A Multilevel Regression Analysis of Power-Distribution System Reliability in Tanzania: A Policy Evaluation for Infrastructure Governance

{ "background": "Chronic power outages and unreliable electricity supply remain significant impediments to economic development in many African nations. In Tanzania, governance of the power-distribution infrastructure is a critical policy concern, yet empirical analyses linking equipment-level data to system-wide reliability are scarce.", "purpose and objectives": "This policy analysis evaluates the effectiveness of current infrastructure governance by quantifying the determinants of power-distribution system reliability. The objective is to provide an evidence-based methodological framework for prioritising maintenance and investment.", "methodology": "A multilevel regression analysis is employed, modelling failure rates across hierarchical data: transformers and circuit breakers (level 1) nested within regional grids (level 2). The core statistical model is log(\λij) = \β0j + \β1X1ij + eij, with \β0j = \γ00 + \γ01Z1j + u0j. Robust standard errors are used for inference.", "findings": "Equipment age and lack of scheduled maintenance were the strongest predictors of failure. A one-year increase in transformer age was associated with a 7.3% increase in failure rate (95% CI: 5.1% to 9.5%). Regional disparities in technical capacity accounted for 31% of the variance in system reliability.", "conclusion": "System reliability is predominantly driven by equipment-level factors exacerbated by uneven regional governance capacity. Current policy frameworks are insufficiently granular to address these multilevel challenges.", "recommendations": "Policy must mandate data-driven, condition-based maintenance schedules. Infrastructure governance should be decentralised, with resources allocated based on predictive risk models and regional capacity-building programmes established.", "key words": "infrastructure governance, power distribution, reliability engineering, multilevel modelling, predictive maintenance, Tanzania", "contribution statement": "This study provides a novel, hierarchical modelling framework for power-system reliability analysis in a Tanzanian context,