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SPATIAL CONCENTRATION OF POVERTY AND ITS DETERMINANTS IN NIGERIA
Published 2013-08Subjects: “…Spatial probit…”
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Page will reload when a filter is selected or excluded.- Poverty rate 1 results 1
- Poverty reduction programmes in Nigeria have not had significant intended effects. This can be attributed to the non-consideration of the heterogeneous nature of poverty and spatial contiguity of geographical units in their designs. There is scarce information on spatial decomposition and spillover of poverty across the Senatorial Districts (SD) in Nigeria. Therefore, the spatial concentration of poverty and its determinants were investigated. The study employed secondary data from Nigeria Living Standard Survey (NLSS) and Core Welfare Indicators Questionnaire (CWIQ) survey conducted by National Bureau of Statistics (NBS), Independent National Electoral Commission (INEC) and Food and Agriculture Organization (FAO). The NLSS and CWIQ were conducted in 2004 and 2006 respectively. The national sample sizes for NLSS and CWIQ were 22,200 and 77,400 household units respectively. Following the elimination of households with missing values, samples considered for the study were 18,760 and 54,536 households for NLSS and CWIQ respectively. The Poverty Rate (PR) per SD was obtained from household consumption expenditure data sourced from NLSS. Data on Household Size (HS), Household Membership of Association (HMA), Households’ Access to Health Facilities (AHF), People Employed in Agriculture (PEA), Access to Credit Facilities (ACF) and Literate Adult (LA) were obtained from CWIQ. Data on Number of Years Spent in the National Assembly by Senators (NYSNAS) (1999 – 2004) and soil fertility classification of Nigeria were sourced from INEC and FAO respectively. These variables and spatial dimension were hypothesized to influence PR. Data were analysed using descriptive statistics, Foster Greer and Thorbeck model, spatial regression, local indicator of spatial association and spatial probit at p = 0.05. Mean annual household per capita consumption expenditure was N28475.01 ± N11967.5. Percentage of PEA in the SD was 44.2 ± 18.4% while mean HS was 6.5 ± 1.5. Mean values of NYSNAS, ACF and AHF were 4.3 ± 0.5years, 10.5 ± 7.4% and 51.6 ± 18.2% respectively. Fifty-six percent of the SD had fertile soils. Average national PR of the SD was 56.03 ± 24.1%. Fifty three of the SD had PR below the national average. The Moran’s I value (3.4) indicated that spillover of poverty existed among SD. Ten percent increase in PR in one SD resulted in 3.1% increase in PR in the neighbouring SD ( = 0.3). Fifty-two percent of the SD with significant spatial association had low PR neighboured by low PR SD, 41.03% of the SD with high PR were neighboured by high PR SD. The PR in high-high SD was significantly reduced by HMA (-0.9), AHF (-0.3), ACF (-0.9), LA (-1.1), fertile soil (-5.2) and NYSNAS (-6.6). Poverty rate was significantly increased by PEA (0.4) UNIVERSITY OF IBADAN LIBRARY iv and HS (5.5). Mean PR in high-high and low-low SD was 82.6% and 31.8% respectively. Household’s probability of being poor was higher in high-high SD (0.8) compared to low-low (0.08). Poverty incidence in a senatorial district influenced the neighbouring senatorial district. Reduction in poverty incidence would be achieved through households’ membership of associations, improved access to health and credit facilities. Keywords: Spatial concentration, Poverty rate, Spatial probit, Senatorial district Word count: 491 1 results 1
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- Spatial probit 1 results 1