Methodological Evaluation of Off-Grid Communities Systems in Uganda Using Time-Series Forecasting Modelsfor Cost-Effectiveness Analysis

Off-grid communities in Uganda face significant challenges in accessing reliable energy sources for agricultural productivity. A systematic literature review was conducted, focusing on methodologies applied in studies evaluating the cost-effectiveness of off-grid energy solutions for agriculture. Time-series forecasting models were identified as a primary tool for analysis. The review highlighted the use of ARIMA (AutoRegressive Integrated Moving Average) model in predicting future costs and returns with reasonable accuracy, though variability existed across different time horizons and data sets. Time-series forecasting models can effectively measure cost-effectiveness of off-grid systems but require careful selection based on specific agricultural contexts to ensure robust predictions. Researchers should consider incorporating more diverse datasets to enhance model generalizability and include sensitivity analyses to account for uncertainties. Off-Grid Communities, Cost-Effectiveness Analysis, Time-Series Forecasting, ARIMA Model, Agricultural Productivity The empirical specification follows Y=β₀+β^ X+ε, and inference is reported with uncertainty-aware statistical criteria.