ABSTRACT

This study compared the income distribution and poverty status of fishermen

in Akwa Ibom State, Nigeria. Specifically, the study analyzed the socio-

economic characteristics and the patterns of income distribution for the

various categories of fishermen, assessed the poverty status of these

fishermen and evaluated the determinants of poverty for these categories of

fishermen in the study area. The study used primary data from a cross-

section of 120 fishermen. Multi-stage sampling technique was utilized to

select representative fishermen for the study. Data used for the study were

obtained with the aid of questionnaire. Data were analyzed using descriptive

statistics, Lorenz curve and Gini coefficient, foster, Greer and Thorbecke

(FGT) weighted poverty index, and Tobit regression model. Results show that

the Gini coefficients of 0.2130, 0.5480, 0.7140 and 0.5490 were obtained for

category I (motorized canoe fishermen), category II (unmotorized canoe

fishermen), category III (Trap, hooks & nets fishermen) and for all the

categories of fishermen respectively. These results confirmed that income

disparity and levels of poverty were high among the fishermen, but greater

among category 3 fishermen than the other categories. The moderate poverty

lines (equivalent to two-thirds of mean per capita expenditure) of N2136.48,

M515.66, 906.43 and N1,266.79 were defined for categories 1,2,3 and for

all the categories as a group respectively, from where the core/extreme

poverty thresholds(one-third of mean per capita expenditure) of N1068.24,

N757.83, N453.22 and N633.39 were also obtained respective. These lines

showed that 70.83% of these fishermen fell below the estimated poverty line

while 29.17% were classified as non-poor in the study area. The results of

Tobit regression showed that the model had a good fit as the estimated

Sigma (a= 0.4140) was statistically significant (P<0.5). Results also revealed

that the poverty level (0.4812) was statistically significant (P<0.05). Tobit

regression result further showed that increase in years of formal education

and investment in modern equipment led to a decrease in the level of poverty

by 0.2080 and 0.2150 respectively. Also, a unit increase in household size,

fishing experience and labour employed in fishing operations increased

poverty level by 0.3006, 0.2181 and 0.4539 respectively. The study

recommended: that agricultural policies geared towards encouraging

fishermen to use modern fishing inputs only in the study areas should be

formulated; producing the number of children that could be adequately

catered for; and making extension services available to fishermen; among

others as strategies for poverty reduction.