scholarly works

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Determinants of Child Mortality in Rural Nigeria
(2012) Adepoju, A.O.; Akanni, O.; Falusi, A.O.
This study examined the determinants of child mortality in rural Nigeria employing the 2008 Nigeria Demographic and Health Survey (NDHS) data. Data were analyzed using Descriptive Statistics and the Logit regression model. The result of analysis showed that the average age of the respondents at first birth is 19 years; while more than half of them had no formal education, and about three-fifths had less than 24 months birth interval. Secondary and higher education of mother, age of mother at first birth, place of delivery, type of birth, child ever breastfed, sex of child, were among the significant factors influencing child mortality in rural Nigeria. Maternal education, access to adequate health care (especially for pregnant women and children under five years) and increased awareness of benefits of breastfeeding were identified as the key factors to reducing child mortality in rural Nigeria.
Non-Income Inequality Among Rural Households in Nigeria
(2011) Awoniyi, O. A.
Inequality is an important factor in understanding the welfare of rural households. Most discussions on inequality have focused primarily on income to the exclusion of non-income dimensions such as skills, education, political participation, health and life expectancy. Knowledge of non-income inequality will enhance the understanding of the key welfare attributes of Rural Households (RHs). The extent of and factors affecting non-income inequality among households in rural Nigeria were investigated. The data were from 2006 Core Welfare Indicator Questionnaire Survey obtained by National Bureau of Statistics (NBS). Respondents were selected using a two-stage cluster sampling technique involving the selection of 10 Enumeration Areas (EA) from each Local Government Area followed by the selection of 10 housing units from each EA. Of the 77,400 households sampled by NBS, 59,567 were rural. Data set used included socio-economic characteristics, housing condition, assets, household educational attainment, access to health care services and political participation. Generalized Entropy, Shapley decomposition and ordered probit regression were employed in analyses (p=0.05) Mean age for respondents (RHs) was 48.7±15.3 years; Farming Households (FHs) and Non-Farming households (NFHs) were 48.7±16.2 and 48.7±14.9 years respectively. Mean household size for RHs was (4.9±2.1); FHs (4.9±3.2) and NFHs (4.8±1.9) respectively. Education, political and health inequalities among RHs were 0.409, 0.196 and 0.320 respectively. Education inequality was higher among FHs (0.413) compared with NFHs (0.407). There was higher political inequality among FHs relative to NFHs with indices of 0.200 and 0.195, respectively. Health inequality was also higher among FHs (0.327) than NFHs (0.300) respectively. North-West zone had the highest education inequality for both FHs (0.432) and NFHs (0.412). Political inequality was highest in the South-East zone for both FHs and NFHs with indices of 0.220 and 0.213 respectively. North-East zone had the highest health inequality at 0.350 and 0.319 for FHs and NFHs respectively. Between 82.7% and 95.4% of education, political and health inequalities across the zones were explained by within group disparity while the rest was by between group dynamics for all RHs. Sanitation index, asset base index, house ownership and condition index increased probability of RHs having high educational attainment by 0.004, 0.003 and 0.029 respectively. Household size and age of household head reduced educational inequality by 0.002 and 0.001. A percentage change in asset base index as well as house-ownership and condition index increased political inequality among RHs by 0.001 and 0.001 respectively. One percent increase in household size and age reduced it by 0.001 and 0.001 respectively. The probability of RHs having high access to health care increased by 0.002, 0.002 and 0.022 with 1% increase in sanitation index, asset base index, house ownership and condition. However, household size and age reduced it by 0.004 and 0.001 respectively. Educational inequality was highest across regions in the country when compared with other non-income welfare attributes. Households in the North are more politically balanced but with higher level of inequality in education and health. Furthermore, farming households are disadvantaged as they have higher inequalities in education, political participation and health care.
Impact of Fadama- II Project on Income Inequality and Poverty Reduction of Rural Households in Nigeria
(2012) Akinlade, R. J.
Efforts to reduce rural inequality and poverty in Nigeria have no appreciable impact partly due to their supply-driven approach. In recent times emphasis is shifting to demand driven approach through Community Driven Development (CDD) projects with focus on bottom-up development. Fadama-II (2004 and 2009), one of the CDD projects invested mainly in agricultural assets to increase the income of the users. However, the impact of the project on Income Inequality (IE) and poverty has not been fully established. Therefore, the impact of Fadama-II on IE and poverty reduction of rural households in Nigeria was investigated. Secondary data collected by the International Food Policy Research Institute from twelve World Bank supported Fadama-II states in 2006/2007 farming year were used. These states lie in three agroecological zones; three in Humid Forest (HF), three in Moist Savanna (MS) and six in Dry Savanna (DS). A sample of 3,750 households comprising: Fadama-II Beneficiaries (FB)-34%; Fadama-II non-beneficiaries within Fadama Local Government Areas (LGAs)-33%; and Fadama-II non-beneficiaries outside Fadama LGAs-33% was used for the study. Information used was on socio-economic characteristics, major assets and major components of household income and expenditure. The data were analysed using propensity score matching, descriptive statistics, double difference estimator, Gini-coefficient, Foster-Greer-Thorbecke weighted poverty index, and Poverty Equivalent Growth Rate (PEGR) at p=0.05 There were 1738 households with similar characteristics across the strata. Mean age (42.7 ± 11.8years) and household size (9.0 ± 6.4) of FB were not significantly different from those of the non-beneficiaries. The Per Capita Expenditure (PCE) of FB before the project was N52,703.4 ± 91,730.3. Annual PCE increased by 13.8%, 17.1% and 29.1% for HF, MS and DS zones respectively. Income inequality of FB before the project was 0.547. Fadama- II decreased IE nationwide by 21.2% with female FB having higher reduction of 27.2% compared with male of 14.1%. Income inequality of FB engaged in Up- stream Farming Activities (UFA) decreased by 19.6%, while those in Down-stream Farming Activities (DFA) decreased by 10.1%. The IE reduced by 28.4%, 12.9% and 11.7% in HF, MS and DS respectively. At a poverty line of N35,299.0 per annum, 52.2% of FB were poor before the project. Poverty Incidence (PI) reduced by 34.0% for female FB compared with 7.8% for male. The poverty incidence of FB in UFA reduced by 14.2% compared with 7.1% for those in DFA. The PI reduced by 31.8%, 7.9% and 5.6% for HF, MS and DS zones respectively. The annual growth rate of PCE of 27.7% was less than the PEGR of 45.3% for FB nationwide. The PCE growth rate of 13.8%, 17.1% and 29.1% in HF, MS and DS respectively was less than their PEGR at 48.7%, 41.0%, and 39.3% respectively. Fadama-II significantly increased income and reduced both income inequality and poverty of beneficiaries especially among females across the three agroecological zones. The project benefited a larger percentage of the poor. Hence, Economic Community Driven Development projects should be encouraged to reduce income inequality and poverty in rural Nigeria.

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