This paper presents empirical study of economies of scale and cost efficiency of small scale maize production in Ondo State of Nigeria, using farm level survey data collected from 200 farms in the study area. The results shows that there is a relative presence of economies of scale among the farmers meaning that an average farm in the sampled area produce at a minimum cost considering the size of the farm which is an indication that they operates in stage II of production surface (stage of efficient utilization of resource).This result was further collaborated by the mean cost efficiency of 1.161 obtained from the data analysis which shows that an average farm in the sample area is about 16% above the frontier cost, indicating that they are relatively efficient in allocating their scarce resources. The result of the analysis indicate that presence of cost inefficiency effects in the maize production as depicted by the significant estimated gamma coefficient of about 0.81 and the generalized likelihood ratio test result obtained from the data analysis.

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Purpose -The purpose of this paper is to analyze the technical efficiency (TE) of the rainfed rice farming system in Nigeria. Design/methodology/approach -Special attention is directed to the construction of confidence interval (CI) for individual efficiency estimates using stochastic frontier production model. Findings -The results show that the coefficient of the regression monotonically and significantly increased output level, while returns-to-scale (RTS) of 0.943 suggest decreasing RTS in the study. An average point estimate of TE of 0.669 is obtained from the analysis. CI show that the TE intervals are quite wide, as the assumption that farms originally identified to be on the frontier, or very close to the frontier, by the point estimate may be below the frontier. Age and years of schooling of the farmers are efficiency-increasing policy variables found in the study. Originality/value -Contrary to the previous efficiency studies, the present study demonstrates that economic inferences drawn on the basis of CI seem plausible to provide much more fruitful and insightful information about the TE of farms in the country, rather than the point estimation alone.

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The study examined the effects of land acquisition for large scale farming on the performance; productivity and technical efficiency of small-scale farming in Nigeria. The primary data for the study were collected from 200 small-scale farmers selected using the multistage sampling technique, from three local government areas in Ondo State, Nigeria. The farmers were grouped into Group A: farmers whose families donated land for large scale oil palm project and Group B: farmers whose families did not donate land for the large scale oil palm project in the study area. Data collected were analyzed using descriptive statistics, gross margin and stochastic frontier production function analyses. The study revealed that farmers in group A had long distant farms that were in small highly fragmented holdings and produced mainly arable crops that yielded smaller revenue compared with the farmers in group B. It was further revealed that group B farms were more productive in the allocation of resources and over all production as measured by the decreasing positive elasticity of production of most of the variables involved in the production function analysis. The group B farms were also more technically efficient than the group A farms. The study therefore recommends that government should open up the lands on the highways that are not owned by any family for prospective large scale agricultural producers.

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This study employed a stochastic frontier model to analyze the productivity and technical efficiency (TE) of cassava processing methods among small scale processors in SouthWest , Nigeria. The study was carried out in three states of Ogun, Oyo and Ondo, Nigeria. Data were obtained from primary sources using a set of structured questionnaire assisted with interview schedule. The multistage sampling technique was used. Data were analyzed using: descriptive statistics and the stochastic frontier production function using a farm level survey data collected from 373 small scale cassava processors. Results showed that cassava processing under local and modern methods was in stage one (stage of inefficiency) of the production region and that processors using the local method of processing cassava were more technically efficient than those using the modern method.