DOWNLOAD THE FULL PROJECT

1172 Users found this project useful

CONTRIBUTIONS OF WOMEN TO HOUSEHOLD FARMING DECISIONS AMONG COCOA-BASED AGROFORESTRY HOUSEHOLDS IN EKITI STATE, NIGERIA

Abstract

This study examined the contributions of women to household farming decisions among cocoa-based agroforestry households in Ekiti state, Nigeria using cross-sectional data. The study used purposive, multistage and random sampling techniques for the selection of 120 cocoa-based agroforestry farm units that constituted respondents for the study. The analytical techniques involved descriptive statistics, exploratory factor analysis and multinomial logistic regression model. With regards to food crop production activities, the contributions of women to decision making were very high with mean values of between 2.48 – 3.19 on a 4-point scale, while that of the men were comparatively low with mean values ranging from 1.85 – 2.66. However, in the cocoa production activities, the contributions of women to decision making were relatively low with mean ranging between 1.42 – 3.23 compare to high contributions of men with mean values ranging from 2.82 – 3.94 on a 4-point scale. The multinomial logistic regression result comparing high contribution (3) as base outcome, revealed that years of formal education of the women, financial contribution status of the women to farming activities, average number of hours spent on cocoa farm per day were negatively related while years of farming experience of the women and number of adult male farmers in a household were positively and significantly related with the probability of women making low (1) or medium (2) contributions to household farming decisions. The t-test of no significant difference between the contributions of women and men to farming decisions in the production of the integrated food crops and the cocoa revealed that, on the average, women had significantly higher contributions to decision making in food crop production activities while in cocoa production, men had significantly higher contributions. The identified constraints militating against women farmers were classified into three major factors using principal component factor analysis with varimax – rotated and factor loading of 0.30. These constraints range from techno-institutional factor (lack of extension programmes directed to women, lack of access to NGOs programmes and low technicalknow- how); socio-personal factor (the belief that women are subordinate, low self confidence of women, multiple domestic responsibilities of women farmers) and economic financial factor which include low/lack of financial contributions by women farmers to farming activities, involvement of the women in off farm jobs, lack of collateral security to secure loans to support farming and so on. The study, therefore, recommends inter alia,