A Multidimensional Analysis of Insurance Exclusion in Nigeria: Drivers, Consequences, and Policy Architecture

This dissertation provides a multidimensional analysis of insurance exclusion in Nigeria, developing an original conceptual framework that integrates supply-side, demand-side, institutional, and behavioral drivers into a unified model, and empirically tests this framework using nationally representative data. Insurance exclusion, defined as the systematic inability of specific population segments to access, afford, or benefit equitably from formal insurance products, constitutes a major barrier to economic resilience and poverty reduction in Nigeria. Existing analyses treat insurance exclusion as a simple penetration measurement problem, failing to capture its multidimensional character and the heterogeneous pathways through which different groups experience exclusion. This study constructs a Nigerian Insurance Exclusion Index (NIEI) using latent class analysis applied to data from 3,000 households across all six geopolitical zones, capturing access exclusion, price exclusion, marketing exclusion, self-exclusion, and claims exclusion as distinct dimensions. Multilevel regression analysis decomposes exclusion variance across individual, household, community, and state levels, identifying the most powerful exclusion drivers at each level. Policy simulation modeling evaluates the expected exclusion reduction impact of alternative interventions including premium subsidies, mandatory inclusion quotas, and community-based distribution models. Qualitative fieldwork in twelve communities provides thick description of lived exclusion experiences. The NIEI constitutes an original measurement contribution with application across sub-Saharan Africa. Keywords: Insurance Exclusion, Nigeria, Latent Class Analysis, Multidimensional Analysis, Financial Inclusion.