ABSTRACT
The study on the gender differentials of livelihood diversification strategies and its effects on poverty status of rural households was conducted in Niger State, Nigeria. Multi–stage sampling technique was used to select 138 male and 92 female rural households on which structured questionnaire complemented with interview schedule was employed to collect primary data. Data collected were analyzed using descriptive statistics (means, percentages and frequency counts) and inferential statistics (Logit and Tobit regression model) as well as Foster Greer and Thorbeck (FGT) model. The result of the analysis obtained showed that the male and female gender had mean age of 39 years and 35 years respectively. The male gender had a mean of 12 years in formal schooling, while the female gender had a mean of 6.5 years in formal schooling. The mean farm size of the male was 2.1 hectares and 1.4 hectares for the female. Majority (79.7%) of the male were married, while 94.6% of the female were married. Also, majority (70.3%) of the male and 88.0% of the female had contact with extension agents, 63.0% of the male and 56.5% of the female had access to credit, and 41.3% of the male and 89.1% of the female were members of cooperative societies. Livelihood diversification strategies of the rural household encompasses crop, livestock and nonfarm enterprises. The male were mostly engaged in livelihood diversification strategies such as rice (89.1%) with a mean annual income of ₦534,768, Chicken (31.2%) with a mean annual income of ₦71,349 and self–employment (61.6%) with a mean monthly income of ₦49,027, while the female were engaged mostly on vegetables production (85.9%) with a mean annual income of ₦103,533, chicken rearing (75.0%) with a mean annual income of ₦85,993 and self–employment (77.2%) with a mean monthly income of ₦35,027. Based on the poverty lines computed, 47.8% of the males were found to be non – poor, 42.8% were poor and 9.4% were core–poor, while 59.8% of the female were found to be non–poor, 27.2% were poor and 13.0% were core–poor. Result of the Logit regression marginal effect estimate revealed that household size (0.0559), farm size (0.0211), livelihood diversification strategies (0.3997), income (0.2080), extension (0.0329), credit (0.1122) and cooperative (1.0892) had influence on poverty status of the male gender, while age (-0.0372), marital status (-0.4162), expenditure (-0.1150), farm size (0.1449), livelihood diversification strategies (1.4105), income (0.7590), extension contact (0.0523) and cooperative societies (0.4451) had influence on poverty status of the female gender. The livelihood diversification strategies adopted by the male and female gender had a significant effect on the likelihood of them being poor or not. Also, Tobit regression estimate revealed that household size (0.0184), education (0.0061), farming experience (-0.0097), credit (0.1420), farm size (-0.0124), income (0.4850), expenditure (0.8790), extension contact (0.0351) and occupation (0.0747) had influence on livelihood diversification strategies of the males, while years of farming experience (- 0.0083), credit (0.2880), expenditure (0.2080), cooperative societies (0.0079) and extension contact (0.0187) had influence on livelihood diversification strategies of the females. The major constraints to livelihood diversification strategies reported by the males were inadequate access to credit ( ̅= 4.22) and poor market information ( ̅= 4.12) ranked 1st and 2nd, while the females reported increase cost of production ( ̅= 4.34) and inadequate access to credit ( ̅= 3.91) ranked 1st and 2nd. In conclusion, the female gender had lower incidence of poverty (i.e people living below the poverty line) as compared to the male gender, although, the livelihood diversification strategies adopted by the male and female had a significant effect on their likelihood of being poor or not. It was therefore recommended that rural households, government and NGOs should partner through seminar and workshops to promote effective social networks and social investment policy that will enhance livelihood diversification decisions.
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