Abstract
{ "background": "Power-distribution networks in sub-Saharan Africa face persistent efficiency challenges, including high technical losses and unreliable supply. While infrastructure upgrades are ongoing, robust empirical evidence quantifying the impact of specific equipment interventions remains scarce, hindering optimal investment and policy decisions.", "purpose and objectives": "This study aims to develop and apply a rigorous quasi-experimental framework to evaluate the causal effect of modernising distribution equipment—specifically, the installation of amorphous core transformers and automated reclosers—on network efficiency within a real-world operational context.", "methodology": "A difference-in-differences design was implemented, comparing technical loss rates and supply interruption frequency between 42 treatment substations receiving the new equipment and 38 matched control substations over an operational period. The core statistical model is $Y{it} = \\beta0 + \\beta1 (Treati \\times Postt) + \\gamma X{it} + \\alphai + \\deltat + \\epsilon{it}$, where $Y{it}$ is the efficiency metric, with robust standard errors clustered at the substation level.", "findings": "The intervention yielded a statistically significant reduction in average technical losses of 4.7 percentage points (95% CI: 3.1 to 6.3). Furthermore, the frequency of sustained interruptions fell by an estimated 31% in the treatment group relative to the control, with the effect being most pronounced in rural feeder lines.", "conclusion": "The applied quasi-experimental methodology successfully isolated the efficiency gains attributable to the equipment upgrades, demonstrating their substantial practical value. The approach provides a replicable template for evidence-based asset management in constrained utility environments.", "recommendations": "Distribution utilities should prioritise the strategic deployment of high-efficiency transformers and reclosers, particularly on loss-prone feeders. Policymakers and funding bodies should mandate the use of causal evaluation frameworks, like the one presented, for post-implementation assessment of capital projects to validate returns on investment.", "key words":