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Gender differences in technology adoption and agricultural productivity: evidence from Malawi

dc.contributor.authorHirpa Tufa, A.
dc.contributor.authorAlene, A.
dc.contributor.authorCole, S.M.
dc.contributor.authorManda, J.
dc.contributor.authorFeleke, S.
dc.contributor.authorAbdoulaye, T.
dc.contributor.authorChikoye, D.
dc.contributor.authorManyong, V.
dc.date.accessioned2022-08-10T10:17:04Z
dc.date.available2022-08-10T10:17:04Z
dc.date.issued2022-11
dc.identifier.citationHirpa Tufa, A., Alene, A., Cole, S.M., Manda, J., Feleke, S., Abdoulaye, T., ... & Manyong, V. (2022). Gender differences in technology adoption and agricultural productivity: evidence from Malawi. World Development, 159: 106027, 1-15.
dc.identifier.issn0305-750X
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7627
dc.description.abstractIt is widely recognized that female farmers have considerably less access to productive assets and support services than male farmers. There is limited evidence of gender gaps in technology adoption and agricultural productivity after accounting for the differential access to factors of production between males and females. This study investigates the gender differences in the adoption of improved technologies and agricultural productivity in Malawi using nationally representative data collected from 1600 households and 5238 plots. We used a multivariate probit model to analyze the gender differences in the adoption of improved technologies, including intercropping, use of improved varieties, crop rotation and residue retention, manure use, and minimum tillage. To analyze gender differences in agricultural productivity, we used an exogenous switching regression (ESR) model and recentered influence function decomposition. We found that female plot managers were more likely to adopt intercropping and minimum tillage but less likely to adopt crop rotation and use improved varieties than male plot managers. The ESR model estimation results showed that female-managed plots were 14.6–23.1% less productive than male-managed plots. The gender productivity gaps also indicated that female plot managers had an 8.2% endowment advantage but a 23.1% structural disadvantage than male plot managers. The importance of structural effects in accounting for the gender productivity gap highlights the need for policies and agricultural development programs that consider the underlying factors shaping gender productivity gaps rather than focusing solely on agricultural production factors.
dc.description.sponsorshipUnited States Agency for International Development
dc.description.sponsorshipInternational Institute of Tropical Agriculture
dc.format.extent1-15
dc.language.isoen
dc.subjectGender
dc.subjectProductivity
dc.subjectTechnology Transfer
dc.subjectAdoption
dc.subjectMalawi
dc.titleGender differences in technology adoption and agricultural productivity: evidence from Malawi
dc.typeJournal Article
cg.contributor.crpAgriculture for Nutrition and Health
cg.contributor.crpMaize
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.crpPolicies, Institutions and Markets
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionSouthern Africa
cg.coverage.countryMalawi
cg.coverage.hubSouthern Africa Hub
cg.coverage.hubEastern Africa Hub
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemePlant Production and Health
cg.researchthemeSocial Science and Agribusiness
cg.identifier.bibtexciteidHIRPATUFA:2022
cg.isijournalISI Journal
cg.authorship.typesCGIAR Single Centre
cg.iitasubjectAgronomy
cg.iitasubjectFood Security
cg.iitasubjectGender
cg.iitasubjectPlant Production
cg.iitasubjectSmallholder Farmers
cg.journalWorld Development
cg.notesOpen Access Article; Published online: 21 Jul 2022
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1016/j.worlddev.2022.106027
cg.iitaauthor.identifierAdane Tufa: 0000-0001-9801-6526
cg.iitaauthor.identifierArega Alene: 0000-0002-2491-4603
cg.iitaauthor.identifierJulius Manda: 0000-0002-9599-5906
cg.iitaauthor.identifierShiferaw Feleke: 0000-0002-0759-4070
cg.iitaauthor.identifierTahirou Abdoulaye: 0000-0002-8072-1363
cg.iitaauthor.identifierDavid Chikoye: 0000-0002-6047-9821
cg.iitaauthor.identifierVictor Manyong: 0000-0003-2477-7132
cg.futureupdate.requiredNo
cg.identifier.issue106027
cg.identifier.volume159


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