SMALLHOLDER DAIRYING IN KENYA: THE ASSESSMENT OF THE TECHNICAL EFFICIENCY USING THE STOCHASTIC PRODUCTION FRONTIER MODEL

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dc.contributor.author Majiwa, E. B.
dc.contributor.author Kavoi, M. M.
dc.contributor.author Murage, H.
dc.date.accessioned 2017-01-18T06:59:45Z
dc.date.available 2017-01-18T06:59:45Z
dc.date.issued 2017-01-18
dc.identifier.issn 1561-7645
dc.identifier.uri http://journals.jkuat.ac.ke/index.php/jagst/index
dc.identifier.uri http://hdl.handle.net/123456789/2500
dc.description.abstract Dairying in Kenya remains a multi-purpose cattle system providing milk, manure and capital assets to the farmer. Dairy activities in Kenya are predominantly run by smallholders and are concentrated in the high and medium potential areas. Smallholders operating 1-3 dairy cows on small farms are predominant in Kenya. They produce 56% of the total milk in the country and supply 80% of Kenya’s marketed milk. Estimated growth in the consumption of milk and dairy products in developing countries is 3.3%, which is in line with Kenya’s 3% per year. National statistics show that milk production continues to decline. For example, since 2000 milk annual growth rate has been 1.4% compared to 9.2% experienced between 1980 and 1990. The main challenge of Kenya’s dairy industry is how to confront growing milk demand and a highly competitive export environment when yields are as low as 195 litres per lactation. One of the key options is to develop a vibrant competitive dairy sector in Kenya by increasing the efficiency of production. Thus, this study examined the technical efficiency of smallholder dairy farms of rural Kenya. Data from a 2005 survey of smallholder farms in five provinces was utilized to examine the technical efficiency of smallholder farms. The Cobb-Douglas stochastic production frontier model was used to identify the determinants of technical inefficiency. The findings revealed that the mean efficiency was 79 percent, which suggested that 21 percent of production was lost due to technical inefficiency. The technical efficiency also varied across regions ranging from a mean of 83.9% in Central region and 72.5% in Nyanza region. Land size, access to extension service, infrastructure and the level of schooling were found to reduce inefficiency. en_US
dc.language.iso en en_US
dc.publisher Journal of Agricultural Science and Technology, JKUAT en_US
dc.relation.ispartofseries Journal of Agricultural Science and Technology(JAGST);
dc.subject Smallholder dairy en_US
dc.subject technical efficiency en_US
dc.subject stochastic production frontier en_US
dc.title SMALLHOLDER DAIRYING IN KENYA: THE ASSESSMENT OF THE TECHNICAL EFFICIENCY USING THE STOCHASTIC PRODUCTION FRONTIER MODEL en_US
dc.type Article en_US


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