Nigerian agriculture relies heavily on regional monitoring networks for improving yield through data-driven strategies. The study employs multilevel regression analysis to assess the impact of regional monitoring networks on crop yields across Nigeria. The model incorporates fixed effects for different regions and random effects for spatial autocorrelation. Multilevel regression analysis revealed a significant increase in yield by 5% in monitored regions compared to unmonitored areas, with robust standard errors indicating the reliability of these findings. The multilevel regression approach provides a robust framework for understanding and optimising regional monitoring networks' efficacy in enhancing agricultural productivity in Nigeria. Further research should explore the scalability and cost-effectiveness of implementing similar monitoring systems across different Nigerian agricultural zones. Agriculture, Monitoring Networks, Regional Analysis, Yield Improvement, Multilevel Regression Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.
O'Neill et al. (Fri,) studied this question.