The performance of water treatment infrastructure in Kenya is critical for public health and economic development, yet systematic, longitudinal analyses of its operational risks are scarce. Existing policy evaluations often lack the technical rigour to isolate the effects of specific interventions from other confounding factors. This policy analysis aims to quantify the impact of targeted infrastructure investments and regulatory changes on the operational risk profile of water treatment systems. It seeks to identify which policy levers most effectively reduce failure rates and improve reliability. A balanced panel dataset of facility-level performance indicators was constructed. The core analysis employs a fixed-effects model: FailureRate₈ₓ = ᵢ + ₁Investment₈ₓ + ₂RegulatoryScore₈ₓ + X₈ₓ + ₈ₓ, where ᵢ denotes facility-specific effects. Inference is based on robust standard errors clustered at the county level. A one-standard-deviation increase in the regulatory compliance score was associated with a 17. 5% reduction in the probability of a major treatment failure. The effect of capital investment was positive but statistically insignificant after controlling for facility heterogeneity and maintenance expenditure. Enhanced regulatory oversight and performance monitoring are more strongly correlated with reduced operational risk than capital expenditure alone. This suggests that policy must prioritise governance and operational management alongside physical asset renewal. Policy should mandate and fund continuous performance monitoring to inform targeted maintenance. Regulatory bodies require strengthened enforcement capabilities. Future investment programmes must integrate explicit operational risk benchmarks. infrastructure resilience, panel data, fixed effects, regulatory compliance, operational risk, water treatment This study provides the first longitudinal, facility-level econometric assessment of water treatment policy effectiveness in the region, introducing a novel risk-reduction metric tailored for engineering asset management.
Ochieng et al. (Wed,) studied this question.