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 Cit = \α + \β1 Fit + \β2 Ait + \β3 Mit + \ + \εᵢₜ, 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