African Journal of Agricultural Economics and Rural Development

ISSN 2375-0693

African Journal of Agricultural Economics and Rural Development ISSN 2375-0693 Vol. 7 (1), pp. 686-695, January, 2019. © International Scholars Journals

Full Length Research Paper

Agricultural credit demand by smallholder maize farmers in Ghana

Okyerebea Addo Koranteng and Chen Xiufeng

College of Economics and Management, Department of Agricultural Economics, China Agricultural University, 100083 Beijing, PR China.

Corresponding Author: Email: [email protected]. Tel: 008613910821844.

Accepted 26 August, 2018

Abstract

Maize is an important food crop in Ghana, accounting for more than 50% of the country’s total cereal production. However, maize yield in Ghana still remains one of the lowest in sub-Saharan Africa. Providing agricultural credit to farmers cannot be disregarded because it has significant impact in the development of agriculture. There are two sides in accessing credit thus the demand side and supply side. A lot of studies have focused on access to credit from the supply side but that alone will not give adequate information for policy makers. This study examines the factors that influence the demand for credit from the various credit sources in Ghana using multinomial logit model. Data was sourced from the Feed the Future Initiative. A sample size of 1090 farm household was selected from Brong Ahafo, Northern, Upper East and Upper West Regions of Ghana for the study. The multinomial logit model results showed that farmers demand for credit is influenced by an individual’s sex, household size, education, member of farmer-based organization, location of the farmer and land ownership. It is therefore recommended that stakeholders should formulate policies that encourage demand driven financial services from both the formal and informal sectors. Policies aimed at educating farmers by encouraging and advising them on the need to demand for credit for their agricultural activities should be implemented.

Keywords: Agriculture, Credit demand, Ghana, Multinomial logistic regression.