Nigeria Agricultural Journal

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Access to microfinance facilities among agriprenuers in Abia State, Nigeria

L.A. Onyegbulam, U.T. Edozie, D.O. Onu


The study evaluated the level of access and use of microfinance by farmers in Abia State, Nigeria. A purposive sampling technique was adopted using a list of 2018 microfinance beneficiaries generated from Bank of Industry’s database and other agricultural enterprise lending institutions (LAPO, First Bank) Bank of Agriculture). A total of 150 respondents were chosen from a sampling frame of beneficiaries of microfinance programme, and administered with a structured questionnaire. Descriptive statistics and ordered logit regression analysis were used to analyze the data collected. Results showed that majority of the farmers had moderate access to microfinance facilities and that consumer microfinance loan was more readily available to the respondents with a mean of 1.94. The coefficients of the multiple choice questions on ordered logit regression analysis estimated significant factors influencing credit access as marital status and distance to microfinance source is long (+ve at 5% each), educational level (-ve at 5%), loan repayment period and inconsistent policy (-ve at 1% each). Others are; livevestock production, medium scale, small scale, local source of finance and commercial source of finance (=ve at 1% each) and long bureaucratic process (-ve at 10%). Further analysis on constraints to access to microfinance revealed that distance to microfinance source, no internet facilities, lack of co-operate affair commission registration and inconsistent policy were the most importatnt constraints militating against access to microfinance by agriprenuers in the study area with mean scores ≥ 2.5. The results therefore call for policy direction to ensure speedy procedures/ requirements to encourage farmers to access loans and more liaison offices for microfinance institutions should be established at locations closer to the farmers.

Keywords: Microfinance, Access, , Ordered logistics regression model, and Constraints

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