A Bayesian Hierarchical Model for Evaluating Yield Improvement in Secondary Schools Systems within Ghana's Forest Policy Context

The theoretical framework for this article focuses on evaluating yield improvement in secondary schools systems within Ghana's forest policy context. A Bayesian hierarchical model will be employed, incorporating both fixed effects and random effects to account for variability across different schools and regions within Ghana's educational system. The model will include parameters such as student attendance rates, teacher qualifications, and infrastructure quality. This theoretical framework provides a robust method for assessing and improving secondary schools efficiency within Ghana's educational policy landscape. The model can be used to inform future policy decisions by identifying areas where investment is most likely to lead to significant improvements in student outcomes. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.