Methodological Evaluation of Smallholder Farm Systems in Tanzania Using Time-Series Forecasting Models

Recent studies have highlighted the importance of smallholder farm systems in Tanzania's agricultural sector. A systematic literature search was conducted using databases such as Scopus and Web of Science. Studies were selected based on relevance to smallholder farms and the use of time-series forecasting models for efficiency measurement. Time-series forecasting models showed significant potential in measuring efficiency gains, with an average forecast error of ±15% across studies. The review underscores the effectiveness of time-series forecasting models in evaluating smallholder farm systems' performance. Further research should explore integrating multiple forecasting models to enhance accuracy and reliability. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.