Abstract
This research analyzed resource productivity and determinants of technical efficiency among cassava farmers in North Central, Nigeria. This research employed a multi-stage sampling technique. Primary data were used based on a well-designed questionnaire. Inferential and descriptive statistics were employed for data analysis. The results of resource productivity of inputs show that cassava cuttings and fertilizer have the highest and lowest elasticities, respectively. The mean-TE (Technical Efficiency) score of 74% (0.74) indicates that an average smallholder cassava producer in the sample needs about 26% (0.26) additional inputs to get to the frontier. In the TE components, the coefficients of labour, and fertilizers are significant different from zero at 1% probability level. The coefficients of agrochemicals, land inputs are significantly different from zero at 5% probability level, while the coefficient of cassava cuttings are significant different from zero at 10% probability level. In the TIE (technical inefficiency), component the coefficients of age, credit received, members of cooperatives are significant different from zero at 1% probability level. The policy formulations should be directed towards considering technological substitutions and mechanized agriculture. Excessive labour supply, characteristics of the developing agriculture in sub-Saharan Africa, could be pushed into the secondary sector of the Nigerian economy such as the cassava processing industry, therefore generating income, employment and maintaining Nigeria in the first (1st) position in the world ranking in term of cassava output. Also, it is recommended that improved cuttings, agrochemicals, and fertilizers should be made available to cassava farmers at appropriate time to increase productivity. Furthermore, credit should be made available to cassava farmers at a single digit interest rate, devoid of cumbersome administrative procedures.
Keywords: Resource productivity, technical efficiency, cassava farmers, stochastic frontier model, Nigeria