Endogenous Technology Adoption, Social Learning, and Spatial Diffusion of Improved Maize Varieties in North Central Nigeria

Technology diffusion in agricultural systems is shaped by complex social networks, spatial proximity, and information externalities that are inadequately captured by standard adoption models treating individual farmer decisions as independent. This study develops a spatially explicit model of social learning and technology diffusion and applies it to the adoption of improved maize varieties across farming communities in Niger, Kogi, and Benue States in Nigeria's North Central geopolitical zone. The theoretical framework integrates Bayesian social learning with spatial econometrics, generating testable predictions about the spatial autocorrelation of adoption decisions and the role of network centrality in accelerating diffusion. A primary dataset of 480 farm households with detailed information on social network composition, adoption history, and plot-level outcomes was collected. Spatial weight matrices capturing geographic and social proximity were constructed. A spatial autoregressive adoption model was estimated alongside peer effects regressions using community-level variation in early adopter density as an instrument. Results confirm significant spatial clustering of adoption, with adoption probability increasing by 14 percentage points for each 10 percent increase in the proportion of adopters within a two-kilometre radius. Social learning effects are strongest through demonstration on visible plots and farmer field school platforms. Network bridgers, defined as farmers with cross-community connections, generate larger diffusion multipliers than network hubs. The study makes a theoretical contribution by integrating endogenous network formation into the technology diffusion model and provides novel evidence for the design of spatially targeted extension campaigns in North Central Nigeria. Keywords: technology diffusion, social learning, spatial econometrics, improved maize, North Central Nigeria