Abstract
{ "background": "District hospitals are critical nodes in Ethiopia's healthcare system, yet persistent resource constraints necessitate rigorous efficiency measurement. Panel-data econometric methods offer a robust approach for analysing efficiency dynamics over time, but the methodological frameworks applied in this specific context have not been systematically evaluated.", "purpose and objectives": "This systematic review aims to identify, critically appraise, and synthesise methodological frameworks used for panel-data efficiency estimation in Ethiopian district hospitals, assessing their applicability, limitations, and evolution.", "methodology": "A systematic search of multiple electronic databases was conducted following a pre-registered protocol. Studies employing panel-data methods (e.g., stochastic frontier analysis) to estimate technical efficiency were included. Quality assessment used a modified checklist for econometric applications. The primary estimation model synthesised was a true fixed-effects stochastic frontier: $\\ln y{it} = \\alphai + \\beta'x{it} + v{it} - u{it}$, where $u{it} \\sim N^+(\\mu, \\sigma_u^2)$.", "findings": "The review identified a predominant reliance on output-oriented stochastic frontier analysis. A key theme was the frequent omission of statistical inference on inefficiency determinants; only a minority of studies reported robust standard errors or bootstrapped confidence intervals for second-stage regression parameters. The direction of findings consistently indicated substantial, but unquantified, heterogeneity in efficiency scores across regions.", "conclusion": "Existing methodological applications are heterogeneous and often lack rigorous statistical inference, limiting the robustness of policy conclusions. There is a clear need for greater methodological transparency and the adoption of more advanced panel-data estimators that control for unobserved heterogeneity.", "recommendations": "Future research should employ system generalised method of moments estimators to address endogeneity and report cluster-robust standard errors. Policymakers should require sensitivity analyses using different panel estimators before basing resource allocation decisions on efficiency rankings.", "key words": "healthcare efficiency, stochastic frontier analysis, panel data, econometric methods, health