Tax Evasion, Shadow Economy Estimation, and Optimal Enforcement Policy in Nigeria: A Structural Approach

This doctoral study develops a structural econometric approach to jointly estimate the size of Nigeria's shadow economy, the magnitude of associated tax evasion, and derive implications for optimal enforcement policy design. Shadow economy estimation and tax evasion quantification are methodologically interdependent yet typically pursued in separate strands of the literature, limiting the coherence of derived policy prescriptions. This study integrates these approaches within a unified structural model drawing on Allingham-Sandmo evasion theory extended for developing country institutional realities. The structural model incorporates a currency demand equation, an electricity consumption model, and a labour market informality indicator, estimated simultaneously using a seemingly unrelated regression system on annual Nigerian data from 1990 to 2024. The model jointly identifies shadow economy size, tax gap estimates by major tax type, and the detection probability implied by FIRS enforcement activity. An optimal enforcement policy simulation derives cost-minimising audit probabilities and penalty structures for each identified tax gap segment. The study expects to find that Nigeria's shadow economy consistently exceeds 40 percent of GDP and that the tax gap attributable to shadow activity is substantially larger than the gap from formal sector non-compliance, with profound implications for prioritising audit resources toward base-broadening rather than existing taxpayer deepening. Original contributions include the first jointly estimated shadow economy-tax evasion-enforcement optimisation model for Nigeria. Keywords: tax evasion, shadow economy, enforcement policy, Allingham-Sandmo model, tax gap.