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dc.contributor.authorMuguna, Benson K
dc.date.accessioned2015-12-11T09:21:00Z
dc.date.available2015-12-11T09:21:00Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/11295/93412
dc.description.abstractThe agricultural sector contributes greatly to the economic growth of Kenya. The sector employs more than half of national workforce and above 80% of citizens depends on agriculture as a source of livelihood. The challenge of land expansion to achieve high agricultural productivity and food security has resulted to agricultural land-use intensification as the major solution. In order to achieve intensification of agricultural land-use, human capital development is imperative. To motivate public and private investment in HCD, there is need to evaluation the contribution of HCD on the agricultural land-use intensification. This study employs a modified Cobb-Douglas production function to estimate the contribution of HCD on the TFP of the agricultural sector. Agricultural land-use intensification is a TFP measure, which estimates the share of non conventional inputs on the agricultural output. The explanatory variable explained 55.4% of the depend variable of the study. Only 44.6% of agricultural TFPg was not explained by the regressed model. The included HCD indicators were significant to the model, demonstrated by their respective Fstatistics which were less than the critical value of 0.05 in 5% level of significance. Education with a coefficient of 3.882754 considerably contributed to the agricultural land-use intensification compared to other HCD indicator variables of ill-health and income. Land is also critical in the growth of TFP. According to the findings of this study, investment in education, health and better market conditions is necessary to achieve desired level of agricultural land-use intensification.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.titleThe Contribution of Human Capital Development on Agricultural Land-use Intensification: Analysis Using Mwea Irrigation Scheme Dataen_US
dc.typeThesisen_US


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