Researchers generally assume spatial homogeneity when assessing the factors that influence farmers to adopt improved agricultural technologies. However, the potential for spatial heterogeneity is high due to, for example, neighborhood effects such as farmers sharing information about new technology. Ignoring spatial heterogeneity can result in biased or inefficient regression estimates and make inferences based on t and F statistics misleading. Using data collected from 300 randomly selected farmers in three districts of Mozambique during the 2003/04 crop season, a spatial Tobit model was specified to estimate which factors determined the adoption of improved maize varieties, after an initial diagnostic test rejected the null hypothesis of spatial... |