The informal economy constitutes a significant, yet poorly measured, component of economic activity in many African nations. In Côte d’Ivoire, its substantial contribution to national output is acknowledged, but estimates vary widely due to disparate methodological approaches, obscuring accurate fiscal and economic planning. This study aims to systematically compare the efficacy and outcomes of three dominant methodologies for measuring the informal sector's contribution to gross domestic product (GDP) within a single national context. It evaluates their conceptual coherence, data requirements, and resultant estimates. A comparative analytical framework was employed, applying expenditure-based, labour force survey-based, and multiple indicator-based methodologies to a harmonised dataset. The analysis focused on methodological rigour, assumptions, and the comparability of output estimates generated by each approach. The methodologies yielded significantly divergent estimates of the informal sector's share of GDP, ranging from 35% to 52%. The multiple indicator approach, incorporating both direct and indirect proxies, produced the most stable and comprehensive estimate, suggesting a contribution of approximately 45%. The choice of measurement methodology fundamentally alters the perceived scale of the informal economy, with substantial implications for economic analysis and policy. No single method is definitive, but a hybrid, multi-proxy approach offers greater robustness for policy formulation. National statistical offices should adopt a tiered measurement strategy that integrates labour force data with periodic specialised surveys and indirect indicators. Policymakers must explicitly reference the methodological basis of informal economy estimates when designing interventions. informal economy, GDP measurement, comparative methodology, national accounts, economic statistics, Côte d’Ivoire This study provides the first systematic, comparative application of competing measurement frameworks to a harmonised West African dataset, demonstrating how methodological choices directly shape the quantified economic significance of informality.