ANALYSIS OF GENDER DIMENSION IN ADOPTION OF CLIMATE SMART AGRICULTURE PRACTICES IN EFRATANA GIDIM DISTRICT, NORTH SHEWA ZONE, ETHIOPIA

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dc.contributor.author Shumye, Ayahlush
dc.contributor.author Seyoum, Chanyalew (PhD)
dc.contributor.author Kifle, Dereje (Assistant Professor)
dc.date.accessioned 2018-01-28T21:04:07Z
dc.date.available 2018-01-28T21:04:07Z
dc.date.issued 2020-02
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/266
dc.description 98p. en_US
dc.description.abstract Climate change is adversely affecting agricultural production in Africa. Across societies, the impacts of climate change affect males and females differently. To overcome these impacts, it is crucial to adopt climate smart agriculture practices. Male and female farmers in developing countries have different vulnerabilities and capacities to deal with the impact of climate change. Accordingly, socio-economic and gender analysis is an important step for gender-appropriate targeting of CSA practices. This study, therefore, examined how males and females within the same household adopt CSA practices in Efratana Gidim District, North Shewa Zone, Amhara Regional State, Ethiopia using cross-sectional data collected in 2019. In this study, a total of 97 pairs of couples involved, making 194 respondents in total. They were selected randomly from four sample kebeles using a multi-stage random sampling technique. Hence, structured interview schedule, focus group discussions and key informant interviews were used to collect primary data. Secondary data relevant to the study were collected to enrich the findings. Descriptive and inferential statistics, as well as econometric models, were used to analyze the quantitative data while the qualitative data was narrated. The result shows that of the total sample respondents, 35.05% of female and 42.27% of male farmers were found to be the user of different CSA practices, while 14.95% of female and 7.73% of male respondents were found to be nonuser. Thus there were significant gender differences in adoption of CSA practices. The multinomial logit (MNL) model result showed that from a total of 15 explanatory variables nine (9) of them significantly influenced the adoption of CSA practices (P ≤ 10%). Likewise, age, education, gender (being male), agro-ecological zones, family size, farm income, frequency of extension contacts and membership in a local institution were influenced positively and significantly, while the distance from the nearest market influenced negatively and significantly. Lack of technical skill to practice, high input price, a blind recommendation of practices, lack of own land, lack of road for transportation, lack of market information and lack of input access were the main challenges of farmers to adopt CSA practices in the study area. Besides, credit access to purchase input for the practices, the intervention of NGOs (Agricultural Growth Program), and local cooperative to get input credit, training and demonstration were some opportunities that appreciate farmers adopt CSA practices. This study concludes that adoption of CSA practices was better to be gender inclusive and more female farmers' contributions were unrecognized in agriculture and they have core activities for rural households as a means of improving livelihood and to cope with the negative impacts of climate change. Thus, the Woreda administration and agricultural office in rural development strategy should give emphasis on the promotion of gender-inclusive village wise education and training in addition to formal education, provide area suitable CSA practices and empowering female farmers to encourage their participation in adoption of CSA practices en_US
dc.description.sponsorship Haramaya university en_US
dc.language.iso en en_US
dc.publisher haramaya university en_US
dc.subject Efratana Gidim, CSA practices, adoption, multinomial logit (MNL), challenges, opportunity en_US
dc.title ANALYSIS OF GENDER DIMENSION IN ADOPTION OF CLIMATE SMART AGRICULTURE PRACTICES IN EFRATANA GIDIM DISTRICT, NORTH SHEWA ZONE, ETHIOPIA en_US
dc.type Thesis en_US


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