Analysis of Technical Efficiency Differentials among Maize Farmers in Nigeria

This study analyses technical efficiency differentials and their determinants among maize farmers in Nigeria. A total sample of 300 maize farmers from Oyo and Kebbi States (150 from each) was selected, and data on input-output and socioeconomic variables were collected and analysed using descriptive statistical methods and by applying a translog frontier production function to the data. Results show that in the two states surveyed, the sizes of farms were small, and they were mostly managed by hired labour in Oyo State, and by family labour in Kebbi State. The results also indicate that the sampled farmers are not technically efficient, with mean technical efficiencies of only 0.5588 and 0.5758 in Oyo and Kebbi states, respectively. However, there are increasing returns to scale in both states. The main determinants of technical efficiency were found to include extension services and farm distance in the two states, farming experience in Oyo State, and credit accessibility, number of other crops grown and rainfall (precipitation) in Kebbi State. Furthermore, the study found that the differences in the mean technical efficiency levels of the farmers did not emanate from the absolute differences in the individual efficiencies among the farmers in the various farming communities. Nonetheless, there were significant absolute differences in the mean efficiencies among farmers in the zones of each of the two states, and the difference in the mean technical efficiencies of the two states was found to be highly significant. The study concludes that there is considerable room for improving the technical efficiencies in the two states. This, however, calls for the motivation of the farmers by making available more production inputs. It is suggested that these farmers are empowered with appropriate financial means to acquire these inputs and to hire more labour. In this way, farmers will be able to allocate more land to maize cultivation. When this is done, farmers’ productivity will improve, resulting in maximum return of farmers’ output (in quantity and value terms) per input use and, consequently, increasing their income. This will ultimately reduce hunger and alleviate poverty.