Tripartite analysis of multidimensional poverty intensity in Nigerian Cities

Poverty remains a challenge requiring multidimensional interventions. The study examines the key indicators contributing to multidimensional poverty intensity across the three multidimensional poverty indices (MPI) specifications. A grid sampling technique was used to sample 1098 household heads for questionnaire administration using Geographic Open Kits (GeoODK) across three selected cities in Nigeria. Mapping techniques were used to reveal the spatial distribution of multidimensional poverty. Backward regression and Generalized Linear Model (GLM) Multivariate Analysis were inferential techniques used in this study. Results show that the most significant contributors to multidimensional poverty under all specifications were indicators of health and education- feeding (β = 0.605, p = 0.00), school attendance (β = 0.410, p = 0.00), and health (β = 0.154, p = 0.00) for MPI-1; feeding (β = 0.426, p = 0.00), and school attendance (β = 0.272, p = 0.00) for MPI-2, and majorly school attendance (β = 0.312, p = 0.000) and sanitation (β = 0.317, p = 0.000) for MPI-3. There is a statistically significant collective difference in multidimensional poverty incidence and intensity at Lambda-value (0.709) and p-value (0.000) for all three specifications of multidimensional poverty. This study concludes that feeding and school attendance are the major indicators of multidimensional poverty in the study area. This study recommends a policy that prioritizes basic social amenities, especially elementary education and primary healthcare, which would enable residents to escape multidimensional poverty in all its specifications at the ward level.