American Journal of Applied Sciences

Impact of Microfinance on the Efficiency of Maize Producers in Nigeria

Muhammad Auwal Ahmed, Zainalabidin Mohamed, Abdullahi Iliyasu and Golnaz Rezai

DOI : 10.3844/ajassp.2017.569.577

American Journal of Applied Sciences

Volume 14, Issue 5

Pages 569-577

Abstract

The study applies descriptive analysis, Slacks-Based Measure (SBM) of efficiency model and fractional regression model to data collected in 2016 using cross-sectional survey of maize producers in Nigeria. The purpose was to determine the impact of microfinance on the technical efficiency of maize producers and evaluates factors that influence inefficiency among credit beneficiaries and non-credit beneficiaries. Results show that the respective mean technical efficiency of credit beneficiaries and non-credit beneficiaries were 79 and 69%, which is far from the frontier technology. This means that technical efficiency can be improve by 21 and 31% respectively, with the same set of inputs. Slacks analysis shows that in order to attain optimum efficiency, credit beneficiaries should reduce fertilizer usage by 32.34%, seeds by 6.03%, labour by 7.79% and agrochemicals by 2.44% per hectare. Similarly, non-credit beneficiaries should reduce the usage of fertilizer slacks by about 19.48%, seeds by 2.73%, labour by 2.54% and agrochemicals slacks by 1.76% per hectare. Microfinance credit, household size, years of farming experience and education increases efficiency, while drought and age declines efficiency. Findings are useful to the farmers as appropriate input reduction for inefficient farms can be set to enable them attain optimum efficiency level. Maize producers should be encouraged to collect microfinance loan in order to increase their scale of operations and government in collaboration with research institutes should educate farmers on the actual input quantities to apply. This could help to reduce production costs, increase the farmers’ efficiency and provide maize to consumers at an affordable rate.

Copyright

© 2017 Muhammad Auwal Ahmed, Zainalabidin Mohamed, Abdullahi Iliyasu and Golnaz Rezai. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.