No abstract

No abstract

Purpose Globally, corruption has been identified as a major problem. Even though corruption is widespread, it varies in magnitude, types and consequences. In Nigeria, corruption is endemic, and it is responsible for the many socioeconomic problems in the country. Hence, the study aims to determine the patterns and state level correlations of corruption in Nigeria. Design/methodology/approach Data for this study were sourced from the National Bureau of Statistics and other official sources and were analyzed with Global Moran’s I, Local Moran’s I and multivariate step-wise regression. Findings This study’s findings revealed significant clustering of corruption in the country with Rivers States as the only hotspot (I = 0.068; z = 2.524; p < 0.05), while domestic debt and market size were the state level significant predictors. Research limitations/implications Only bribery as a form of corruption was examined in this study, more studies are needed on the predictors of other forms of corruption. Practical implications This study recommends increased market competition through investment grants, subsidies and tax incentives to facilitate trade interactions among Nigerians, which can lead to exchange of cultural norms that discourage corruption. It is also advocated that domestic debt must be effectively and efficiently channelled towards economic development which in the long run will have a positive impact on the socio-economic well-being of the citizens as well as drive down corrupt practices. Originality/value Although the causes of corruption have received considerable attention in the literature, little is known on the geographical distribution and the effect of market size and domestic debt on corruption in Nigeria.

The high rate of poverty in Nigeria is alarming with over 105 million people living in poverty. Despite the significant proportion of the population living in poverty in the country and the obvious spatial variations, there is scant evidence regarding the spatial factors driving the variations, leading to ineffectual policies for tackling the problem. Thus, the aim of this study is to analyze the geographical distribution of poverty and the predictors across Nigeria with a view to providing spatially explicit policies to curb the high poverty rates. The data were obtained from the United Nations Development Program Report and the National Bureau of Statistics. Spatial statistics of global and local Moran's indexes, ordinary least squares regression, and the geographically weighted regression techniques were adopted for the data analysis. Noticeable geographical variations in poverty rates in the country were observed, with high clusters in northern Nigeria. Moreover, the predictors of poverty differed significantly across the country, following socioeconomic pathways and location. While the illiteracy rate and location (distance to the coast) were predictors of poverty in northern Nigeria, unemployment was more of a predictor in southern Nigeria. The study recommends spatially explicit policies to curb poverty in the country.

No abstract