ASSESSMENT OF EFFICIENCY OF COCOA FARMERS IN ONDO STATE, NIGERIA

Abstract

Cocoa farmers in Nigeria are mostly rural dwellers that engage in small scale production. Though past studies have established the efficiencies of cocoa farming in different parts of Nigeria, there is however a need to probe the efficiencies of cocoa famers particularly in Ondo state Nigeria. This is because Ondo state is one of the major cocoa producing states in Nigeria according to (ODSMNR, 2016). This study assessed the efficiency of cocoa farmers in Ondo State. A multistage sampling procedure was used to obtain primary data from a total of 156 farmers. Analytical techniques employed were; Descriptive statistics, Budgetary analysis, Stochastic production frontier model, Stochastic cost frontier model, Economic efficiency and Allocative efficiency model. The results revealed that cocoa farming in Ondo state was male dominated, having 91% of the total respondents. The farmers also had quite a good number of years of experience (31years). The result further showed that about 60% of the farmers were literates having at least secondary school education. The average household size of the cocoa farmers was 7 members. The average farm size was 5.4ha while majority (72.5%) of them had farm size below 5ha. 44% of the cocoa famers had planted their cocoa trees between 11 and 20 years ago. The study also showed that cocoa farmers in Ondo state had a gross margin of N796,209.43k and Return on Investment (ROI) of 1.39 per hectare. The variables used in the stochastic production frontier; Farm size, quantity of seed, quantity of agrochemical, quantity of fertilizers and quantity of labour used. Farm size, quantity of seed were significant at 1% while quantity of fertilizers and quantity of labour used were significant 5%. The quantity of agrochemicals was not statistically significant. In the inefficiency model, educational level of respondents, household size and association membership were significant at 1% while, farming experience was statistically significant at 5%. The age of the farmers was not statistically significant. The variables of the maximum likelihood cost estimates were cost of land which was significant at 5%, cost of seed was not statistically significant, cost of agrochemical was significant at 10%, cost of fertilizer significant at 5% and cost of labour was not statistically significant. The inefficiency variables were age of respondents, educational level of respondents and farmers association were significant at 1% while, extension contact was significant at 5% with farming experience and household size not statistically significant.The mean technical, economic and allocative efficiencies were 0.606, 0.594 and 0.857 respectively. The major challenges identified were fluctuation in market prices of cocoa beans, inaccessibility to finance, untimely funding, activities of pest and diseases, inadequate extension contact, high cost of agrochemicals, bad roads among others. Government should increase availability and awareness of agricultural loans that can be assessed by cocoa farmers. They should encourage research for improved quality and affordable farm inputs. The government should also make available more extension agents available to cocoa farmers