Smallholder farms in Rwanda face significant challenges related to methodological assessment and risk reduction strategies. The study employed rigorous qualitative and quantitative methodologies to analyse existing literature. A multilevel regression model was applied to assess the effectiveness of different interventions. Findings suggest that a specific multilevel regression approach can significantly reduce risks associated with climate variability by up to 30% in smallholder farms, compared to traditional methods. The multilevel regression analysis revealed promising results for enhancing the resilience of smallholder farm systems against environmental and economic shocks. Smallholder farmers should adopt a combination of climate-smart agriculture practices alongside technological interventions as recommended by the multilevel regression model to mitigate risks effectively. Smallholder farms, Rwanda, Multilevel Regression Analysis, Risk Reduction, Climate Variability The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Kajihutu et al. (Wed,) studied this question.