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Research Paper | Agricultural Economics | Nigeria | Volume 5 Issue 12, December 2016

Socio -Economic Characteristics and Factors Affecting Credit Acquisition and Output of Rice (Oryza sativa) Farmers in Yakurr Local Government Area of Cross River State, Nigeria

Ettah O. I | Kuye O. O

Abstract: Socio-economic characteristics of farmers and other factors are known to affect agricultural credit acquisition resulting to low output. The study therefore attempts to examine the socio-economic characteristics and factors affecting output of credit beneficiaries of rice farmers in Yakurr Local Government Area of Cross River State, Nigeria. One hundred and eight respondents were selected through a three stage random sampling technique. Data were collected with the use of a structured questionnaire. Descriptive statistics and multiple regression analysis were used to analyze the collected data. The result showed that farmers were in their productive age (35 years), male dominated rice production (69.44 %), 81 % of the farmers were married. Results of socio-economic characteristics also show that majority of the farmers only have primary education (57 %) and only 8 years of farming experience respectively. Household size was observed to be only 8 persons mostly, 2.6 hectares of farm land were mostly cultivated by the farmers and 88 % and 85 % had no training and no membership of association respectively, while an average of 100, 086 realized as their farm-income. Result of the regression analysis shows that farm size, income and household size positively affected output of farmers at various levels of probability, while age negatively affected the output of farmers. It was recommended among others that farmers should be encouraged to belong to farmers association to enable them take advantage of such associations, extension services and training programmes should be organized for farmers by government and relevant NGOs and policies that would make farmland available to farmers should made.

Keywords: Rice, socio-economic characteristics, farmers, regression analysis, agricultural credit

Edition: Volume 5 Issue 12, December 2016,

Pages: 2120 - 2124

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