Methodological Evaluation and Panel-Data Estimation of Power-Distribution Equipment Cost-Effectiveness in Senegal, 2000–2026

"background": "The economic sustainability of power-distribution infrastructure in sub-Saharan Africa is a critical engineering challenge. Existing cost-effectiveness analyses often lack robust, longitudinal methodologies, leading to suboptimal investment planning and asset management. ", "purpose and objectives": "This study aims to develop and apply a novel panel-data econometric framework to evaluate the cost-effectiveness of key power-distribution equipment in a West African context, providing evidence for lifecycle cost modelling and capital planning. ", "methodology": "A balanced panel dataset for transformers, switchgear, and conductors was constructed from utility records and procurement databases. Cost-effectiveness was modelled using a generalised least squares estimator with fixed effects for regions and equipment types. The core model is C{it = \ + \1 Fit + \2 Ait + \3 Mit + \ + \₈ₓ, where C is total lifecycle cost, F is failure rate, A is age, and M is maintenance expenditure. Robust standard errors were clustered at the equipment-cohort level. ", "findings": "Transformer assets demonstrated superior long-term cost-effectiveness, with a 10% increase in preventive maintenance expenditure associated with a 3. 2% reduction in total lifecycle cost (95% CI: 2. 1% to 4. 3%). Conversely, certain conductor types showed significantly higher failure-induced costs than previously estimated. ", "conclusion": "The panel-data approach provides a more rigorous basis for evaluating distribution equipment performance than static models. Significant heterogeneity exists in the cost-effectiveness of different asset classes, influenced strongly by maintenance regimes. ", "recommendations": "Utilities should prioritise investment in predictive maintenance for transformers and review specifications for overhead conductors. The methodological framework should be adopted for long-term infrastructure planning to optimise capital and operational expenditure. ", "key words": "power distribution, cost-effectiveness, panel data, asset management, lifecycle costing, econometric modelling", "contribution statement