Technical efficiency of cassava farmers in Ekiti State, Nigeria
Department of Agricultural Economics and Extension Services, Ekiti State University, Ado Ekiti, Nigeria.
Research Article
World Journal of Advanced Research and Reviews, 2023, 18(02), 919-926
Publication history:
Received on 05 April 2023; revised on 12 May 2023; accepted on 15 May 2023
Abstract:
This study measured the technical efficiency of cassava farmers in Ekiti State, Nigeria. A multi-stage sampling technique was employed to select 120 respondents for the study. Primary data were collected from the randomly selected respondents through a well-structured and self-administered questionnaire. The results of the study indicated that more than half (52.5%) of the cassava farmers were older than 50 years of age and had household sizes within the range of 6-10 persons. About 51.6 percent of the respondents had more than a primary school education. No difference existed between those with tertiary education and those without formal education regarding the cultivated farm size (4.00 ha). Combined labour (family and hired labour) was prevalent among the farmers, as submitted by 65.8 percent of the cassava farmers. Results from the Stochastic Frontier Production Function (SFPF) model indicated that herbicide and pesticide, depreciation value of tools, cost of fertiliser used, and farm size significantly differed from zero and were important in cassava production. Also, the year of formal education, farming experience and marital status were the major socioeconomic characteristics affecting the technical inefficiency of the cassava farmers. Essentially, the technical efficiency of cassava farmers ranges between 0.334 and 0.972, with a mean value of 0.790. This shows that, on average, farmers could obtain about 80% of potential output from a given set of inputs. For technical efficiency to be improved in the study area, the year of formal education and farming experience should be considered by policymakers.
Keywords:
Cassava farmers; Technical efficiency; Ekiti State; Stochastic Frontier
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