Browsing by Author "Kefa C"

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    Assessment of Farmers’ Adaptation to the Effects of Climate Change in Kenya: the Case of Kyuso District
    (Journal of Economics and Sustainable Development, 2024-01-12) Ndambiri H. K.; Ritho C.; Mbogoh S.G; Ng’ang’a S. I; Muiruri E. J; Nyangweso P.M; Kipsat M. J; Ogada J. O; Omboto P. I; Kefa C; Kubowon, P. C; Cherotwo F. H
    The study was carried out to assess how farmers in Kyuso District have adapted to the effects of climate change. Survey data was collected from 246 farmers from six locations that were sampled out through a multistage and simple random sampling procedure. The probit regression model was fitted into the data in order to assess factors influencing farmers’ adaptation to the effects of climate change. The analysis revealed that 85% of the farmers had adapted in various ways to the effects of climate change. In this regard, the age of the farmer, gender, education, farming experience, farm income, access to climate information, household size, local agro-ecology, distance to input/output market, access to credit, access to water for irrigation, precipitation and temperature were found to have significant influence on the probability of farmers to adapt to climate change. The study suggests that more policy efforts should thus be geared towards helping all the farmers in the district to adapt to climate change.
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    Socio-Economic and Institutional Constraints to Accessing Credit among Smallholder Farmers in Nyandarua District, Kenya
    (European Journal of Business and Management, 2024-07-12) Muiruri, E. J.; Nyangweso, P. M; Kipsat, M. J.; Ndambiri, H. K; Ritho C; Ng’ang’a; Kefa C; Ogada J. O; Omboto P. I.; Kubowon, P. C; Cherotwo F. H
    Amongst the challenges faced by smallholder farmers in production is inaccessibility to credit. This study sought to identify household socio-economic and institutional constraints influencing access to credit among smallholder farmers in Nyandarua District. The study used a Logit model. Both quantitative and qualitative data were acquired from primary and secondary sources. Primary data was collected using questionnaires through a survey design. A sample of 164 smallholder farmers was selected using stratified, multi-stage random sampling techniques. Data was analyzed using descriptive statistics and maximum likelihood method using Statistical Package for Social Sciences (SPSS). The study established that socio-economic constraints such as age, gender, household size, farm income, collateral and awareness are critical determinants of access to credit. The study also established that institutional requirements such as costs involved in operating / maintaining bank accounts, loan requirements and transaction costs involved in the credit process influenced access to credit. The study concludes that household socio-economic characteristics and institutional requirements influence access to credit. Key recommendations made include the need by government to deal with bureaucracies involved in land registration to benefit majority of smallholder farmers who remain insecure in the land they use without proof of ownership and also to make easier the registration of lease certificates for those who do not own land and use land on leasehold tenure system. Financial institutions should also put in place less stringent credit requirements and reduce credit costs especially interest rates to make credit more affordable.