This paper examines the impact of social networks and peer effects on the adoption of agricultural innovations in Northern Mozambique, using a unique dataset on sunflower adoption. The authors analyze whether and how individual adoption decisions depend on the choices of others in their social networks. They find that the relationship between the probability of adoption and the number of known adopters follows an inverse-U shape, meaning that the marginal benefit of knowing one more adopter is positive when the farmer knows few other adopters but becomes negative when the farmer knows many. This suggests that while information sharing is important, knowing many adopters might lead to strategic delays in adoption to free-ride on the information gathered by others. The study also highlights the importance of controlling for village heterogeneity and endogenous group formation, which are not typically addressed in previous literature. The findings have implications for understanding the diffusion of agricultural innovations and the role of social networks in economic development.This paper examines the impact of social networks and peer effects on the adoption of agricultural innovations in Northern Mozambique, using a unique dataset on sunflower adoption. The authors analyze whether and how individual adoption decisions depend on the choices of others in their social networks. They find that the relationship between the probability of adoption and the number of known adopters follows an inverse-U shape, meaning that the marginal benefit of knowing one more adopter is positive when the farmer knows few other adopters but becomes negative when the farmer knows many. This suggests that while information sharing is important, knowing many adopters might lead to strategic delays in adoption to free-ride on the information gathered by others. The study also highlights the importance of controlling for village heterogeneity and endogenous group formation, which are not typically addressed in previous literature. The findings have implications for understanding the diffusion of agricultural innovations and the role of social networks in economic development.