AI Summary & Key Takeaways
AI InsightThe study recommends based on the outcome of this research that farm inputs such as fertilizers, chemical. and improved quality seeds should be given to sesame producers at affordable prices and at appropriate time to increase productivity and efficiency.
📌 3 Key Takeaways
Abstract
This research study analyzed production efficiency among sesame (Sesamum indicum) farmers in North West, Nigeria. Approximately, 150 sesame producers were selected among the villages utilizing a multi-stage sampling approach. Data used were of primary sources based on a well-structured questionnaire. The method employed econometric tools for analysis of data which include stochastic production efficiency frontier model (SPEFM) and principal component model (PCM). The result shows that the significant predictors influencing TE (Technical Efficiency) of sesame production include farm size, chemical, seed, fertilizer, and labour. The significant socio-economic factors increasing TE or decreasing technical inefficiency (TIE) of sesame production include education, age, years of farm experience, size of household, and extension contact. The calculated return to scale (RTS) was 1.4025, this signifies an increasing RTS. The gamma or variance ratio of 0.8038 implies that 80.38% of random variations in output of sesame is due to farmers’ inefficiency, the remaining 19.62% of sesame output deviation from the potential level was because of random noises like unexpected rainfall, frost, and other natural disaster beyond the control of sesame producers. The minimum estimated technical efficiency is 0.06, the maximum is 0.98. The average TE score of sesame producer is 0.5430 leaving out an inefficiency gap of 0.4570 for improvement. The coefficient of total variance (σ^2) is 2.9221, this was significant at 1 percent probability level, which hypothesized that perfect goodness of fit of data with the Cobb-Douglas stochastic frontier model and also the assumption of the composite error term was properly specified. The 3 major constraints faced by sesame producers include lack of credit (1st), lack of improved quality seeds (2nd), and high cost of farm inputs(3rd). The study recommends based on the outcome of this research that farm inputs such as fertilizers, chemical. and improved quality seeds should be given to sesame producers at affordable prices and at appropriate time to increase productivity and efficiency.
Özet
This research study analyzed production efficiency among sesame (Sesamum indicum) farmers in North West, Nigeria. Approximately, 150 sesame producers were selected among the villages utilizing a multi-stage sampling approach. Data used were of primary sources based on a well-structured questionnaire. The method employed econometric tools for analysis of data which include stochastic production efficiency frontier model (SPEFM) and principal component model (PCM). The result shows that the significant predictors influencing TE (Technical Efficiency) of sesame production include farm size, chemical, seed, fertilizer, and labour. The significant socio-economic factors increasing TE or decreasing technical inefficiency (TIE) of sesame production include education, age, years of farm experience, size of household, and extension contact. The calculated return to scale (RTS) was 1.4025, this signifies an increasing RTS. The gamma or variance ratio of 0.8038 implies that 80.38% of random variations in output of sesame is due to farmers’ inefficiency, the remaining 19.62% of sesame output deviation from the potential level was because of random noises like unexpected rainfall, frost, and other natural disaster beyond the control of sesame producers. The minimum estimated technical efficiency is 0.06, the maximum is 0.98. The average TE score of sesame producer is 0.5430 leaving out an inefficiency gap of 0.4570 for improvement. The coefficient of total variance (σ^2) is 2.9221, this was significant at 1 percent probability level, which hypothesized that perfect goodness of fit of data with the Cobb-Douglas stochastic frontier model and also the assumption of the composite error term was properly specified. The 3 major constraints faced by sesame producers include lack of credit (1st), lack of improved quality seeds (2nd), and high cost of farm inputs(3rd). The study recommends based on the outcome of this research that farm inputs such as fertilizers, chemical. and improved quality seeds should be given to sesame producers at affordable prices and at appropriate time to increase productivity and efficiency.