THE STATISTICAL ANALYSIS OF POVERTY AS A DISEASE IN NIGERIA

ABSTRACT
This study focused on the Statistical Analysis of Poverty as a disease in Nigeria case study of fisherfolks in Kwara State. Primary data was collected through structured questionnaire administered to 306 randomly selected fisherfolks. Data were analysed using descriptive statistics, the net margin Statistical Analysis, Foster Greer and Thorbecke poverty index and to bit regression model. The mean age of 40 years indicates that majority of fisherfolks fell within the productive age group and the estimated mean years of schooling implies that artisanal fisheries operations in the State were performed mostly by illiterate and semi-illiterate fisher folks. The institutional variables of fishery households revealed that fisherfolks that had access to clinic and hospital were only 8.2%. About 43% of respondents who engaged in self and traditional medication, and about 20% who uses modern drugs without prescription. About one-third of respondents‟ households, 29.1% patronized orthodox medical services for prescription. The monthly mean per adult equivalent household expenditure was ₦9075.23 with a poverty threshold of ₦6050.15. About 77.7% of total monthly expenditure of fishery households were expended on food and the left over, 22.3% comprises of payments for others. Net margin of N10, 601.98, Gross ratio of 82.5%, profit margin of 17.5% and a return on investment of 1.21 were obtained as profitability measures, which implied that for every N1 invested in fishery enterprise, a profit of ₦1.21 was made. Results of FGT decomposition revealed that poverty incidence for the whole sample households yield a poverty headcount ratio of 0.533, that is, 53.3% of the total sample households spent less than what they would need to meet minimum living standard requirements. Poverty incidence, depth and severity revealed that the years of schooling of household heads were inversely related to poverty as a disease and directly related with family size of household heads. However, fisherfolks that utilized credits, and adopt improve fishing techniques and outboard engines had lower poverty incidence, depth and severity respectively. A stochastic dominance Statistical Analysis validates the choice of poverty line. Evidence from maximum likelihood estimates of determinants of fishing households‟ poverty of  tobit regression showed that eight of the ten variables included in the model were significant at different levels (P<0.01, P<0.05 and P<0.10) and had expected a priori expectations expect nonfishing income. The study identified poor access to credit and low extension visits as prime constraints affecting fishery practices. The study recommends that State Ministry of Education in collaboration with extension agents could consider providing basic education training within the fishing communities. Fisherfolks should rejuvenate their cooperative societies to enable them feel government impact; to access credits and new innovations; opening up the rural roads by self or community effort