Hierarchical Cluster Analysis of Rural Poverty Profiles and Its Policy Implications for Targeted Poverty Alleviation Programs in Akwa Ibom State, Nigeria

Abstract

This study utilizes hierarchical cluster analysis to identify distinct rural poverty profiles in Akwa Ibom State, Nigeria, and examines their implications for targeted poverty alleviation programs. Through the use of structured questionnaires, data on 28 multidimensional poverty indicators such as income, access to basic services, education, health, housing conditions, and asset ownership amongst others were obtained and analyzed from 400 households in 30 randomly sampled rural communities in the State. The analysis of the data using factor analysis model yielded eight principal dimensions of rural poverty which accounted for 76.87 percent of the variation in the original 28 primary indicator variables. The factor scores that arose from the analysis was employed to classify the communities into three groups viz-a-viz: the core/critically poor households consisting of 14 communities and the very poor households consisting of 15 communities, with the third group described as a single-member poor community based on their poverty profiles. The analysis reveals several varied poverty clusters which ranges from households experiencing extreme multidimensional deprivation across all indicators to those facing specific, localized challenges. The findings demonstrate that rural poverty in Akwa Ibom State is not uniform but consists of distinct profiles requiring differentiated policy approaches. The research suggests that effective poverty alleviation strategies must move beyond uniform interventions to embrace cluster-specific policies that address the unique combination of deprivations characterizing each group. This nuanced approach enables more efficient resource allocation and potentially greater impact in poverty reduction efforts, providing a framework for evidence-based policymaking in the state's poverty alleviation efforts.