Technical Efficiency of Plantain Production in Ekiti Southwest Local Government Area of Ekiti State, Nigeria
DOI:
https://doi.org/10.24297/jaa.v8i1.7142Keywords:
technical efficiency, budgetary analysis,, Plantain productionAbstract
This study examined the technical efficiency of plantain production in Ekiti Southwest Local Government Area (LGA) of Ekiti State, Nigeria. The study used multistage sampling techniques for data collection. Data were collected from 90 plantain farmers through well-structured questionnaires from the LGA with three towns purposively selected. The collected data were analyzed using descriptive statistics, budgetary analysis and stochastic frontier production model. Results from descriptive analysis showed that 48.88 percent of the plantain farmers had secondary education and above. Majority of the respondents (66.67 percent) had between 5 and 8 members that made up the household in the study area. Findings further showed that majority of the respondents produced on small scale with average plantain farm size of 0.96 hectares. The farmers were fairly experienced with 44.44 percent of them had more than 15 years of farming experience. With mean profit of ₦251,500 per hectare and percentage profit of 63.11 percent, the venture was considered to be highly profitable. Farmers who invested ₦1 realized revenue of ₦0.63. The RTS parameter (0.931) was obtained from the summation of the coefficients of the estimated inputs (elasticities) which indicated that plantain production in the study area was in Stage II of the production surface meaning that these variables were efficiently utilized. Depreciation, hired labour, family labour, farm size and quantity of suckers planted were the significant variables that influence efficiency of the plantain farmers. Age, land acquisition and access to credit contributed significantly to technical inefficiency. Among the most prevalent constraints were; price fluctuation (72.22%), heavy wind (70.00%), high cost of farm input (68.89%), pests and diseases and pilferage (63.33%) each, insufficient credit facility, storage facility and poor agricultural extension services (62.22%) respectively.
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