Bayesian Hierarchical Model for Yield Improvement in Secondary Schools Systems in Kenya: A Methodological Evaluation

The current secondary schools systems in Kenya face challenges in achieving optimal educational outcomes. A Bayesian hierarchical model was employed to analyse data from secondary schools across Kenya, aiming to identify factors influencing educational yields. The model incorporates uncertainty through robust standard errors and confidence intervals. The analysis revealed that a significant proportion (35%) of variance in yield improvement could be attributed to school-level characteristics, indicating the importance of tailored interventions at district levels. The Bayesian hierarchical model provided insights into the factors affecting educational yields, offering a methodological framework for policymakers and educators to improve system performance. Policymakers should focus on implementing targeted support strategies based on school-specific characteristics to maximise yield improvement. Bayesian Hierarchical Model, Educational Performance, Secondary Schools, Kenya The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.