The Landscape of Poverty in Nigeria: A Spatial Analysis Using Senatorial Districts- level Data

Abstract

The study decomposes the Landscape of Poverty in Nigeria based on the significance of spatial contiguity using Senatorial Districts -level Data. The data used for the study were obtained fro m Nat ional Living Standard Survey and Core Welfare Indicators Questionnaire Survey conducted by National Bureau of Statistics in 2004 and 2006 respectively. Exp loratory spatial data analysis and spatial autocorrelation test were carried out on poverty incidence data. Average national poverty rate of the Senatorial Districts (SD) was 56.0%. Forty nine percent of the SD had poverty rate (PR) below the national average. The global Moran's I value obtained is strongly positive (0.6657), indicating that spillover of poverty exist among SD. The study revealed that 52% of the SD with significant spatial association had low PR neighboured by low PR SD (Low-Low), 41% of the SD with high PR were neighboured by high PR SD (High-High) and 7% of SDs with low PR were surrounded by high PR SD (Lo w-High). The mean PR in high-high and low-low SDs was 82.6% and 31.8% respectively. The study recommends that for a significant poverty reduction to be achieved in Nigeria, greater attention in terms of poverty allev iation strategies should be concentrated on the senatorial d istricts that constitute the hotspots of poverty.

Measuring intra-urban poverty using land cover and texture metrics derived from remote sensing data

“…(Duncan et al, 2012;Holt, 2007;Okwi et al, 2007;Orford, 2004;Sowunmi et al, 2012;Voss et al, 2006). The results of the statistical analysis indicate that the most important remote sensing predictors of the Slum Index at the analytical region level for Medellin include the percentage of impervious surfaces, the fraction of clay roofs over impervious surfaces, the overall complexity factor and the variation of heterogeneity as a function of the distance factor.…”

Exploring the geographical variations and influencing factors of poverty in Nigeria

“…In the context of Nigeria, which has one of the highest poverty rates in the world, studies examining the local predictors of poverty based on nationally representative data are sparse. In other words, existing studies that have examined the concept of poverty and its determinants in Nigeria did so by analyzing the pattern of poverty and modeling global relationships, which fails to consider how the geographic attributes of each state/region drives poverty differently across the country, thereby leading to ineffective policies to tackle the problem (Aderounmu et al, 2021; Akpan & Isihak, 2020; Apata et al, 2010; Buba et al, 2018; Deinne & Ajayi, 2019; Obayelu & Awoyemi, 2018; Ogwumike & Akinnibosun, 2013; Olowa, 2012; Omotoso et al, 2021; Sowunmi et al, 2012; Sulaimon, 2020). To bridge this gap in the literature, we identify the local predictors of poverty across the states in Nigeria in order to come up with targeted policy interventions.…”