This paper explores access to agricultural microcredit in Ghana using household survey data collected for the 2013/2014 farming season. The study approaches the access to microcredit from two angles pertaining to the factors influencing access to loan and when accessed, the determinants of loan size. Since these two choices are related, the Heckman selection model was chosen as the analytical tool for addressing the possible presence of sample selectivity bias in the loan size regression. A multi-stage stratified random sampling technique was used to select 300 smallholder rice farmers from three irrigation schemes in Northern Ghana who were interviewed using a semi-structured questionnaire. The study revealed that the following factors influence access to agricultural microcredit in Northern Ghana: gender, household income, farm capital, improved technology adoption, contact with extension, the location of the farm, and awarenes s of lending institutions in the area. Gender, household size, farm capital, cattle ownership and improved technology adoption were the significant factors determining loan size. The study recommends the improvement of extension service delivery to smallholder farmers to enable them to access microcredit facilities for agricultural production.
Key words: Agricultural microcredit, binary probit model, Heckman selection model, loan size, Northern Ghana, smallholder farmers.
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