3 research outputs found
Rural Land Market, Livelihood and Welfare among Households in Oyo State, Southwest Nigeria
With rapid population growth and resulting increased land fragmentation, landholding becomes smaller, negatively impacting on the living standard of rural households. Thus, the need to understand the potentials of land markets to improve rural households’ access to land through the adjustment of households’ landholding for livelihood activities, and its consequent effect on their welfare. This paper examined the relationship between rural land market, livelihood and welfare among households in Oyo state, Southwest Nigeria. Using a structured questionnaire, a survey was conducted on a sample of 200 respondents, who were selected through multistage sampling procedure. Descriptive statistics, Land Market Index (LMI), Tobit model and multiple regression analysis were used to analyse the primary data. Results show that majority (74.0%) of households were involved in crop farming with mean income of ₦53 833.33 (±26 784.560), which was relatively higher than livestock ₦31 567.08 (±20 897.47). The mean total monthly expenditure was ₦26 548.50 (±8945.5692). Identified land transaction methods include purchase (76.3%), lease (19.8%), and rent (3.9%). On the average, 97.0% of land held by households were acquired through market (LMI=0.97). Sex and household status had significant positive effects on the extent of households’ participation in land market at p<0.01. Also, LMI, crop farming and livestock farming had significant positive effect on households’ welfare. Obtaining land through market for livelihood activities promotes households’ welfare. Rural land market and livelihood activities have significant positive effects on the welfare of farmers. There is need for Government to facilitate formal land markets in rural areas
Educación y empleo femenino en Nigeria
This paper examined female education and employment in Nigeria. The 2018 Nigeria Demographic and Health Survey data (NDHS, 2018) was used. After sorting out for missing data, 28,494 women’s individual data were used. Data were analyzed using descriptive statistics and Multinomial logit regression. Only 0.3% of women in Nigeria are unemployed while 99.7% are employed in skilled and unskilled jobs. However, only 13.4% of the women are engaged in skilled employment; 8.5% are in professional/technical/managerial jobs while 4.9% are involved in skilled manual. The majority (86.3%) are in the unskilled manual employment category; 1.6% in clerical, 49.4% in sales, 9.5% in services, 0.1% in unskilled manual and 25.7% in Agriculture. The likelihood of being involved in professional/technical/managerial employment by women in Nigeria increases with age (0.06), region {North West (1.18), South West (1.87}, educational level {secondary (0.68), tertiary (1.64)}, wealth index{richer (0.90), richest(0.95)}. On the other hand, the likelihood of being engaged in professional/technical/managerial employment type reduces with large household size >10persons (-0.71). Engagement of women in skilled employment types are driven by education while education discourages them in engaging in unskilled employment types. However, because the highest proportion of the women have secondary education, they are found more in the unskilled employment types. Also, engagement in skilled employment types is driven by wealth index while age drives skilled and unskilled employment types. Nigerian women are not much involved in skilled employment, the right policy should be put in place to educate girls beyond the secondary education level and enlighten them on the need to be involved in skilled employment.Este documento examina la educación y el empleo femenino en Nigeria. Se utilizaron los datos de la Encuesta Demográfica y de Salud de Nigeria de 2018 (NDHS, 2018). Después de depurar los datos faltantes, se utilizaron los datos individuales de 28,494 mujeres. Los datos se analizaron utilizando estadÃsticas descriptivas y regresión logit multinomial. Solo el 0.3% de las mujeres en Nigeria están desempleadas mientras que el 99.7% están empleadas en trabajos calificados y no calificados. Sin embargo, solo el 13.4% de las mujeres están involucradas en empleos calificados; el 8.5% en trabajos profesionales/técnicos/gerenciales, mientras que el 4.9% están en trabajos manuales calificados. La mayorÃa (86.3%) está en la categorÃa de empleo manual no calificado; el 1.6% en trabajos clericales, el 49.4% en ventas, el 9.5% en servicios, el 0.1% en trabajos manuales no calificados y el 25.7% en agricultura. La probabilidad de estar involucrada en empleos profesionales/técnicos/gerenciales para las mujeres en Nigeria aumenta con la edad (0.06), la región {Noroeste (1.18), Suroeste (1.87)}, el nivel educativo {secundaria (0.68), terciaria (1.64)}, el Ãndice de riqueza {más rico (0.90), el más rico (0.95)}. Por otro lado, la probabilidad de estar involucrada en empleos profesionales/técnicos/gerenciales disminuye con un tamaño de hogar grande >10 personas (-0.71). La participación de las mujeres en tipos de empleo calificado está impulsada por la educación, mientras que la educación las desalienta de participar en tipos de empleo no calificado. Sin embargo, debido a que la mayor proporción de las mujeres tiene educación secundaria, se encuentran más en los tipos de empleo no calificado. Además, la participación en tipos de empleo calificado está impulsada por el Ãndice de riqueza, mientras que la edad impulsa tanto el empleo calificado como el no calificado. Las mujeres nigerianas no están muy involucradas en empleos calificados, se debe implementar la polÃtica adecuada para educar a las niñas más allá del nivel de educación secundaria y concienciarlas sobre la necesidad de involucrarse en empleos calificados
Income Diversification, Inequality and Poverty among Rural Households in Oyo State, Nigeria
The study examined income diversification, inequality and poverty among rural households in Oyo state, Nigeria. Cross-section data were generated from the survey conducted on a sample of 200 households with the aid of structured questionnaire using multi-stage sampling procedure. Descriptive statistics, diversification index, Gini coefficient, FGT poverty index, and the Probit regression model were used to analyze data. Mean income diversification index of 1.22 shows that majority of the respondents had multiple streams of income but crop farming had the largest share (90%) in total income. Mean income of respondents was ₦77,613.2±83575.01, and Gini coefficient of 0.48, 0.46, and 0.39 were obtained for total income, nonagricultural income, and agricultural income respectively. The poverty line was ₦6,490.50 and mean per capita expenditure was ₦9,735.74. The head count ratio showed that 53.5% of the households were poor while 46.5% were regarded as non-poor, and poverty gap was 0.214. From probit results, age, secondary occupation, and farm size had significant inverse relationship with poverty status. Having primary and secondary income sources is poverty reducing, therefore, rural households should be encouraged to remain in farming, especially crop farming, and motivated through skill acquisition to diversify into other income generating activities.