Ocean Fishery Dependence, Poverty and Inequality Nexus: Micro Leve Empiric Evidence From the Coastal Lowlands of Kenya

Abstract

Kenya’s ocean fishery resource offers livelihood options and a source of income to poor rural households. Although the resources have the potential to alleviate poverty and inequality higher dependence can perpetuate poverty. Poverty and inequality remain development concerns and have been at the forefront of policy agendas worldwide. However, the effort has been compromised by environmental degradation, poor infrastructure, and inadequate institutional support, particularly in Kilifi County. Therefore, the study sought to contribute to the achievement of blue economy sub-themes such as poverty eradication, inclusive economy, food security and managing and sustaining marine life through sustainable dependence and livelihood among households in Kilifi County, Kenya. Multi-stage sampling technique was used to collect data from 384 households. Primary data was obtained through structured pretested questionnaires administered by trained enumerators. Data was analyzed using both SPSS and STATA packages. Descriptive statistics was employed to determine the livelihood options among households. Results indicated that ocean fishery and related activities is the highest livelihood option with participation rate of approximately 68% exhibiting gender differences. Ocean fishery and related activities is a male dominated livelihood option; however, females were more than a half in fish trading and small scale processing since it required low capital and unskilled labour. Fractional response model was also used to determine factors affecting ocean fishery dependence. Education level, agricultural productive assets, access to credit, group membership, security tenure, flood, and fish price were found to significantly influencing ocean fishery dependence. Further, multi-dimension poverty indices were estimated and later multivalued treatment effect approach was used to determine the effect of ocean fishery dependence on the indices. The households were classified on non-dependency, low dependency and high dependency and were approximately 32.0%, 18.0% and 50.0% respectively. The results revealed that there were significant differences between different dependence levels in each welfare outcome, a finding that would not have been obtained by binary treatment effect methods. The results also indicated that increasing ocean fishery dependence increased multi-dimension poverty indices among dependent households. The study, therefore, recommends a clear stakeholder mapping coupled with the effective institutional and regulatory framework to enhance sustainable ocean fishery dependence that will contribute to the achievement of blue economy approach.