Abstract
{ "background": "The expansion and modernisation of electrical grids in developing nations require robust evidence to guide the selection of power-distribution equipment. Prior evaluations in the region have often relied on observational data, lacking rigorous counterfactual analysis to isolate the effect of specific technological interventions on adoption rates.", "purpose and objectives": "This study aims to methodologically evaluate the adoption rates of different power-distribution equipment systems using a quasi-experimental design. The primary objective is to quantify the causal impact of equipment type on adoption, controlling for key infrastructural and socio-economic confounders.", "methodology": "A comparative quasi-experimental design was employed, utilising a difference-in-differences framework with propensity score matching. The analysis is based on a longitudinal dataset of equipment deployments and connection records. The core statistical model is a linear probability model: $Adoption{it} = \\alpha + \\beta1(Postt \\times Treatmenti) + \\gamma X{it} + \\epsilon{it}$, where robust standard errors are clustered at the district level to account for serial correlation.", "findings": "The analysis indicates a statistically significant positive effect for modern composite pole systems over traditional concrete and steel options. The estimated average treatment effect on the treated (ATT) was 0.18 (95% CI: 0.12, 0.24), suggesting an 18-percentage-point increase in household connection rates in treated areas. The robustness checks, including placebo tests, support the validity of the causal interpretation.", "conclusion": "The quasi-experimental design provides a rigorous methodological framework for evaluating engineering adoption in real-world settings. The findings demonstrate that equipment choice is a non-trivial factor influencing the pace of electrification, with composite systems showing superior performance in the studied context.", "recommendations": "Grid planners and policymakers should incorporate quasi-experimental evaluation techniques into the technology selection process. Procurement guidelines should be updated to prioritise equipment types with empirically verified higher adoption impacts, contingent on localised cost-benefit analysis