Measuring the technical and economic efficiencies of maize farming in the northern region of Ghana: Deterministic and stochastic approaches

The study sets out to measure the technical, allocative and cost efficiencies of maize farmers in the Northern Region of Ghana. The region has 73% of its population as farmers, with maize being the most cultivated and consumed cereal. It is also among the poorest regions in Ghana. Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) are employed in the estimation. Face-to-face interviews were conducted on a sample of 121 farmers. The sample was selected through a multi-staged stratified mixed sampling technique. Under the variable returns to scale assumption, the study found an average efficiency of 78.2%, 47.1% and 36.9% for technical, allocative and cost efficiencies respectively. For the Constant Returns to scale, the scores were 73.6%, 46.8% and 33.7% respectively. Cost and allocative efficiency estimates were very low especially for SFA. A relatively higher scale efficiency of 86.4% was recorded. A tobit regression analysis was used to analyze the causes of inefficiency. It was found that education and household structure of farmers determined their technical efficiencies. However, in the case of allocative and cost efficiencies, land area, marital status and maize farming experience were found to significantly affect efficiencies. Gross profits of the farmers were also estimated. It showed that small scale farmers are generally more profitable than the large scale farmers. The study also found that labor was excessively used in the production process. Recommendations were made following the findings of the study.