In Kenya, agricultural productivity is influenced by various process-control systems used in farming practices. These systems aim to optimise yield and resource utilization. A DiD analysis was conducted, applying econometric techniques to compare pre- and post-intervention periods in various districts. Data on crop yields and input usage were collected from agricultural extension services. The DiD model revealed an average increase of 15% in maize yield across the study area with a confidence interval of ±3 percentage points, indicating significant improvements due to the control systems. This research supports the efficacy of process-control systems in enhancing agricultural productivity in Kenya. The findings suggest that targeted interventions could further boost yields. Further studies should explore the long-term impacts and scalability of these systems across diverse crop types and farming contexts. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Kinyanjui et al. (Sat,) studied this question.