Millet is grown in the large savanna region of Nigeria mostly in a system of intercropping with other crops. The study seeks to analyse the efficiencies of millet-based production pattern and its determining factors in the derived savanna zone of Nigeria. Data were collected from primary sources using a structured questionnaire administered to the selected 196 millet-based farmers. Input oriented Data Envelope Analysis (DEA) and Tobit regression model were used to achieve the aims of the research. The mean Technical Efficiency (TE) of the millet and sorghum (MS), millet-sorghum-groundnut and cowpea (MSGC), millet-sorghum and groundnut (MSG), millet-sorghum and cowpea (MSC) and sole millet (SM) were 40, 21, 38, 32 and 48 % respectively. This suggests that in the short run, there are gaps of 60, 79, 62, 68 and 52 % to increase the efficiency levels respectively. This may be through enhanced use of accessible production inputs. The mean Allocative Efficiency (AE) for the millet-based farmers was 0.56, 0.55, 0.67, 0.56 and 0.91 for MS, MSGC, MSG, MSC and SM respectively. The results revealed that estimates of factors that influence millet-based farmers’ systems have different degrees of statistical significance and where the level of significance is the same, the magnitude and direction were not the same. The numbers of millet-based farms operating under constant, increasing, and decreasing returns to scale were also estimated. The result of sensitivity analysis for an optimum plan for millet-based inputs used showed that land, seed, labour, fertilizer and agrochemicals are not limiting resources to obtain optimal farm plan. These results indicate the units needed to be decreased from various millet farms respectively for optimal production. More youths should be encouraged by the government and private organizations by providing them with necessary incentives to engage in farming to minimize inefficiency associated with older aged farmers.
Millet is grown in the large savanna region of Nigeria mostly in a system of intercropping with other crops. The study seeks to analyse the efficiencies of millet-based production pattern and its determining factors in the derived savanna zone of Nigeria. Data were collected from primary sources using a structured questionnaire administered to the selected 196 millet-based farmers. Input oriented Data Envelope Analysis (DEA) and Tobit regression model were used to achieve the aims of the research. The mean Technical Efficiency (TE) of the millet and sorghum (MS), millet-sorghum-groundnut and cowpea (MSGC), millet-sorghum and groundnut (MSG), millet-sorghum and cowpea (MSC) and sole millet (SM) were 40, 21, 38, 32 and 48 % respectively. This suggests that in the short run, there are gaps of 60, 79, 62, 68 and 52 % to increase the efficiency levels respectively. This may be through enhanced use of accessible production inputs. The mean Allocative Efficiency (AE) for the millet-based farmers was 0.56, 0.55, 0.67, 0.56 and 0.91 for MS, MSGC, MSG, MSC and SM respectively. The results revealed that estimates of factors that influence millet-based farmers’ systems have different degrees of statistical significance and where the level of significance is the same, the magnitude and direction were not the same. The numbers of millet-based farms operating under constant, increasing, and decreasing returns to scale were also estimated. The result of sensitivity analysis for an optimum plan for millet-based inputs used showed that land, seed, labour, fertilizer and agrochemicals are not limiting resources to obtain optimal farm plan. These results indicate the units needed to be decreased from various millet farms respectively for optimal production. More youths should be encouraged by the government and private organizations by providing them with necessary incentives to engage in farming to minimize inefficiency associated with older aged farmers.
Primary Language | English |
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Subjects | Behaviour-Personality Assessment in Psychology |
Journal Section | Makaleler |
Authors | |
Publication Date | January 26, 2021 |
Acceptance Date | December 27, 2020 |
Published in Issue | Year 2021 Volume: 5 Issue: 1 |