Abstract:

Information on efficiency in sunflower production is generally lacking and this in turn
industry. This study
and planners make informed policy on how to increase sunflower productivity with the
existing resources and available technologies. The general objective was to assess the
possibilities for productivity gains that can be made from the current resources by
sunflower farmers in Lango in view of guiding policy makers. The specific objectives
were to; estimate farm-level technical efficiency of sunflower in Lango Sub-region. And
identify factors which influence technical efficiency among sunflower farmers.
Using cross-sectional data from 196 households from four districts of Lango Sub-region,
data was collected to measure farm level technical efficiency in sunflower production.
The study employed stochastic frontier approach where the results of C-D functional
form showed that coefficient of inputs had positive value of 1.1136 indicating increasing
indicates that education of household head, contract farming and access to credit had
significant influence on technical inefficiency.
The study therefore calls for attention of the policy-makers and the planners to give top
enhance agricultural productivity. Such policies inclusion promoting operation of big
contract producers. Perhaps the government could also
vi
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was therefore motivated by the desire to ensure that policy makers
case of coffee and cotton development
returns to scale. The observed technical efficiency ranged from 16.76% to 96.20% with a
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private companies which can
mean of 81.2%, indicating a wide variation among the different farmers. Further inquiry
priority to strengthening of rural and agricultural supporting institutions in order to
has severely limited the ability to devise promising policy initiatives in sunflower
long way in addressing their resource use constraints thus improving efficiency
subsidies could help them to improve efficiency. Such policies could go hand in hand
with strengthening government extension link in sunflower currently is lacking.
The study also recommends the need for further research to look into allocative
efficiency. Additional study can be conducted by employing stochastic cost function
model to explore input-cost minimization or data envelop analysis. Additional study can
be done that look at oxen as one of the main input variables.