One of the important indicators of the Sustainable Development Goal (SDG) 16 (Peace, Justice and Strong Institutions) is to track the proportion of children under-5 years whose births have been registered with the appropriate civil authorities. Without an appropriate proof of a child's age, it would be difficult to ensure they receive age-specific education, immunizations and dosages of medicines. This could hamper the achievement of quality education (SDG 4), promotion of good health and well-being (SDG 3) and in the long-term reduction in poverty rates (SDG 1). In 2013, only 31\% of children were reported to be registered and only 15% were considered certified at the time of the interview (NPC2014). Most of these children are hypothesized to be living in areas with poor access to public services. However, there is little research in the economic literature that has focused on the link between accessibility and birth registration. This paper aims to fill this gap by providing answers to the following questions: 1) Are registration centers equally distributed in Nigeria 2) Are there spatial correlations in the distribution of registration centers in Nigeria? The findings suggest that registration centres are unequally distributed in Nigeria especially within the Northern Nigerian states. The average catchment area is 9529.67kms in the north compared to 1888.16kms in the south. At the state level, the average catchment area for Taraba state is 1057.75kms compared to Lagos state with a catchment area of 28.66kms. Overall, the Gini coefficient of 0.19 suggests moderate inequality with the north-west has the greatest inequality at the zonal level. Given this established inequality, an exploratory spatial data analysis is carried out at the state level. The global Moran's suggests a spatial auto-correlation, suggesting spatial clustering albeit a modest one across the states. A local spatial analysis at the state level show no hotspots in the distribution of registration centers, however six states (Adamawa, Gombe, Sokoto, Taraba and Yobe) were identified as cold spots. When the land size is considered, the results identified three hotspots (Abia, Imo and Rivers states) and ten coldspots (Adamawa, Bauchi, Borno, Gombe, Kebbi, Plateau, Sokoto, Taraba and Yobe states). Finally, the Federal Capital Territory was a significant spatial outlier.
|Publication status||Published - Nov 2019|
|Event||The IAFOR Conference for Higher Education Research / The Asian Conference on the Liberal Arts: Uncertain Futures - Lingnan University, Hong Kong, Hong Kong|
Duration: 8 Nov 2019 → 10 Nov 2019
|Conference||The IAFOR Conference for Higher Education Research / The Asian Conference on the Liberal Arts|
|Abbreviated title||CHER/ACLA 2019|
|Period||8/11/19 → 10/11/19|