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dc.contributor.authorMumo, Elijah M
dc.date.accessioned2022-05-13T06:23:04Z
dc.date.available2022-05-13T06:23:04Z
dc.date.issued2021
dc.identifier.urihttp://erepository.uonbi.ac.ke/handle/11295/160605
dc.description.abstractAdverse climate change threatens livelihood security of rural households that depend mainly on on-farm income sources as it leads to depressed yields from both crop and livestock production. Climate smart agriculture innovations offer an avenue for farmers to concurrently build resilience to climate change and increase agricultural productivity. This study focused on risk attitudes and adoption of climate smart agricultural technologies among smallholder farmers in the Nyando basin in South-Western Kenya. . The specific objectives of the study were to assess Nyando basin farmers risk attitudes; determine the factors influencing livelihood diversification among Nyando households; and finally determine how Nyando basin farmers’ risk attitudes and livelihood diversification influence their adoption of climate smart agricultural technologies. The study hypotheses were that Nyando smallholder farmers do not have a risk averse attitude; household head, household socioeconomic characteristics and institutional factors do not significantly influence Nyando households livelihood diversification; Nyando basin farmers risk attitudes and household livelihood diversification do not significantly influence the adoption of CSA technologies. The study utilized primary data collected from 122 randomly selected farm households in the contiguous Nyando basin stretching between Kisumu and Kericho counties. Farmers risk attitudes were elicited through a hypothetical risk experiment and the results of the experiment showed that Nyando basin farmers were moderately risk averse. The factors that influence Nyando households’ livelihood diversification were modeled through a binary logit model. The results showed that the age of the household head, farmer training and social capital had a significant negative influence on livelihood diversification, household head education and the effect of floods significantly favored livelihood diversification. The study analyzed the effect of farmers’ risk attitudes and household livelihood diversification on adoption of climate smart agricultural technologies through the multivariate probit and ordered probit models. Farmers’ risk attitudes and livelihood diversification had a significant influence on probability of households adopting climate smart agricultural technologies. Other variables which had a significant influence on the decision of households to adopt climate smart agricultural technologies were gender of household head, wealth status of a household, distance to local markets, access to loans, farmer training, location and climate risks. The study recommends farmer training and farmer loan access to promote adoption of appropriate climate smart agricultural technologies. Targeted farmer training will help to promote livelihood diversification among Nyando basin rural households. Considering that farmers’ risk attitudes significantly influence adoption of climate smart technologies, relevant stakeholders should work on providing appropriate insurance covers to encourage a greater adoption of agricultural technologies. Future research can incorporate plot analysis in analyzing the factors that influence the adoption of climate smart agricultural technologies in the Nyando basin region.en_US
dc.language.isoenen_US
dc.publisherUONen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectClimate smart agricultural technologies, multivariate and ordered probit modelsen_US
dc.titleRisk Attitudes and Adoption of Climate Smart Agricultural Technologies Among Smallholder Farmers in the Nyando Basin in South-western Kenyaen_US
dc.typeThesisen_US


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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States