ABSTRACT

This research work on the role of micro finance institutions in rural enterprises critically examined these enterprises in two categories — farm and nonfarm operations. The specific objectives were among others to examine the socio-economic characteristics of the enterprise owners, ascertain the level of performance of the two different operations and factors affecting the decision to access loans from these micro financing institutions as well as the incomes of the two operations were tested for significance. The study adopted a simple random sampling technique in selecting 8 and 7 farm and nonfarm operators from four autonomous communities of Ezinihite L.G.A of mo State who utilized microfinance loans making a total of 60 respondents. The result of the soclo-economic characteristics revealed that certain age bracket tended towards a particular occupation. The data reveals that age bracket 20-40 had a total of 70% for nonfarm operators against 37% of their farm counterparts. The marital status of the respondents showed that single-headed households participated lower compared to the married and also, this participation was higher in agricultural related activities compared to their non-agricultural counterparts. Male-headed households participated most in agricultural related activities as given by their large 77% against a 23% female headed household. This does not in any way imply that males were most involved in agriculture.. The data on farm size shows that most farmers (about 47%) had farm sizes not less than 40% of the farmers earned between 1, 000 to 200,000 which showed I the highest proportion indicating that majority of the farmers fell within this income range. The multiple regression results for factors affecting farmers' output using the exponential form as the lead equation showed that 66.8% farm output (measured in naira) was decided by the independent variables included in the model. The result showed that farm size, number of years of schooling, farming experience and amount invested were all positive at 1%, 5%, 10% and 10% respectively while loan amount was negative at 5%. For the nonfarm operators, firm size, years of experience, and loan amount were all positive at 10% while number of years of schooling and interest amount were negative at 5% and 10% respectively. The Logit regression result for factors influencing farm operators' access to microfinance revealed that age, number of years of schooling, farm/firm size and years of experience were positive at 10%, 5%, 5% and 10% respectively while distance was negative at 10%. The t-test result showed that there was no significant difference between the two operators.