"background": "Transport infrastructure maintenance in West Africa is critical for economic development but often constrained by resource inefficiencies. Systematic, quantitative evaluations of operational improvements within public sector maintenance depots are scarce, particularly those employing robust causal inference techniques. ", "purpose and objectives": "This paper develops and applies a quasi-experimental econometric model to rigorously quantify the causal effect of a reorganisational intervention on the operational efficiency of a network of road vehicle maintenance depots. ", "methodology": "A difference-in-differences (DiD) model is specified: Y{it = \ + \ (Treati \ Postt) + \ + \ +, where Y₈ₓ is the depot efficiency score. Treatment and control groups were defined from depot administrative records. The parallel trends assumption was tested using lead-lag models, and inference was based on cluster-robust standard errors at the depot level. ", "findings": "The intervention generated a statistically significant positive effect. Treated depots demonstrated a 17. 5% increase in their composite efficiency score relative to control depots (95% CI: 9. 2% to 25. 8%). The gains were primarily driven by reductions in vehicle downtime and improved inventory turnover. ", "conclusion": "The applied DiD framework provides credible evidence that targeted organisational restructuring can yield substantial efficiency improvements in public transport maintenance operations. The methodology offers a template for evidence-based decision-making in infrastructure asset management. ", "recommendations": "Infrastructure agencies should adopt similar causal evaluation frameworks for programme assessment. Policy should focus on replicating the specific managerial and logistical changes validated in the treatment group, particularly those relating to spare parts procurement and workshop scheduling. ", "key words": "infrastructure management, causal inference, operational efficiency, maintenance depots, difference-in-differences", "contribution statement": "This paper presents a novel application of the DiD model to isolate the causal impact of a management intervention within African public sector
Sarr et al. (Wed,) studied this question.