2014
DOI: 10.4314/star.v3i3.33
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Analysis of Technical Efficiency of Small Holder Maize Growing Farmers of Horo Guduru Wollega Zone, Ethiopia: A Stochastic Frontier Approach

Abstract: Article InformationThe objective of this study was to examine the level of technical efficiency of smallholder maize producers and identify its determinants in Horo Guduru Wollega zone of Oromia Regional State, Ethiopia. A Cobb-Douglass stochastic production function model was used for the analysis. To specify technical inefficiency effects of socioeconomic variables, Maximum Likelihood Estimation (MLE) technique using data collected from 120 randomly selected sample farmers in 2011 was applied. The MLE result… Show more

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Cited by 23 publications
(21 citation statements)
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“…Off/non-farm incomes enable them to purchase or hire productive inputs. This result is consistent with the study by Hailemaraim (2015), Kitila and Alemu (2014) and it is in contrast with the study by Hailsellasie (2005). Coefficient of distance to nearest market was positively related with technical efficiency and statistically significant at 5% percent level of significance which is not priori expectation.…”
Section: Determinants Of Technical Inefficiencysupporting
confidence: 92%
“…Off/non-farm incomes enable them to purchase or hire productive inputs. This result is consistent with the study by Hailemaraim (2015), Kitila and Alemu (2014) and it is in contrast with the study by Hailsellasie (2005). Coefficient of distance to nearest market was positively related with technical efficiency and statistically significant at 5% percent level of significance which is not priori expectation.…”
Section: Determinants Of Technical Inefficiencysupporting
confidence: 92%
“…Off/non-farm incomes enable them to purchase or hire productive inputs. This result is consistent with the study by Hailemaraim [19] and Kitila [23] and it is in contrast with the study by Hailsellasie [22].…”
Section: Determinants Of Technical Inefficiencysupporting
confidence: 92%
“…This implies that increasing labour by 1% will increase output by about 0.526 % ceteris paribus. The findings correspond to those obtained by [10] and [16] but are not in accordance with findings of [17] and [18] The estimate for seed (0.243) is positive and significant at 5%. The significance of seed quantity is due to the fact that seed determines to a large extent the output obtained.…”
Section: Maximum Likelihood Estimates (Mle) Of the Parameters Of The supporting
confidence: 49%