This study was undertaken to identify credit constrained status of households and analyse the determinants of credit constraints in the Afigya-Kwabre District of Ghana. A multistage random sampling was used to select 166 households which comprised of 94 credit constrained households and 72 credit unconstrained households. A semi-structured questionnaire was used to elicit primary data from the respondents. The Direct Elicitation Method (DEM) was used to identify credit constrained household whilst binary logit was uused to determine households that were likely to be credit constrained. Results revealed that 57% of the households were credit constrained. Also, the results of the logit showed that sex, age, farm experience, farm size, years of formal education, household size, extension contact and distance were the major factors which significantly determine the credit constraint status of the households. In order to address the credit constrained status of the households, it is recommended that educational programs be organized by government for the households since more years of education reduces credit constraint. Credit lenders should strategically site their institutions close to the rural communities (households) to increase household credit access and reduce transaction cost. Extension workers must educate households on how they could be creditworthy to lending institutions.
This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License