Regional monitoring networks in Nigeria have been established to enhance agricultural productivity and resilience against climate-related risks. A multilevel regression model was employed to analyse data from multiple levels including farmers' responses and climate variability. The model accounts for both fixed effects (system design) and random effects (site-specific variations). The analysis revealed that improved irrigation practices significantly reduced crop failure risk by an average of 25% across monitored sites, indicating the positive impact of system interventions. Multilevel regression analysis provided valuable insights into the effectiveness of regional monitoring networks in enhancing agricultural resilience, particularly through targeted agricultural interventions. Future studies should focus on scaling up successful practices and integrating more sophisticated climate forecasting models to improve risk management strategies. The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Nwankwo et al. (2014) studied this question.