden_US
cg.coverage.countryEthiopiaen_US
cg.coverage.iso3166-alpha2ETen_US
cg.coverage.regionAfricaen_US
cg.coverage.regionEastern Africaen_US
cg.howPublishedFormally Publisheden_US
cg.identifier.doihttps://doi.org/10.1016/j.agsy.2024.103988en_US
cg.identifier.projectIFPRI - Innovation Policy and Scaling Uniten_US
cg.identifier.publicationRankAen_US
cg.isijournalISI Journalen_US
cg.issn0308-521Xen_US
cg.issueAugust 2024en_US
cg.journalAgricultural Systemsen_US
cg.reviewStatusPeer Reviewen_US
cg.volume219en_US
dc.contributor.authorAlemu, Solomonen_US
dc.contributor.authorKosmowski, Fredericen_US
dc.contributor.authorStevenson, James R.en_US
dc.contributor.authorMallia, Paolaen_US
dc.contributor.authorTaye, Lemien_US
dc.contributor.authorMacours, Karenen_US
dc.date.accessioned2024-06-07T14:41:45Zen_US
dc.date.available2024-06-07T14:41:45Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/145067en_US
dc.titleStudying inclusive innovation with the right data: An empirical illustration from Ethiopiaen_US
dcterms.abstractCONTEXT Agricultural innovations are inclusive when they are used by any member of society who wants to use them. Conversely, agricultural innovations that can only be used by a specific privileged group within society can be characterized as “exclusive”. OBJECTIVE The first objective of this paper is to examine the inclusivity of agricultural innovations in Ethiopia, using national representative data and considering a wide portfolio of innovations resulting from the collaborative research between CGIAR and its national partners. Second, we also examine how measurement error may affect how we characterize the inclusivity of agricultural innovations. METHODS We use nationally-representative survey data from Ethiopia (collected in 2018/19) in which best-practice measures of the adoption of a large number of agricultural innovations were embedded, including the adoption of CGIAR-related improved maize varieties measured using two different approaches: subjective, self-reported survey data; and objective DNA fingerprinting of crop samples taken from the same farmers' plots. A rich set of household variables is also collected in the survey, which allows characterizing the types of farmers that are adopting different innovations, and the extent to which conclusions regarding the inclusivity of innovations depends on the measurement of the latter. RESULTS AND CONCLUSIONS Many innovations are not disproportionately more likely to be adopted by male, larger, richer, or more connected farmers. When using self-reported data on adoption of improved maize varieties, adoption appears positively correlated with having larger landholdings and households with lower female participation in agriculture, and negatively correlated with poorer households (being among the bottom 40% of consumption distribution). Substituting survey responses with the results of DNA fingerprinting these correlations disappear, with farm size, gender and poverty status no longer predictive of adoption. SIGNIFICANCE The results suggest the potential value of offering a menu of innovations to farmers to increase inclusivity, as it allows each farmer to be a critical consumer of potential innovations and select those that best correspond to their own needs and constraints. We also highlight how important data quality is in ensuring we have correct information about inclusive innovation.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceScientistsen_US
dcterms.available2024-06-01en_US
dcterms.bibliographicCitationAlemu, Solomon; Kosmowski, Frederic; Stevenson, James R.; Mallia, Paola; Taye, Lemi; and Macours, Karen. 2024. Studying inclusive innovation with the right data: An empirical illustration from Ethiopia. Agricultural Systems 219(August 2024): 103988. https://doi.org/10.1016/j.agsy.2024.103988en_US
dcterms.extent103988en_US
dcterms.issued2024-08en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherElsevieren_US
dcterms.subjectagricultureen_US
dcterms.subjectinnovationen_US
dcterms.subjectdataen_US
dcterms.subjectfarmersen_US
dcterms.typeJournal Articleen_US

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