Browsing by Author "Kipsat M. J"

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    Analysis of Farmers’ Perceptions of the Effects of Climate Change in Kenya
    (AgEcon Search, 2024-02-19) Ndambiri H. K; Ritho C; Mbogoh S.G; Nyangweso P.M; Ng’ang’a S. I.; Muiruri E. J; Kipsat M. J; Kubowon; Cherotwo F. H; Omboto P. I
    A cross-sectional analysis was carried out to evaluate how farmers in Kyuso District have perceived climate change. Data was collected from 246 farmers from six locations sampled out through a multistage and simple random sampling procedure. The logistic regression analysis was carried out to assess factors influencing farmers’ perceptions of climate change. The analysis revealed that 94% of farmers in Kyuso District had a perception that climate was changing. In this regard, age of the household head, gender, education, farming experience, household size, distance to the nearest input/output market, access to irrigation water, local agro-ecology, access to information on climate change, access to extension services, off farm income and change in temperature and precipitation were found to have significant influence on the probability of farmers to perceive climate change. Since the level of perception to climate change revealed by the study was found to be high (94%), the study suggests that more policy efforts should thus be geared towards helping farmers to adapt to climate change.
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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.