We use recruitment into a laboratory experiment in Kolkata, India to analyze how social networks select individuals for jobs. The experiment allows subjects to refer actual network members for casual jobs as experimental subjects under exogenously varied incentive contracts. We provide evidence that some workers, those who are high ability, have useful information about the abilities of members of their social network. However, the experiment also shows that social networks provide incentives to refer less qualified workers, and firms must counterbalance these incentives in order to effectively use existing employees to help overcome their screening problem.

Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence of one explanation for why centrality matters: a diffusion process governed by complex contagion. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low.

We conducted an experiment providing fertilizer grants to female rice farmers in Mali. We found that women who received fertilizer used both more fertilizer and more complementary inputs such as herbicides and hired labor. This shows that farmers respond to an increase in one input by re-optimizing other inputs. Second, while the increase in inputs led to a considerable increase in output, we found no evidence that profits increased. Our results suggest that fertilizer's impact on profits is small compared to other sources of variation. This may make it difficult for farmers to learn about the returns to fertilizer.