COMMERCIALIZING AGRICULTURE IN DEPRIVED REGIONS OF GHANA: A CASE OF THE EKUMFI DISTRICT, CENTRAL REGION

• Published in: International journal of food and agricultural economics 2021-01, Vol.9 (1), p.59-71
• Main Authors: Yeboah, Frederick Kwame, Adingo, Samuel, Coffie, Cephas Paa Kwesi, Nyarko, Daniel Ayisi
• Format: Article
• Language: English
• Subjects: Agribusiness; Agricultural and Food Policy; Agricultural policy; Agricultural production; Agriculture; Binomial distribution; Chi-square test; Commercial farming; Commercialization; Community/Rural/Urban Development; Crops; Data collection; Empowerment; Farm Management; Farmers; Farming; Farms; Food security; Food Security and Poverty; Households; International trade; interventions; Land area; Land Economics/Use; logistic; Population; Poverty; production factors; Productivity; Questionnaires; Regression analysis; Resource allocation; Rural areas; Small-scale farming; Statistical analysis; Statistical tests; subsistence; Subsistence agriculture
• ISSN: 2147-8988; 2149-3766
• DOI: 10.22004/ag.econ.309385

The subsistence nature of farming is commonly prevalent in poverty-stricken areas of Ghana. This is because a high number of farm households cultivate land sizes below 5 hectares purposely for ensuring household food security and basic survival needs. The Ekumfi district due to its position as one of the poorest districts in the central region of Ghana with a suitable Agricultural environment and the high concentration of small-scale farming activities has drawn the attention of previous and successive Governments. Employing binary logistic regression, the study focused on determining the contributing factors influencing the commercialization of agriculture with particular reference to the Ekumfi District. This is to guide future research and policy drafting concerning Agricultural commercialization interventions in the district. Soliciting views from 512 randomly sampled farmer population from 15 farming zones primarily with the aid of structured questionnaires and interviews. Among 13 demographic and production factors, 5 production factors namely market, income, credit, location, and labour statistically predicted the response variable with varying marginal effects. A chi-square statistic of 0.1% and a predictive power of 96.9% further prove the suitability of the adopted model. The study suggests similar studies in other deprived regions of the country to serve as a guide for regimented resource allocation and formulation of long term agricultural policies in the light of Ghana's Agricultural industrialization Agenda.